1 //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 //
9 // This pass implements the Bottom Up SLP vectorizer. It detects consecutive
10 // stores that can be put together into vector-stores. Next, it attempts to
11 // construct vectorizable tree using the use-def chains. If a profitable tree
12 // was found, the SLP vectorizer performs vectorization on the tree.
13 //
14 // The pass is inspired by the work described in the paper:
15 // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks.
16 //
17 //===----------------------------------------------------------------------===//
18
19 #include "llvm/Transforms/Vectorize/SLPVectorizer.h"
20 #include "llvm/ADT/ArrayRef.h"
21 #include "llvm/ADT/DenseMap.h"
22 #include "llvm/ADT/DenseSet.h"
23 #include "llvm/ADT/MapVector.h"
24 #include "llvm/ADT/None.h"
25 #include "llvm/ADT/Optional.h"
26 #include "llvm/ADT/PostOrderIterator.h"
27 #include "llvm/ADT/STLExtras.h"
28 #include "llvm/ADT/SetVector.h"
29 #include "llvm/ADT/SmallBitVector.h"
30 #include "llvm/ADT/SmallPtrSet.h"
31 #include "llvm/ADT/SmallSet.h"
32 #include "llvm/ADT/SmallVector.h"
33 #include "llvm/ADT/Statistic.h"
34 #include "llvm/ADT/iterator.h"
35 #include "llvm/ADT/iterator_range.h"
36 #include "llvm/Analysis/AliasAnalysis.h"
37 #include "llvm/Analysis/CodeMetrics.h"
38 #include "llvm/Analysis/DemandedBits.h"
39 #include "llvm/Analysis/GlobalsModRef.h"
40 #include "llvm/Analysis/LoopAccessAnalysis.h"
41 #include "llvm/Analysis/LoopInfo.h"
42 #include "llvm/Analysis/MemoryLocation.h"
43 #include "llvm/Analysis/OptimizationRemarkEmitter.h"
44 #include "llvm/Analysis/ScalarEvolution.h"
45 #include "llvm/Analysis/ScalarEvolutionExpressions.h"
46 #include "llvm/Analysis/TargetLibraryInfo.h"
47 #include "llvm/Analysis/TargetTransformInfo.h"
48 #include "llvm/Analysis/ValueTracking.h"
49 #include "llvm/Analysis/VectorUtils.h"
50 #include "llvm/IR/Attributes.h"
51 #include "llvm/IR/BasicBlock.h"
52 #include "llvm/IR/Constant.h"
53 #include "llvm/IR/Constants.h"
54 #include "llvm/IR/DataLayout.h"
55 #include "llvm/IR/DebugLoc.h"
56 #include "llvm/IR/DerivedTypes.h"
57 #include "llvm/IR/Dominators.h"
58 #include "llvm/IR/Function.h"
59 #include "llvm/IR/IRBuilder.h"
60 #include "llvm/IR/InstrTypes.h"
61 #include "llvm/IR/Instruction.h"
62 #include "llvm/IR/Instructions.h"
63 #include "llvm/IR/IntrinsicInst.h"
64 #include "llvm/IR/Intrinsics.h"
65 #include "llvm/IR/Module.h"
66 #include "llvm/IR/NoFolder.h"
67 #include "llvm/IR/Operator.h"
68 #include "llvm/IR/PassManager.h"
69 #include "llvm/IR/PatternMatch.h"
70 #include "llvm/IR/Type.h"
71 #include "llvm/IR/Use.h"
72 #include "llvm/IR/User.h"
73 #include "llvm/IR/Value.h"
74 #include "llvm/IR/ValueHandle.h"
75 #include "llvm/IR/Verifier.h"
76 #include "llvm/InitializePasses.h"
77 #include "llvm/Pass.h"
78 #include "llvm/Support/Casting.h"
79 #include "llvm/Support/CommandLine.h"
80 #include "llvm/Support/Compiler.h"
81 #include "llvm/Support/DOTGraphTraits.h"
82 #include "llvm/Support/Debug.h"
83 #include "llvm/Support/ErrorHandling.h"
84 #include "llvm/Support/GraphWriter.h"
85 #include "llvm/Support/KnownBits.h"
86 #include "llvm/Support/MathExtras.h"
87 #include "llvm/Support/raw_ostream.h"
88 #include "llvm/Transforms/Utils/LoopUtils.h"
89 #include "llvm/Transforms/Vectorize.h"
90 #include <algorithm>
91 #include <cassert>
92 #include <cstdint>
93 #include <iterator>
94 #include <memory>
95 #include <set>
96 #include <string>
97 #include <tuple>
98 #include <utility>
99 #include <vector>
100
101 using namespace llvm;
102 using namespace llvm::PatternMatch;
103 using namespace slpvectorizer;
104
105 #define SV_NAME "slp-vectorizer"
106 #define DEBUG_TYPE "SLP"
107
108 STATISTIC(NumVectorInstructions, "Number of vector instructions generated");
109
110 cl::opt<bool>
111 llvm::RunSLPVectorization("vectorize-slp", cl::init(false), cl::Hidden,
112 cl::desc("Run the SLP vectorization passes"));
113
114 static cl::opt<int>
115 SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden,
116 cl::desc("Only vectorize if you gain more than this "
117 "number "));
118
119 static cl::opt<bool>
120 ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden,
121 cl::desc("Attempt to vectorize horizontal reductions"));
122
123 static cl::opt<bool> ShouldStartVectorizeHorAtStore(
124 "slp-vectorize-hor-store", cl::init(false), cl::Hidden,
125 cl::desc(
126 "Attempt to vectorize horizontal reductions feeding into a store"));
127
128 static cl::opt<int>
129 MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden,
130 cl::desc("Attempt to vectorize for this register size in bits"));
131
132 static cl::opt<int>
133 MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden,
134 cl::desc("Maximum depth of the lookup for consecutive stores."));
135
136 /// Limits the size of scheduling regions in a block.
137 /// It avoid long compile times for _very_ large blocks where vector
138 /// instructions are spread over a wide range.
139 /// This limit is way higher than needed by real-world functions.
140 static cl::opt<int>
141 ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden,
142 cl::desc("Limit the size of the SLP scheduling region per block"));
143
144 static cl::opt<int> MinVectorRegSizeOption(
145 "slp-min-reg-size", cl::init(128), cl::Hidden,
146 cl::desc("Attempt to vectorize for this register size in bits"));
147
148 static cl::opt<unsigned> RecursionMaxDepth(
149 "slp-recursion-max-depth", cl::init(12), cl::Hidden,
150 cl::desc("Limit the recursion depth when building a vectorizable tree"));
151
152 static cl::opt<unsigned> MinTreeSize(
153 "slp-min-tree-size", cl::init(3), cl::Hidden,
154 cl::desc("Only vectorize small trees if they are fully vectorizable"));
155
156 // The maximum depth that the look-ahead score heuristic will explore.
157 // The higher this value, the higher the compilation time overhead.
158 static cl::opt<int> LookAheadMaxDepth(
159 "slp-max-look-ahead-depth", cl::init(2), cl::Hidden,
160 cl::desc("The maximum look-ahead depth for operand reordering scores"));
161
162 // The Look-ahead heuristic goes through the users of the bundle to calculate
163 // the users cost in getExternalUsesCost(). To avoid compilation time increase
164 // we limit the number of users visited to this value.
165 static cl::opt<unsigned> LookAheadUsersBudget(
166 "slp-look-ahead-users-budget", cl::init(2), cl::Hidden,
167 cl::desc("The maximum number of users to visit while visiting the "
168 "predecessors. This prevents compilation time increase."));
169
170 static cl::opt<bool>
171 ViewSLPTree("view-slp-tree", cl::Hidden,
172 cl::desc("Display the SLP trees with Graphviz"));
173
174 // Limit the number of alias checks. The limit is chosen so that
175 // it has no negative effect on the llvm benchmarks.
176 static const unsigned AliasedCheckLimit = 10;
177
178 // Another limit for the alias checks: The maximum distance between load/store
179 // instructions where alias checks are done.
180 // This limit is useful for very large basic blocks.
181 static const unsigned MaxMemDepDistance = 160;
182
183 /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling
184 /// regions to be handled.
185 static const int MinScheduleRegionSize = 16;
186
187 /// Predicate for the element types that the SLP vectorizer supports.
188 ///
189 /// The most important thing to filter here are types which are invalid in LLVM
190 /// vectors. We also filter target specific types which have absolutely no
191 /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just
192 /// avoids spending time checking the cost model and realizing that they will
193 /// be inevitably scalarized.
isValidElementType(Type * Ty)194 static bool isValidElementType(Type *Ty) {
195 return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() &&
196 !Ty->isPPC_FP128Ty();
197 }
198
199 /// \returns true if all of the instructions in \p VL are in the same block or
200 /// false otherwise.
allSameBlock(ArrayRef<Value * > VL)201 static bool allSameBlock(ArrayRef<Value *> VL) {
202 Instruction *I0 = dyn_cast<Instruction>(VL[0]);
203 if (!I0)
204 return false;
205 BasicBlock *BB = I0->getParent();
206 for (int i = 1, e = VL.size(); i < e; i++) {
207 Instruction *I = dyn_cast<Instruction>(VL[i]);
208 if (!I)
209 return false;
210
211 if (BB != I->getParent())
212 return false;
213 }
214 return true;
215 }
216
217 /// \returns True if all of the values in \p VL are constants (but not
218 /// globals/constant expressions).
allConstant(ArrayRef<Value * > VL)219 static bool allConstant(ArrayRef<Value *> VL) {
220 // Constant expressions and globals can't be vectorized like normal integer/FP
221 // constants.
222 for (Value *i : VL)
223 if (!isa<Constant>(i) || isa<ConstantExpr>(i) || isa<GlobalValue>(i))
224 return false;
225 return true;
226 }
227
228 /// \returns True if all of the values in \p VL are identical.
isSplat(ArrayRef<Value * > VL)229 static bool isSplat(ArrayRef<Value *> VL) {
230 for (unsigned i = 1, e = VL.size(); i < e; ++i)
231 if (VL[i] != VL[0])
232 return false;
233 return true;
234 }
235
236 /// \returns True if \p I is commutative, handles CmpInst as well as Instruction.
isCommutative(Instruction * I)237 static bool isCommutative(Instruction *I) {
238 if (auto *IC = dyn_cast<CmpInst>(I))
239 return IC->isCommutative();
240 return I->isCommutative();
241 }
242
243 /// Checks if the vector of instructions can be represented as a shuffle, like:
244 /// %x0 = extractelement <4 x i8> %x, i32 0
245 /// %x3 = extractelement <4 x i8> %x, i32 3
246 /// %y1 = extractelement <4 x i8> %y, i32 1
247 /// %y2 = extractelement <4 x i8> %y, i32 2
248 /// %x0x0 = mul i8 %x0, %x0
249 /// %x3x3 = mul i8 %x3, %x3
250 /// %y1y1 = mul i8 %y1, %y1
251 /// %y2y2 = mul i8 %y2, %y2
252 /// %ins1 = insertelement <4 x i8> undef, i8 %x0x0, i32 0
253 /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1
254 /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2
255 /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3
256 /// ret <4 x i8> %ins4
257 /// can be transformed into:
258 /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5,
259 /// i32 6>
260 /// %2 = mul <4 x i8> %1, %1
261 /// ret <4 x i8> %2
262 /// We convert this initially to something like:
263 /// %x0 = extractelement <4 x i8> %x, i32 0
264 /// %x3 = extractelement <4 x i8> %x, i32 3
265 /// %y1 = extractelement <4 x i8> %y, i32 1
266 /// %y2 = extractelement <4 x i8> %y, i32 2
267 /// %1 = insertelement <4 x i8> undef, i8 %x0, i32 0
268 /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1
269 /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2
270 /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3
271 /// %5 = mul <4 x i8> %4, %4
272 /// %6 = extractelement <4 x i8> %5, i32 0
273 /// %ins1 = insertelement <4 x i8> undef, i8 %6, i32 0
274 /// %7 = extractelement <4 x i8> %5, i32 1
275 /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1
276 /// %8 = extractelement <4 x i8> %5, i32 2
277 /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2
278 /// %9 = extractelement <4 x i8> %5, i32 3
279 /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3
280 /// ret <4 x i8> %ins4
281 /// InstCombiner transforms this into a shuffle and vector mul
282 /// TODO: Can we split off and reuse the shuffle mask detection from
283 /// TargetTransformInfo::getInstructionThroughput?
284 static Optional<TargetTransformInfo::ShuffleKind>
isShuffle(ArrayRef<Value * > VL)285 isShuffle(ArrayRef<Value *> VL) {
286 auto *EI0 = cast<ExtractElementInst>(VL[0]);
287 unsigned Size = EI0->getVectorOperandType()->getVectorNumElements();
288 Value *Vec1 = nullptr;
289 Value *Vec2 = nullptr;
290 enum ShuffleMode { Unknown, Select, Permute };
291 ShuffleMode CommonShuffleMode = Unknown;
292 for (unsigned I = 0, E = VL.size(); I < E; ++I) {
293 auto *EI = cast<ExtractElementInst>(VL[I]);
294 auto *Vec = EI->getVectorOperand();
295 // All vector operands must have the same number of vector elements.
296 if (Vec->getType()->getVectorNumElements() != Size)
297 return None;
298 auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand());
299 if (!Idx)
300 return None;
301 // Undefined behavior if Idx is negative or >= Size.
302 if (Idx->getValue().uge(Size))
303 continue;
304 unsigned IntIdx = Idx->getValue().getZExtValue();
305 // We can extractelement from undef vector.
306 if (isa<UndefValue>(Vec))
307 continue;
308 // For correct shuffling we have to have at most 2 different vector operands
309 // in all extractelement instructions.
310 if (!Vec1 || Vec1 == Vec)
311 Vec1 = Vec;
312 else if (!Vec2 || Vec2 == Vec)
313 Vec2 = Vec;
314 else
315 return None;
316 if (CommonShuffleMode == Permute)
317 continue;
318 // If the extract index is not the same as the operation number, it is a
319 // permutation.
320 if (IntIdx != I) {
321 CommonShuffleMode = Permute;
322 continue;
323 }
324 CommonShuffleMode = Select;
325 }
326 // If we're not crossing lanes in different vectors, consider it as blending.
327 if (CommonShuffleMode == Select && Vec2)
328 return TargetTransformInfo::SK_Select;
329 // If Vec2 was never used, we have a permutation of a single vector, otherwise
330 // we have permutation of 2 vectors.
331 return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc
332 : TargetTransformInfo::SK_PermuteSingleSrc;
333 }
334
335 namespace {
336
337 /// Main data required for vectorization of instructions.
338 struct InstructionsState {
339 /// The very first instruction in the list with the main opcode.
340 Value *OpValue = nullptr;
341
342 /// The main/alternate instruction.
343 Instruction *MainOp = nullptr;
344 Instruction *AltOp = nullptr;
345
346 /// The main/alternate opcodes for the list of instructions.
getOpcode__anoncd21379e0111::InstructionsState347 unsigned getOpcode() const {
348 return MainOp ? MainOp->getOpcode() : 0;
349 }
350
getAltOpcode__anoncd21379e0111::InstructionsState351 unsigned getAltOpcode() const {
352 return AltOp ? AltOp->getOpcode() : 0;
353 }
354
355 /// Some of the instructions in the list have alternate opcodes.
isAltShuffle__anoncd21379e0111::InstructionsState356 bool isAltShuffle() const { return getOpcode() != getAltOpcode(); }
357
isOpcodeOrAlt__anoncd21379e0111::InstructionsState358 bool isOpcodeOrAlt(Instruction *I) const {
359 unsigned CheckedOpcode = I->getOpcode();
360 return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode;
361 }
362
363 InstructionsState() = delete;
InstructionsState__anoncd21379e0111::InstructionsState364 InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp)
365 : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {}
366 };
367
368 } // end anonymous namespace
369
370 /// Chooses the correct key for scheduling data. If \p Op has the same (or
371 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p
372 /// OpValue.
isOneOf(const InstructionsState & S,Value * Op)373 static Value *isOneOf(const InstructionsState &S, Value *Op) {
374 auto *I = dyn_cast<Instruction>(Op);
375 if (I && S.isOpcodeOrAlt(I))
376 return Op;
377 return S.OpValue;
378 }
379
380 /// \returns true if \p Opcode is allowed as part of of the main/alternate
381 /// instruction for SLP vectorization.
382 ///
383 /// Example of unsupported opcode is SDIV that can potentially cause UB if the
384 /// "shuffled out" lane would result in division by zero.
isValidForAlternation(unsigned Opcode)385 static bool isValidForAlternation(unsigned Opcode) {
386 if (Instruction::isIntDivRem(Opcode))
387 return false;
388
389 return true;
390 }
391
392 /// \returns analysis of the Instructions in \p VL described in
393 /// InstructionsState, the Opcode that we suppose the whole list
394 /// could be vectorized even if its structure is diverse.
getSameOpcode(ArrayRef<Value * > VL,unsigned BaseIndex=0)395 static InstructionsState getSameOpcode(ArrayRef<Value *> VL,
396 unsigned BaseIndex = 0) {
397 // Make sure these are all Instructions.
398 if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); }))
399 return InstructionsState(VL[BaseIndex], nullptr, nullptr);
400
401 bool IsCastOp = isa<CastInst>(VL[BaseIndex]);
402 bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]);
403 unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode();
404 unsigned AltOpcode = Opcode;
405 unsigned AltIndex = BaseIndex;
406
407 // Check for one alternate opcode from another BinaryOperator.
408 // TODO - generalize to support all operators (types, calls etc.).
409 for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) {
410 unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode();
411 if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) {
412 if (InstOpcode == Opcode || InstOpcode == AltOpcode)
413 continue;
414 if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) &&
415 isValidForAlternation(Opcode)) {
416 AltOpcode = InstOpcode;
417 AltIndex = Cnt;
418 continue;
419 }
420 } else if (IsCastOp && isa<CastInst>(VL[Cnt])) {
421 Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType();
422 Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType();
423 if (Ty0 == Ty1) {
424 if (InstOpcode == Opcode || InstOpcode == AltOpcode)
425 continue;
426 if (Opcode == AltOpcode) {
427 assert(isValidForAlternation(Opcode) &&
428 isValidForAlternation(InstOpcode) &&
429 "Cast isn't safe for alternation, logic needs to be updated!");
430 AltOpcode = InstOpcode;
431 AltIndex = Cnt;
432 continue;
433 }
434 }
435 } else if (InstOpcode == Opcode || InstOpcode == AltOpcode)
436 continue;
437 return InstructionsState(VL[BaseIndex], nullptr, nullptr);
438 }
439
440 return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]),
441 cast<Instruction>(VL[AltIndex]));
442 }
443
444 /// \returns true if all of the values in \p VL have the same type or false
445 /// otherwise.
allSameType(ArrayRef<Value * > VL)446 static bool allSameType(ArrayRef<Value *> VL) {
447 Type *Ty = VL[0]->getType();
448 for (int i = 1, e = VL.size(); i < e; i++)
449 if (VL[i]->getType() != Ty)
450 return false;
451
452 return true;
453 }
454
455 /// \returns True if Extract{Value,Element} instruction extracts element Idx.
getExtractIndex(Instruction * E)456 static Optional<unsigned> getExtractIndex(Instruction *E) {
457 unsigned Opcode = E->getOpcode();
458 assert((Opcode == Instruction::ExtractElement ||
459 Opcode == Instruction::ExtractValue) &&
460 "Expected extractelement or extractvalue instruction.");
461 if (Opcode == Instruction::ExtractElement) {
462 auto *CI = dyn_cast<ConstantInt>(E->getOperand(1));
463 if (!CI)
464 return None;
465 return CI->getZExtValue();
466 }
467 ExtractValueInst *EI = cast<ExtractValueInst>(E);
468 if (EI->getNumIndices() != 1)
469 return None;
470 return *EI->idx_begin();
471 }
472
473 /// \returns True if in-tree use also needs extract. This refers to
474 /// possible scalar operand in vectorized instruction.
InTreeUserNeedToExtract(Value * Scalar,Instruction * UserInst,TargetLibraryInfo * TLI)475 static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst,
476 TargetLibraryInfo *TLI) {
477 unsigned Opcode = UserInst->getOpcode();
478 switch (Opcode) {
479 case Instruction::Load: {
480 LoadInst *LI = cast<LoadInst>(UserInst);
481 return (LI->getPointerOperand() == Scalar);
482 }
483 case Instruction::Store: {
484 StoreInst *SI = cast<StoreInst>(UserInst);
485 return (SI->getPointerOperand() == Scalar);
486 }
487 case Instruction::Call: {
488 CallInst *CI = cast<CallInst>(UserInst);
489 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
490 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) {
491 if (hasVectorInstrinsicScalarOpd(ID, i))
492 return (CI->getArgOperand(i) == Scalar);
493 }
494 LLVM_FALLTHROUGH;
495 }
496 default:
497 return false;
498 }
499 }
500
501 /// \returns the AA location that is being access by the instruction.
getLocation(Instruction * I,AliasAnalysis * AA)502 static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) {
503 if (StoreInst *SI = dyn_cast<StoreInst>(I))
504 return MemoryLocation::get(SI);
505 if (LoadInst *LI = dyn_cast<LoadInst>(I))
506 return MemoryLocation::get(LI);
507 return MemoryLocation();
508 }
509
510 /// \returns True if the instruction is not a volatile or atomic load/store.
isSimple(Instruction * I)511 static bool isSimple(Instruction *I) {
512 if (LoadInst *LI = dyn_cast<LoadInst>(I))
513 return LI->isSimple();
514 if (StoreInst *SI = dyn_cast<StoreInst>(I))
515 return SI->isSimple();
516 if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I))
517 return !MI->isVolatile();
518 return true;
519 }
520
521 namespace llvm {
522
523 namespace slpvectorizer {
524
525 /// Bottom Up SLP Vectorizer.
526 class BoUpSLP {
527 struct TreeEntry;
528 struct ScheduleData;
529
530 public:
531 using ValueList = SmallVector<Value *, 8>;
532 using InstrList = SmallVector<Instruction *, 16>;
533 using ValueSet = SmallPtrSet<Value *, 16>;
534 using StoreList = SmallVector<StoreInst *, 8>;
535 using ExtraValueToDebugLocsMap =
536 MapVector<Value *, SmallVector<Instruction *, 2>>;
537
BoUpSLP(Function * Func,ScalarEvolution * Se,TargetTransformInfo * Tti,TargetLibraryInfo * TLi,AliasAnalysis * Aa,LoopInfo * Li,DominatorTree * Dt,AssumptionCache * AC,DemandedBits * DB,const DataLayout * DL,OptimizationRemarkEmitter * ORE)538 BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti,
539 TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li,
540 DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB,
541 const DataLayout *DL, OptimizationRemarkEmitter *ORE)
542 : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC),
543 DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) {
544 CodeMetrics::collectEphemeralValues(F, AC, EphValues);
545 // Use the vector register size specified by the target unless overridden
546 // by a command-line option.
547 // TODO: It would be better to limit the vectorization factor based on
548 // data type rather than just register size. For example, x86 AVX has
549 // 256-bit registers, but it does not support integer operations
550 // at that width (that requires AVX2).
551 if (MaxVectorRegSizeOption.getNumOccurrences())
552 MaxVecRegSize = MaxVectorRegSizeOption;
553 else
554 MaxVecRegSize = TTI->getRegisterBitWidth(true);
555
556 if (MinVectorRegSizeOption.getNumOccurrences())
557 MinVecRegSize = MinVectorRegSizeOption;
558 else
559 MinVecRegSize = TTI->getMinVectorRegisterBitWidth();
560 }
561
562 /// Vectorize the tree that starts with the elements in \p VL.
563 /// Returns the vectorized root.
564 Value *vectorizeTree();
565
566 /// Vectorize the tree but with the list of externally used values \p
567 /// ExternallyUsedValues. Values in this MapVector can be replaced but the
568 /// generated extractvalue instructions.
569 Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues);
570
571 /// \returns the cost incurred by unwanted spills and fills, caused by
572 /// holding live values over call sites.
573 int getSpillCost() const;
574
575 /// \returns the vectorization cost of the subtree that starts at \p VL.
576 /// A negative number means that this is profitable.
577 int getTreeCost();
578
579 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for
580 /// the purpose of scheduling and extraction in the \p UserIgnoreLst.
581 void buildTree(ArrayRef<Value *> Roots,
582 ArrayRef<Value *> UserIgnoreLst = None);
583
584 /// Construct a vectorizable tree that starts at \p Roots, ignoring users for
585 /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking
586 /// into account (and updating it, if required) list of externally used
587 /// values stored in \p ExternallyUsedValues.
588 void buildTree(ArrayRef<Value *> Roots,
589 ExtraValueToDebugLocsMap &ExternallyUsedValues,
590 ArrayRef<Value *> UserIgnoreLst = None);
591
592 /// Clear the internal data structures that are created by 'buildTree'.
deleteTree()593 void deleteTree() {
594 VectorizableTree.clear();
595 ScalarToTreeEntry.clear();
596 MustGather.clear();
597 ExternalUses.clear();
598 NumOpsWantToKeepOrder.clear();
599 NumOpsWantToKeepOriginalOrder = 0;
600 for (auto &Iter : BlocksSchedules) {
601 BlockScheduling *BS = Iter.second.get();
602 BS->clear();
603 }
604 MinBWs.clear();
605 }
606
getTreeSize() const607 unsigned getTreeSize() const { return VectorizableTree.size(); }
608
609 /// Perform LICM and CSE on the newly generated gather sequences.
610 void optimizeGatherSequence();
611
612 /// \returns The best order of instructions for vectorization.
bestOrder() const613 Optional<ArrayRef<unsigned>> bestOrder() const {
614 auto I = std::max_element(
615 NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(),
616 [](const decltype(NumOpsWantToKeepOrder)::value_type &D1,
617 const decltype(NumOpsWantToKeepOrder)::value_type &D2) {
618 return D1.second < D2.second;
619 });
620 if (I == NumOpsWantToKeepOrder.end() ||
621 I->getSecond() <= NumOpsWantToKeepOriginalOrder)
622 return None;
623
624 return makeArrayRef(I->getFirst());
625 }
626
627 /// \return The vector element size in bits to use when vectorizing the
628 /// expression tree ending at \p V. If V is a store, the size is the width of
629 /// the stored value. Otherwise, the size is the width of the largest loaded
630 /// value reaching V. This method is used by the vectorizer to calculate
631 /// vectorization factors.
632 unsigned getVectorElementSize(Value *V) const;
633
634 /// Compute the minimum type sizes required to represent the entries in a
635 /// vectorizable tree.
636 void computeMinimumValueSizes();
637
638 // \returns maximum vector register size as set by TTI or overridden by cl::opt.
getMaxVecRegSize() const639 unsigned getMaxVecRegSize() const {
640 return MaxVecRegSize;
641 }
642
643 // \returns minimum vector register size as set by cl::opt.
getMinVecRegSize() const644 unsigned getMinVecRegSize() const {
645 return MinVecRegSize;
646 }
647
648 /// Check if homogeneous aggregate is isomorphic to some VectorType.
649 /// Accepts homogeneous multidimensional aggregate of scalars/vectors like
650 /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> },
651 /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on.
652 ///
653 /// \returns number of elements in vector if isomorphism exists, 0 otherwise.
654 unsigned canMapToVector(Type *T, const DataLayout &DL) const;
655
656 /// \returns True if the VectorizableTree is both tiny and not fully
657 /// vectorizable. We do not vectorize such trees.
658 bool isTreeTinyAndNotFullyVectorizable() const;
659
660 /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values
661 /// can be load combined in the backend. Load combining may not be allowed in
662 /// the IR optimizer, so we do not want to alter the pattern. For example,
663 /// partially transforming a scalar bswap() pattern into vector code is
664 /// effectively impossible for the backend to undo.
665 /// TODO: If load combining is allowed in the IR optimizer, this analysis
666 /// may not be necessary.
667 bool isLoadCombineReductionCandidate(unsigned ReductionOpcode) const;
668
getORE()669 OptimizationRemarkEmitter *getORE() { return ORE; }
670
671 /// This structure holds any data we need about the edges being traversed
672 /// during buildTree_rec(). We keep track of:
673 /// (i) the user TreeEntry index, and
674 /// (ii) the index of the edge.
675 struct EdgeInfo {
676 EdgeInfo() = default;
EdgeInfollvm::slpvectorizer::BoUpSLP::EdgeInfo677 EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx)
678 : UserTE(UserTE), EdgeIdx(EdgeIdx) {}
679 /// The user TreeEntry.
680 TreeEntry *UserTE = nullptr;
681 /// The operand index of the use.
682 unsigned EdgeIdx = UINT_MAX;
683 #ifndef NDEBUG
operator <<(raw_ostream & OS,const BoUpSLP::EdgeInfo & EI)684 friend inline raw_ostream &operator<<(raw_ostream &OS,
685 const BoUpSLP::EdgeInfo &EI) {
686 EI.dump(OS);
687 return OS;
688 }
689 /// Debug print.
dumpllvm::slpvectorizer::BoUpSLP::EdgeInfo690 void dump(raw_ostream &OS) const {
691 OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null")
692 << " EdgeIdx:" << EdgeIdx << "}";
693 }
dumpllvm::slpvectorizer::BoUpSLP::EdgeInfo694 LLVM_DUMP_METHOD void dump() const { dump(dbgs()); }
695 #endif
696 };
697
698 /// A helper data structure to hold the operands of a vector of instructions.
699 /// This supports a fixed vector length for all operand vectors.
700 class VLOperands {
701 /// For each operand we need (i) the value, and (ii) the opcode that it
702 /// would be attached to if the expression was in a left-linearized form.
703 /// This is required to avoid illegal operand reordering.
704 /// For example:
705 /// \verbatim
706 /// 0 Op1
707 /// |/
708 /// Op1 Op2 Linearized + Op2
709 /// \ / ----------> |/
710 /// - -
711 ///
712 /// Op1 - Op2 (0 + Op1) - Op2
713 /// \endverbatim
714 ///
715 /// Value Op1 is attached to a '+' operation, and Op2 to a '-'.
716 ///
717 /// Another way to think of this is to track all the operations across the
718 /// path from the operand all the way to the root of the tree and to
719 /// calculate the operation that corresponds to this path. For example, the
720 /// path from Op2 to the root crosses the RHS of the '-', therefore the
721 /// corresponding operation is a '-' (which matches the one in the
722 /// linearized tree, as shown above).
723 ///
724 /// For lack of a better term, we refer to this operation as Accumulated
725 /// Path Operation (APO).
726 struct OperandData {
727 OperandData() = default;
OperandDatallvm::slpvectorizer::BoUpSLP::VLOperands::OperandData728 OperandData(Value *V, bool APO, bool IsUsed)
729 : V(V), APO(APO), IsUsed(IsUsed) {}
730 /// The operand value.
731 Value *V = nullptr;
732 /// TreeEntries only allow a single opcode, or an alternate sequence of
733 /// them (e.g, +, -). Therefore, we can safely use a boolean value for the
734 /// APO. It is set to 'true' if 'V' is attached to an inverse operation
735 /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise
736 /// (e.g., Add/Mul)
737 bool APO = false;
738 /// Helper data for the reordering function.
739 bool IsUsed = false;
740 };
741
742 /// During operand reordering, we are trying to select the operand at lane
743 /// that matches best with the operand at the neighboring lane. Our
744 /// selection is based on the type of value we are looking for. For example,
745 /// if the neighboring lane has a load, we need to look for a load that is
746 /// accessing a consecutive address. These strategies are summarized in the
747 /// 'ReorderingMode' enumerator.
748 enum class ReorderingMode {
749 Load, ///< Matching loads to consecutive memory addresses
750 Opcode, ///< Matching instructions based on opcode (same or alternate)
751 Constant, ///< Matching constants
752 Splat, ///< Matching the same instruction multiple times (broadcast)
753 Failed, ///< We failed to create a vectorizable group
754 };
755
756 using OperandDataVec = SmallVector<OperandData, 2>;
757
758 /// A vector of operand vectors.
759 SmallVector<OperandDataVec, 4> OpsVec;
760
761 const DataLayout &DL;
762 ScalarEvolution &SE;
763 const BoUpSLP &R;
764
765 /// \returns the operand data at \p OpIdx and \p Lane.
getData(unsigned OpIdx,unsigned Lane)766 OperandData &getData(unsigned OpIdx, unsigned Lane) {
767 return OpsVec[OpIdx][Lane];
768 }
769
770 /// \returns the operand data at \p OpIdx and \p Lane. Const version.
getData(unsigned OpIdx,unsigned Lane) const771 const OperandData &getData(unsigned OpIdx, unsigned Lane) const {
772 return OpsVec[OpIdx][Lane];
773 }
774
775 /// Clears the used flag for all entries.
clearUsed()776 void clearUsed() {
777 for (unsigned OpIdx = 0, NumOperands = getNumOperands();
778 OpIdx != NumOperands; ++OpIdx)
779 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes;
780 ++Lane)
781 OpsVec[OpIdx][Lane].IsUsed = false;
782 }
783
784 /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2.
swap(unsigned OpIdx1,unsigned OpIdx2,unsigned Lane)785 void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) {
786 std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]);
787 }
788
789 // The hard-coded scores listed here are not very important. When computing
790 // the scores of matching one sub-tree with another, we are basically
791 // counting the number of values that are matching. So even if all scores
792 // are set to 1, we would still get a decent matching result.
793 // However, sometimes we have to break ties. For example we may have to
794 // choose between matching loads vs matching opcodes. This is what these
795 // scores are helping us with: they provide the order of preference.
796
797 /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]).
798 static const int ScoreConsecutiveLoads = 3;
799 /// ExtractElementInst from same vector and consecutive indexes.
800 static const int ScoreConsecutiveExtracts = 3;
801 /// Constants.
802 static const int ScoreConstants = 2;
803 /// Instructions with the same opcode.
804 static const int ScoreSameOpcode = 2;
805 /// Instructions with alt opcodes (e.g, add + sub).
806 static const int ScoreAltOpcodes = 1;
807 /// Identical instructions (a.k.a. splat or broadcast).
808 static const int ScoreSplat = 1;
809 /// Matching with an undef is preferable to failing.
810 static const int ScoreUndef = 1;
811 /// Score for failing to find a decent match.
812 static const int ScoreFail = 0;
813 /// User exteranl to the vectorized code.
814 static const int ExternalUseCost = 1;
815 /// The user is internal but in a different lane.
816 static const int UserInDiffLaneCost = ExternalUseCost;
817
818 /// \returns the score of placing \p V1 and \p V2 in consecutive lanes.
getShallowScore(Value * V1,Value * V2,const DataLayout & DL,ScalarEvolution & SE)819 static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL,
820 ScalarEvolution &SE) {
821 auto *LI1 = dyn_cast<LoadInst>(V1);
822 auto *LI2 = dyn_cast<LoadInst>(V2);
823 if (LI1 && LI2)
824 return isConsecutiveAccess(LI1, LI2, DL, SE)
825 ? VLOperands::ScoreConsecutiveLoads
826 : VLOperands::ScoreFail;
827
828 auto *C1 = dyn_cast<Constant>(V1);
829 auto *C2 = dyn_cast<Constant>(V2);
830 if (C1 && C2)
831 return VLOperands::ScoreConstants;
832
833 // Extracts from consecutive indexes of the same vector better score as
834 // the extracts could be optimized away.
835 Value *EV;
836 ConstantInt *Ex1Idx, *Ex2Idx;
837 if (match(V1, m_ExtractElement(m_Value(EV), m_ConstantInt(Ex1Idx))) &&
838 match(V2, m_ExtractElement(m_Deferred(EV), m_ConstantInt(Ex2Idx))) &&
839 Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue())
840 return VLOperands::ScoreConsecutiveExtracts;
841
842 auto *I1 = dyn_cast<Instruction>(V1);
843 auto *I2 = dyn_cast<Instruction>(V2);
844 if (I1 && I2) {
845 if (I1 == I2)
846 return VLOperands::ScoreSplat;
847 InstructionsState S = getSameOpcode({I1, I2});
848 // Note: Only consider instructions with <= 2 operands to avoid
849 // complexity explosion.
850 if (S.getOpcode() && S.MainOp->getNumOperands() <= 2)
851 return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes
852 : VLOperands::ScoreSameOpcode;
853 }
854
855 if (isa<UndefValue>(V2))
856 return VLOperands::ScoreUndef;
857
858 return VLOperands::ScoreFail;
859 }
860
861 /// Holds the values and their lane that are taking part in the look-ahead
862 /// score calculation. This is used in the external uses cost calculation.
863 SmallDenseMap<Value *, int> InLookAheadValues;
864
865 /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are
866 /// either external to the vectorized code, or require shuffling.
getExternalUsesCost(const std::pair<Value *,int> & LHS,const std::pair<Value *,int> & RHS)867 int getExternalUsesCost(const std::pair<Value *, int> &LHS,
868 const std::pair<Value *, int> &RHS) {
869 int Cost = 0;
870 SmallVector<std::pair<Value *, int>, 2> Values = {LHS, RHS};
871 for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) {
872 Value *V = Values[Idx].first;
873 // Calculate the absolute lane, using the minimum relative lane of LHS
874 // and RHS as base and Idx as the offset.
875 int Ln = std::min(LHS.second, RHS.second) + Idx;
876 assert(Ln >= 0 && "Bad lane calculation");
877 unsigned UsersBudget = LookAheadUsersBudget;
878 for (User *U : V->users()) {
879 if (const TreeEntry *UserTE = R.getTreeEntry(U)) {
880 // The user is in the VectorizableTree. Check if we need to insert.
881 auto It = llvm::find(UserTE->Scalars, U);
882 assert(It != UserTE->Scalars.end() && "U is in UserTE");
883 int UserLn = std::distance(UserTE->Scalars.begin(), It);
884 assert(UserLn >= 0 && "Bad lane");
885 if (UserLn != Ln)
886 Cost += UserInDiffLaneCost;
887 } else {
888 // Check if the user is in the look-ahead code.
889 auto It2 = InLookAheadValues.find(U);
890 if (It2 != InLookAheadValues.end()) {
891 // The user is in the look-ahead code. Check the lane.
892 if (It2->second != Ln)
893 Cost += UserInDiffLaneCost;
894 } else {
895 // The user is neither in SLP tree nor in the look-ahead code.
896 Cost += ExternalUseCost;
897 }
898 }
899 // Limit the number of visited uses to cap compilation time.
900 if (--UsersBudget == 0)
901 break;
902 }
903 }
904 return Cost;
905 }
906
907 /// Go through the operands of \p LHS and \p RHS recursively until \p
908 /// MaxLevel, and return the cummulative score. For example:
909 /// \verbatim
910 /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1]
911 /// \ / \ / \ / \ /
912 /// + + + +
913 /// G1 G2 G3 G4
914 /// \endverbatim
915 /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at
916 /// each level recursively, accumulating the score. It starts from matching
917 /// the additions at level 0, then moves on to the loads (level 1). The
918 /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and
919 /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while
920 /// {A[0],C[0]} has a score of VLOperands::ScoreFail.
921 /// Please note that the order of the operands does not matter, as we
922 /// evaluate the score of all profitable combinations of operands. In
923 /// other words the score of G1 and G4 is the same as G1 and G2. This
924 /// heuristic is based on ideas described in:
925 /// Look-ahead SLP: Auto-vectorization in the presence of commutative
926 /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha,
927 /// Luís F. W. Góes
getScoreAtLevelRec(const std::pair<Value *,int> & LHS,const std::pair<Value *,int> & RHS,int CurrLevel,int MaxLevel)928 int getScoreAtLevelRec(const std::pair<Value *, int> &LHS,
929 const std::pair<Value *, int> &RHS, int CurrLevel,
930 int MaxLevel) {
931
932 Value *V1 = LHS.first;
933 Value *V2 = RHS.first;
934 // Get the shallow score of V1 and V2.
935 int ShallowScoreAtThisLevel =
936 std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) -
937 getExternalUsesCost(LHS, RHS));
938 int Lane1 = LHS.second;
939 int Lane2 = RHS.second;
940
941 // If reached MaxLevel,
942 // or if V1 and V2 are not instructions,
943 // or if they are SPLAT,
944 // or if they are not consecutive, early return the current cost.
945 auto *I1 = dyn_cast<Instruction>(V1);
946 auto *I2 = dyn_cast<Instruction>(V2);
947 if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 ||
948 ShallowScoreAtThisLevel == VLOperands::ScoreFail ||
949 (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel))
950 return ShallowScoreAtThisLevel;
951 assert(I1 && I2 && "Should have early exited.");
952
953 // Keep track of in-tree values for determining the external-use cost.
954 InLookAheadValues[V1] = Lane1;
955 InLookAheadValues[V2] = Lane2;
956
957 // Contains the I2 operand indexes that got matched with I1 operands.
958 SmallSet<unsigned, 4> Op2Used;
959
960 // Recursion towards the operands of I1 and I2. We are trying all possbile
961 // operand pairs, and keeping track of the best score.
962 for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands();
963 OpIdx1 != NumOperands1; ++OpIdx1) {
964 // Try to pair op1I with the best operand of I2.
965 int MaxTmpScore = 0;
966 unsigned MaxOpIdx2 = 0;
967 bool FoundBest = false;
968 // If I2 is commutative try all combinations.
969 unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1;
970 unsigned ToIdx = isCommutative(I2)
971 ? I2->getNumOperands()
972 : std::min(I2->getNumOperands(), OpIdx1 + 1);
973 assert(FromIdx <= ToIdx && "Bad index");
974 for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) {
975 // Skip operands already paired with OpIdx1.
976 if (Op2Used.count(OpIdx2))
977 continue;
978 // Recursively calculate the cost at each level
979 int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1},
980 {I2->getOperand(OpIdx2), Lane2},
981 CurrLevel + 1, MaxLevel);
982 // Look for the best score.
983 if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) {
984 MaxTmpScore = TmpScore;
985 MaxOpIdx2 = OpIdx2;
986 FoundBest = true;
987 }
988 }
989 if (FoundBest) {
990 // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it.
991 Op2Used.insert(MaxOpIdx2);
992 ShallowScoreAtThisLevel += MaxTmpScore;
993 }
994 }
995 return ShallowScoreAtThisLevel;
996 }
997
998 /// \Returns the look-ahead score, which tells us how much the sub-trees
999 /// rooted at \p LHS and \p RHS match, the more they match the higher the
1000 /// score. This helps break ties in an informed way when we cannot decide on
1001 /// the order of the operands by just considering the immediate
1002 /// predecessors.
getLookAheadScore(const std::pair<Value *,int> & LHS,const std::pair<Value *,int> & RHS)1003 int getLookAheadScore(const std::pair<Value *, int> &LHS,
1004 const std::pair<Value *, int> &RHS) {
1005 InLookAheadValues.clear();
1006 return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth);
1007 }
1008
1009 // Search all operands in Ops[*][Lane] for the one that matches best
1010 // Ops[OpIdx][LastLane] and return its opreand index.
1011 // If no good match can be found, return None.
1012 Optional<unsigned>
getBestOperand(unsigned OpIdx,int Lane,int LastLane,ArrayRef<ReorderingMode> ReorderingModes)1013 getBestOperand(unsigned OpIdx, int Lane, int LastLane,
1014 ArrayRef<ReorderingMode> ReorderingModes) {
1015 unsigned NumOperands = getNumOperands();
1016
1017 // The operand of the previous lane at OpIdx.
1018 Value *OpLastLane = getData(OpIdx, LastLane).V;
1019
1020 // Our strategy mode for OpIdx.
1021 ReorderingMode RMode = ReorderingModes[OpIdx];
1022
1023 // The linearized opcode of the operand at OpIdx, Lane.
1024 bool OpIdxAPO = getData(OpIdx, Lane).APO;
1025
1026 // The best operand index and its score.
1027 // Sometimes we have more than one option (e.g., Opcode and Undefs), so we
1028 // are using the score to differentiate between the two.
1029 struct BestOpData {
1030 Optional<unsigned> Idx = None;
1031 unsigned Score = 0;
1032 } BestOp;
1033
1034 // Iterate through all unused operands and look for the best.
1035 for (unsigned Idx = 0; Idx != NumOperands; ++Idx) {
1036 // Get the operand at Idx and Lane.
1037 OperandData &OpData = getData(Idx, Lane);
1038 Value *Op = OpData.V;
1039 bool OpAPO = OpData.APO;
1040
1041 // Skip already selected operands.
1042 if (OpData.IsUsed)
1043 continue;
1044
1045 // Skip if we are trying to move the operand to a position with a
1046 // different opcode in the linearized tree form. This would break the
1047 // semantics.
1048 if (OpAPO != OpIdxAPO)
1049 continue;
1050
1051 // Look for an operand that matches the current mode.
1052 switch (RMode) {
1053 case ReorderingMode::Load:
1054 case ReorderingMode::Constant:
1055 case ReorderingMode::Opcode: {
1056 bool LeftToRight = Lane > LastLane;
1057 Value *OpLeft = (LeftToRight) ? OpLastLane : Op;
1058 Value *OpRight = (LeftToRight) ? Op : OpLastLane;
1059 unsigned Score =
1060 getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane});
1061 if (Score > BestOp.Score) {
1062 BestOp.Idx = Idx;
1063 BestOp.Score = Score;
1064 }
1065 break;
1066 }
1067 case ReorderingMode::Splat:
1068 if (Op == OpLastLane)
1069 BestOp.Idx = Idx;
1070 break;
1071 case ReorderingMode::Failed:
1072 return None;
1073 }
1074 }
1075
1076 if (BestOp.Idx) {
1077 getData(BestOp.Idx.getValue(), Lane).IsUsed = true;
1078 return BestOp.Idx;
1079 }
1080 // If we could not find a good match return None.
1081 return None;
1082 }
1083
1084 /// Helper for reorderOperandVecs. \Returns the lane that we should start
1085 /// reordering from. This is the one which has the least number of operands
1086 /// that can freely move about.
getBestLaneToStartReordering() const1087 unsigned getBestLaneToStartReordering() const {
1088 unsigned BestLane = 0;
1089 unsigned Min = UINT_MAX;
1090 for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes;
1091 ++Lane) {
1092 unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane);
1093 if (NumFreeOps < Min) {
1094 Min = NumFreeOps;
1095 BestLane = Lane;
1096 }
1097 }
1098 return BestLane;
1099 }
1100
1101 /// \Returns the maximum number of operands that are allowed to be reordered
1102 /// for \p Lane. This is used as a heuristic for selecting the first lane to
1103 /// start operand reordering.
getMaxNumOperandsThatCanBeReordered(unsigned Lane) const1104 unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const {
1105 unsigned CntTrue = 0;
1106 unsigned NumOperands = getNumOperands();
1107 // Operands with the same APO can be reordered. We therefore need to count
1108 // how many of them we have for each APO, like this: Cnt[APO] = x.
1109 // Since we only have two APOs, namely true and false, we can avoid using
1110 // a map. Instead we can simply count the number of operands that
1111 // correspond to one of them (in this case the 'true' APO), and calculate
1112 // the other by subtracting it from the total number of operands.
1113 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx)
1114 if (getData(OpIdx, Lane).APO)
1115 ++CntTrue;
1116 unsigned CntFalse = NumOperands - CntTrue;
1117 return std::max(CntTrue, CntFalse);
1118 }
1119
1120 /// Go through the instructions in VL and append their operands.
appendOperandsOfVL(ArrayRef<Value * > VL)1121 void appendOperandsOfVL(ArrayRef<Value *> VL) {
1122 assert(!VL.empty() && "Bad VL");
1123 assert((empty() || VL.size() == getNumLanes()) &&
1124 "Expected same number of lanes");
1125 assert(isa<Instruction>(VL[0]) && "Expected instruction");
1126 unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands();
1127 OpsVec.resize(NumOperands);
1128 unsigned NumLanes = VL.size();
1129 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
1130 OpsVec[OpIdx].resize(NumLanes);
1131 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) {
1132 assert(isa<Instruction>(VL[Lane]) && "Expected instruction");
1133 // Our tree has just 3 nodes: the root and two operands.
1134 // It is therefore trivial to get the APO. We only need to check the
1135 // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or
1136 // RHS operand. The LHS operand of both add and sub is never attached
1137 // to an inversese operation in the linearized form, therefore its APO
1138 // is false. The RHS is true only if VL[Lane] is an inverse operation.
1139
1140 // Since operand reordering is performed on groups of commutative
1141 // operations or alternating sequences (e.g., +, -), we can safely
1142 // tell the inverse operations by checking commutativity.
1143 bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane]));
1144 bool APO = (OpIdx == 0) ? false : IsInverseOperation;
1145 OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx),
1146 APO, false};
1147 }
1148 }
1149 }
1150
1151 /// \returns the number of operands.
getNumOperands() const1152 unsigned getNumOperands() const { return OpsVec.size(); }
1153
1154 /// \returns the number of lanes.
getNumLanes() const1155 unsigned getNumLanes() const { return OpsVec[0].size(); }
1156
1157 /// \returns the operand value at \p OpIdx and \p Lane.
getValue(unsigned OpIdx,unsigned Lane) const1158 Value *getValue(unsigned OpIdx, unsigned Lane) const {
1159 return getData(OpIdx, Lane).V;
1160 }
1161
1162 /// \returns true if the data structure is empty.
empty() const1163 bool empty() const { return OpsVec.empty(); }
1164
1165 /// Clears the data.
clear()1166 void clear() { OpsVec.clear(); }
1167
1168 /// \Returns true if there are enough operands identical to \p Op to fill
1169 /// the whole vector.
1170 /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow.
shouldBroadcast(Value * Op,unsigned OpIdx,unsigned Lane)1171 bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) {
1172 bool OpAPO = getData(OpIdx, Lane).APO;
1173 for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) {
1174 if (Ln == Lane)
1175 continue;
1176 // This is set to true if we found a candidate for broadcast at Lane.
1177 bool FoundCandidate = false;
1178 for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) {
1179 OperandData &Data = getData(OpI, Ln);
1180 if (Data.APO != OpAPO || Data.IsUsed)
1181 continue;
1182 if (Data.V == Op) {
1183 FoundCandidate = true;
1184 Data.IsUsed = true;
1185 break;
1186 }
1187 }
1188 if (!FoundCandidate)
1189 return false;
1190 }
1191 return true;
1192 }
1193
1194 public:
1195 /// Initialize with all the operands of the instruction vector \p RootVL.
VLOperands(ArrayRef<Value * > RootVL,const DataLayout & DL,ScalarEvolution & SE,const BoUpSLP & R)1196 VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL,
1197 ScalarEvolution &SE, const BoUpSLP &R)
1198 : DL(DL), SE(SE), R(R) {
1199 // Append all the operands of RootVL.
1200 appendOperandsOfVL(RootVL);
1201 }
1202
1203 /// \Returns a value vector with the operands across all lanes for the
1204 /// opearnd at \p OpIdx.
getVL(unsigned OpIdx) const1205 ValueList getVL(unsigned OpIdx) const {
1206 ValueList OpVL(OpsVec[OpIdx].size());
1207 assert(OpsVec[OpIdx].size() == getNumLanes() &&
1208 "Expected same num of lanes across all operands");
1209 for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane)
1210 OpVL[Lane] = OpsVec[OpIdx][Lane].V;
1211 return OpVL;
1212 }
1213
1214 // Performs operand reordering for 2 or more operands.
1215 // The original operands are in OrigOps[OpIdx][Lane].
1216 // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'.
reorder()1217 void reorder() {
1218 unsigned NumOperands = getNumOperands();
1219 unsigned NumLanes = getNumLanes();
1220 // Each operand has its own mode. We are using this mode to help us select
1221 // the instructions for each lane, so that they match best with the ones
1222 // we have selected so far.
1223 SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands);
1224
1225 // This is a greedy single-pass algorithm. We are going over each lane
1226 // once and deciding on the best order right away with no back-tracking.
1227 // However, in order to increase its effectiveness, we start with the lane
1228 // that has operands that can move the least. For example, given the
1229 // following lanes:
1230 // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd
1231 // Lane 1 : A[1] = C[1] - B[1] // Visited 1st
1232 // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd
1233 // Lane 3 : A[3] = C[3] - B[3] // Visited 4th
1234 // we will start at Lane 1, since the operands of the subtraction cannot
1235 // be reordered. Then we will visit the rest of the lanes in a circular
1236 // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3.
1237
1238 // Find the first lane that we will start our search from.
1239 unsigned FirstLane = getBestLaneToStartReordering();
1240
1241 // Initialize the modes.
1242 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
1243 Value *OpLane0 = getValue(OpIdx, FirstLane);
1244 // Keep track if we have instructions with all the same opcode on one
1245 // side.
1246 if (isa<LoadInst>(OpLane0))
1247 ReorderingModes[OpIdx] = ReorderingMode::Load;
1248 else if (isa<Instruction>(OpLane0)) {
1249 // Check if OpLane0 should be broadcast.
1250 if (shouldBroadcast(OpLane0, OpIdx, FirstLane))
1251 ReorderingModes[OpIdx] = ReorderingMode::Splat;
1252 else
1253 ReorderingModes[OpIdx] = ReorderingMode::Opcode;
1254 }
1255 else if (isa<Constant>(OpLane0))
1256 ReorderingModes[OpIdx] = ReorderingMode::Constant;
1257 else if (isa<Argument>(OpLane0))
1258 // Our best hope is a Splat. It may save some cost in some cases.
1259 ReorderingModes[OpIdx] = ReorderingMode::Splat;
1260 else
1261 // NOTE: This should be unreachable.
1262 ReorderingModes[OpIdx] = ReorderingMode::Failed;
1263 }
1264
1265 // If the initial strategy fails for any of the operand indexes, then we
1266 // perform reordering again in a second pass. This helps avoid assigning
1267 // high priority to the failed strategy, and should improve reordering for
1268 // the non-failed operand indexes.
1269 for (int Pass = 0; Pass != 2; ++Pass) {
1270 // Skip the second pass if the first pass did not fail.
1271 bool StrategyFailed = false;
1272 // Mark all operand data as free to use.
1273 clearUsed();
1274 // We keep the original operand order for the FirstLane, so reorder the
1275 // rest of the lanes. We are visiting the nodes in a circular fashion,
1276 // using FirstLane as the center point and increasing the radius
1277 // distance.
1278 for (unsigned Distance = 1; Distance != NumLanes; ++Distance) {
1279 // Visit the lane on the right and then the lane on the left.
1280 for (int Direction : {+1, -1}) {
1281 int Lane = FirstLane + Direction * Distance;
1282 if (Lane < 0 || Lane >= (int)NumLanes)
1283 continue;
1284 int LastLane = Lane - Direction;
1285 assert(LastLane >= 0 && LastLane < (int)NumLanes &&
1286 "Out of bounds");
1287 // Look for a good match for each operand.
1288 for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
1289 // Search for the operand that matches SortedOps[OpIdx][Lane-1].
1290 Optional<unsigned> BestIdx =
1291 getBestOperand(OpIdx, Lane, LastLane, ReorderingModes);
1292 // By not selecting a value, we allow the operands that follow to
1293 // select a better matching value. We will get a non-null value in
1294 // the next run of getBestOperand().
1295 if (BestIdx) {
1296 // Swap the current operand with the one returned by
1297 // getBestOperand().
1298 swap(OpIdx, BestIdx.getValue(), Lane);
1299 } else {
1300 // We failed to find a best operand, set mode to 'Failed'.
1301 ReorderingModes[OpIdx] = ReorderingMode::Failed;
1302 // Enable the second pass.
1303 StrategyFailed = true;
1304 }
1305 }
1306 }
1307 }
1308 // Skip second pass if the strategy did not fail.
1309 if (!StrategyFailed)
1310 break;
1311 }
1312 }
1313
1314 #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP)
getModeStr(ReorderingMode RMode)1315 LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) {
1316 switch (RMode) {
1317 case ReorderingMode::Load:
1318 return "Load";
1319 case ReorderingMode::Opcode:
1320 return "Opcode";
1321 case ReorderingMode::Constant:
1322 return "Constant";
1323 case ReorderingMode::Splat:
1324 return "Splat";
1325 case ReorderingMode::Failed:
1326 return "Failed";
1327 }
1328 llvm_unreachable("Unimplemented Reordering Type");
1329 }
1330
printMode(ReorderingMode RMode,raw_ostream & OS)1331 LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode,
1332 raw_ostream &OS) {
1333 return OS << getModeStr(RMode);
1334 }
1335
1336 /// Debug print.
dumpMode(ReorderingMode RMode)1337 LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) {
1338 printMode(RMode, dbgs());
1339 }
1340
operator <<(raw_ostream & OS,ReorderingMode RMode)1341 friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) {
1342 return printMode(RMode, OS);
1343 }
1344
print(raw_ostream & OS) const1345 LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const {
1346 const unsigned Indent = 2;
1347 unsigned Cnt = 0;
1348 for (const OperandDataVec &OpDataVec : OpsVec) {
1349 OS << "Operand " << Cnt++ << "\n";
1350 for (const OperandData &OpData : OpDataVec) {
1351 OS.indent(Indent) << "{";
1352 if (Value *V = OpData.V)
1353 OS << *V;
1354 else
1355 OS << "null";
1356 OS << ", APO:" << OpData.APO << "}\n";
1357 }
1358 OS << "\n";
1359 }
1360 return OS;
1361 }
1362
1363 /// Debug print.
dump() const1364 LLVM_DUMP_METHOD void dump() const { print(dbgs()); }
1365 #endif
1366 };
1367
1368 /// Checks if the instruction is marked for deletion.
isDeleted(Instruction * I) const1369 bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); }
1370
1371 /// Marks values operands for later deletion by replacing them with Undefs.
1372 void eraseInstructions(ArrayRef<Value *> AV);
1373
1374 ~BoUpSLP();
1375
1376 private:
1377 /// Checks if all users of \p I are the part of the vectorization tree.
1378 bool areAllUsersVectorized(Instruction *I) const;
1379
1380 /// \returns the cost of the vectorizable entry.
1381 int getEntryCost(TreeEntry *E);
1382
1383 /// This is the recursive part of buildTree.
1384 void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth,
1385 const EdgeInfo &EI);
1386
1387 /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can
1388 /// be vectorized to use the original vector (or aggregate "bitcast" to a
1389 /// vector) and sets \p CurrentOrder to the identity permutation; otherwise
1390 /// returns false, setting \p CurrentOrder to either an empty vector or a
1391 /// non-identity permutation that allows to reuse extract instructions.
1392 bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue,
1393 SmallVectorImpl<unsigned> &CurrentOrder) const;
1394
1395 /// Vectorize a single entry in the tree.
1396 Value *vectorizeTree(TreeEntry *E);
1397
1398 /// Vectorize a single entry in the tree, starting in \p VL.
1399 Value *vectorizeTree(ArrayRef<Value *> VL);
1400
1401 /// \returns the scalarization cost for this type. Scalarization in this
1402 /// context means the creation of vectors from a group of scalars.
1403 int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices) const;
1404
1405 /// \returns the scalarization cost for this list of values. Assuming that
1406 /// this subtree gets vectorized, we may need to extract the values from the
1407 /// roots. This method calculates the cost of extracting the values.
1408 int getGatherCost(ArrayRef<Value *> VL) const;
1409
1410 /// Set the Builder insert point to one after the last instruction in
1411 /// the bundle
1412 void setInsertPointAfterBundle(TreeEntry *E);
1413
1414 /// \returns a vector from a collection of scalars in \p VL.
1415 Value *Gather(ArrayRef<Value *> VL, VectorType *Ty);
1416
1417 /// \returns whether the VectorizableTree is fully vectorizable and will
1418 /// be beneficial even the tree height is tiny.
1419 bool isFullyVectorizableTinyTree() const;
1420
1421 /// Reorder commutative or alt operands to get better probability of
1422 /// generating vectorized code.
1423 static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL,
1424 SmallVectorImpl<Value *> &Left,
1425 SmallVectorImpl<Value *> &Right,
1426 const DataLayout &DL,
1427 ScalarEvolution &SE,
1428 const BoUpSLP &R);
1429 struct TreeEntry {
1430 using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>;
TreeEntryllvm::slpvectorizer::BoUpSLP::TreeEntry1431 TreeEntry(VecTreeTy &Container) : Container(Container) {}
1432
1433 /// \returns true if the scalars in VL are equal to this entry.
isSamellvm::slpvectorizer::BoUpSLP::TreeEntry1434 bool isSame(ArrayRef<Value *> VL) const {
1435 if (VL.size() == Scalars.size())
1436 return std::equal(VL.begin(), VL.end(), Scalars.begin());
1437 return VL.size() == ReuseShuffleIndices.size() &&
1438 std::equal(
1439 VL.begin(), VL.end(), ReuseShuffleIndices.begin(),
1440 [this](Value *V, unsigned Idx) { return V == Scalars[Idx]; });
1441 }
1442
1443 /// A vector of scalars.
1444 ValueList Scalars;
1445
1446 /// The Scalars are vectorized into this value. It is initialized to Null.
1447 Value *VectorizedValue = nullptr;
1448
1449 /// Do we need to gather this sequence ?
1450 enum EntryState { Vectorize, NeedToGather };
1451 EntryState State;
1452
1453 /// Does this sequence require some shuffling?
1454 SmallVector<unsigned, 4> ReuseShuffleIndices;
1455
1456 /// Does this entry require reordering?
1457 ArrayRef<unsigned> ReorderIndices;
1458
1459 /// Points back to the VectorizableTree.
1460 ///
1461 /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has
1462 /// to be a pointer and needs to be able to initialize the child iterator.
1463 /// Thus we need a reference back to the container to translate the indices
1464 /// to entries.
1465 VecTreeTy &Container;
1466
1467 /// The TreeEntry index containing the user of this entry. We can actually
1468 /// have multiple users so the data structure is not truly a tree.
1469 SmallVector<EdgeInfo, 1> UserTreeIndices;
1470
1471 /// The index of this treeEntry in VectorizableTree.
1472 int Idx = -1;
1473
1474 private:
1475 /// The operands of each instruction in each lane Operands[op_index][lane].
1476 /// Note: This helps avoid the replication of the code that performs the
1477 /// reordering of operands during buildTree_rec() and vectorizeTree().
1478 SmallVector<ValueList, 2> Operands;
1479
1480 /// The main/alternate instruction.
1481 Instruction *MainOp = nullptr;
1482 Instruction *AltOp = nullptr;
1483
1484 public:
1485 /// Set this bundle's \p OpIdx'th operand to \p OpVL.
setOperandllvm::slpvectorizer::BoUpSLP::TreeEntry1486 void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) {
1487 if (Operands.size() < OpIdx + 1)
1488 Operands.resize(OpIdx + 1);
1489 assert(Operands[OpIdx].size() == 0 && "Already resized?");
1490 Operands[OpIdx].resize(Scalars.size());
1491 for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane)
1492 Operands[OpIdx][Lane] = OpVL[Lane];
1493 }
1494
1495 /// Set the operands of this bundle in their original order.
setOperandsInOrderllvm::slpvectorizer::BoUpSLP::TreeEntry1496 void setOperandsInOrder() {
1497 assert(Operands.empty() && "Already initialized?");
1498 auto *I0 = cast<Instruction>(Scalars[0]);
1499 Operands.resize(I0->getNumOperands());
1500 unsigned NumLanes = Scalars.size();
1501 for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands();
1502 OpIdx != NumOperands; ++OpIdx) {
1503 Operands[OpIdx].resize(NumLanes);
1504 for (unsigned Lane = 0; Lane != NumLanes; ++Lane) {
1505 auto *I = cast<Instruction>(Scalars[Lane]);
1506 assert(I->getNumOperands() == NumOperands &&
1507 "Expected same number of operands");
1508 Operands[OpIdx][Lane] = I->getOperand(OpIdx);
1509 }
1510 }
1511 }
1512
1513 /// \returns the \p OpIdx operand of this TreeEntry.
getOperandllvm::slpvectorizer::BoUpSLP::TreeEntry1514 ValueList &getOperand(unsigned OpIdx) {
1515 assert(OpIdx < Operands.size() && "Off bounds");
1516 return Operands[OpIdx];
1517 }
1518
1519 /// \returns the number of operands.
getNumOperandsllvm::slpvectorizer::BoUpSLP::TreeEntry1520 unsigned getNumOperands() const { return Operands.size(); }
1521
1522 /// \return the single \p OpIdx operand.
getSingleOperandllvm::slpvectorizer::BoUpSLP::TreeEntry1523 Value *getSingleOperand(unsigned OpIdx) const {
1524 assert(OpIdx < Operands.size() && "Off bounds");
1525 assert(!Operands[OpIdx].empty() && "No operand available");
1526 return Operands[OpIdx][0];
1527 }
1528
1529 /// Some of the instructions in the list have alternate opcodes.
isAltShufflellvm::slpvectorizer::BoUpSLP::TreeEntry1530 bool isAltShuffle() const {
1531 return getOpcode() != getAltOpcode();
1532 }
1533
isOpcodeOrAltllvm::slpvectorizer::BoUpSLP::TreeEntry1534 bool isOpcodeOrAlt(Instruction *I) const {
1535 unsigned CheckedOpcode = I->getOpcode();
1536 return (getOpcode() == CheckedOpcode ||
1537 getAltOpcode() == CheckedOpcode);
1538 }
1539
1540 /// Chooses the correct key for scheduling data. If \p Op has the same (or
1541 /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is
1542 /// \p OpValue.
isOneOfllvm::slpvectorizer::BoUpSLP::TreeEntry1543 Value *isOneOf(Value *Op) const {
1544 auto *I = dyn_cast<Instruction>(Op);
1545 if (I && isOpcodeOrAlt(I))
1546 return Op;
1547 return MainOp;
1548 }
1549
setOperationsllvm::slpvectorizer::BoUpSLP::TreeEntry1550 void setOperations(const InstructionsState &S) {
1551 MainOp = S.MainOp;
1552 AltOp = S.AltOp;
1553 }
1554
getMainOpllvm::slpvectorizer::BoUpSLP::TreeEntry1555 Instruction *getMainOp() const {
1556 return MainOp;
1557 }
1558
getAltOpllvm::slpvectorizer::BoUpSLP::TreeEntry1559 Instruction *getAltOp() const {
1560 return AltOp;
1561 }
1562
1563 /// The main/alternate opcodes for the list of instructions.
getOpcodellvm::slpvectorizer::BoUpSLP::TreeEntry1564 unsigned getOpcode() const {
1565 return MainOp ? MainOp->getOpcode() : 0;
1566 }
1567
getAltOpcodellvm::slpvectorizer::BoUpSLP::TreeEntry1568 unsigned getAltOpcode() const {
1569 return AltOp ? AltOp->getOpcode() : 0;
1570 }
1571
1572 /// Update operations state of this entry if reorder occurred.
updateStateIfReorderllvm::slpvectorizer::BoUpSLP::TreeEntry1573 bool updateStateIfReorder() {
1574 if (ReorderIndices.empty())
1575 return false;
1576 InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front());
1577 setOperations(S);
1578 return true;
1579 }
1580
1581 #ifndef NDEBUG
1582 /// Debug printer.
dumpllvm::slpvectorizer::BoUpSLP::TreeEntry1583 LLVM_DUMP_METHOD void dump() const {
1584 dbgs() << Idx << ".\n";
1585 for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) {
1586 dbgs() << "Operand " << OpI << ":\n";
1587 for (const Value *V : Operands[OpI])
1588 dbgs().indent(2) << *V << "\n";
1589 }
1590 dbgs() << "Scalars: \n";
1591 for (Value *V : Scalars)
1592 dbgs().indent(2) << *V << "\n";
1593 dbgs() << "State: ";
1594 switch (State) {
1595 case Vectorize:
1596 dbgs() << "Vectorize\n";
1597 break;
1598 case NeedToGather:
1599 dbgs() << "NeedToGather\n";
1600 break;
1601 }
1602 dbgs() << "MainOp: ";
1603 if (MainOp)
1604 dbgs() << *MainOp << "\n";
1605 else
1606 dbgs() << "NULL\n";
1607 dbgs() << "AltOp: ";
1608 if (AltOp)
1609 dbgs() << *AltOp << "\n";
1610 else
1611 dbgs() << "NULL\n";
1612 dbgs() << "VectorizedValue: ";
1613 if (VectorizedValue)
1614 dbgs() << *VectorizedValue << "\n";
1615 else
1616 dbgs() << "NULL\n";
1617 dbgs() << "ReuseShuffleIndices: ";
1618 if (ReuseShuffleIndices.empty())
1619 dbgs() << "Emtpy";
1620 else
1621 for (unsigned ReuseIdx : ReuseShuffleIndices)
1622 dbgs() << ReuseIdx << ", ";
1623 dbgs() << "\n";
1624 dbgs() << "ReorderIndices: ";
1625 for (unsigned ReorderIdx : ReorderIndices)
1626 dbgs() << ReorderIdx << ", ";
1627 dbgs() << "\n";
1628 dbgs() << "UserTreeIndices: ";
1629 for (const auto &EInfo : UserTreeIndices)
1630 dbgs() << EInfo << ", ";
1631 dbgs() << "\n";
1632 }
1633 #endif
1634 };
1635
1636 /// Create a new VectorizableTree entry.
newTreeEntry(ArrayRef<Value * > VL,Optional<ScheduleData * > Bundle,const InstructionsState & S,const EdgeInfo & UserTreeIdx,ArrayRef<unsigned> ReuseShuffleIndices=None,ArrayRef<unsigned> ReorderIndices=None)1637 TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle,
1638 const InstructionsState &S,
1639 const EdgeInfo &UserTreeIdx,
1640 ArrayRef<unsigned> ReuseShuffleIndices = None,
1641 ArrayRef<unsigned> ReorderIndices = None) {
1642 bool Vectorized = (bool)Bundle;
1643 VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree));
1644 TreeEntry *Last = VectorizableTree.back().get();
1645 Last->Idx = VectorizableTree.size() - 1;
1646 Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end());
1647 Last->State = Vectorized ? TreeEntry::Vectorize : TreeEntry::NeedToGather;
1648 Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(),
1649 ReuseShuffleIndices.end());
1650 Last->ReorderIndices = ReorderIndices;
1651 Last->setOperations(S);
1652 if (Vectorized) {
1653 for (int i = 0, e = VL.size(); i != e; ++i) {
1654 assert(!getTreeEntry(VL[i]) && "Scalar already in tree!");
1655 ScalarToTreeEntry[VL[i]] = Last;
1656 }
1657 // Update the scheduler bundle to point to this TreeEntry.
1658 unsigned Lane = 0;
1659 for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember;
1660 BundleMember = BundleMember->NextInBundle) {
1661 BundleMember->TE = Last;
1662 BundleMember->Lane = Lane;
1663 ++Lane;
1664 }
1665 assert((!Bundle.getValue() || Lane == VL.size()) &&
1666 "Bundle and VL out of sync");
1667 } else {
1668 MustGather.insert(VL.begin(), VL.end());
1669 }
1670
1671 if (UserTreeIdx.UserTE)
1672 Last->UserTreeIndices.push_back(UserTreeIdx);
1673
1674 return Last;
1675 }
1676
1677 /// -- Vectorization State --
1678 /// Holds all of the tree entries.
1679 TreeEntry::VecTreeTy VectorizableTree;
1680
1681 #ifndef NDEBUG
1682 /// Debug printer.
dumpVectorizableTree() const1683 LLVM_DUMP_METHOD void dumpVectorizableTree() const {
1684 for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) {
1685 VectorizableTree[Id]->dump();
1686 dbgs() << "\n";
1687 }
1688 }
1689 #endif
1690
getTreeEntry(Value * V)1691 TreeEntry *getTreeEntry(Value *V) {
1692 auto I = ScalarToTreeEntry.find(V);
1693 if (I != ScalarToTreeEntry.end())
1694 return I->second;
1695 return nullptr;
1696 }
1697
getTreeEntry(Value * V) const1698 const TreeEntry *getTreeEntry(Value *V) const {
1699 auto I = ScalarToTreeEntry.find(V);
1700 if (I != ScalarToTreeEntry.end())
1701 return I->second;
1702 return nullptr;
1703 }
1704
1705 /// Maps a specific scalar to its tree entry.
1706 SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry;
1707
1708 /// A list of scalars that we found that we need to keep as scalars.
1709 ValueSet MustGather;
1710
1711 /// This POD struct describes one external user in the vectorized tree.
1712 struct ExternalUser {
ExternalUserllvm::slpvectorizer::BoUpSLP::ExternalUser1713 ExternalUser(Value *S, llvm::User *U, int L)
1714 : Scalar(S), User(U), Lane(L) {}
1715
1716 // Which scalar in our function.
1717 Value *Scalar;
1718
1719 // Which user that uses the scalar.
1720 llvm::User *User;
1721
1722 // Which lane does the scalar belong to.
1723 int Lane;
1724 };
1725 using UserList = SmallVector<ExternalUser, 16>;
1726
1727 /// Checks if two instructions may access the same memory.
1728 ///
1729 /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it
1730 /// is invariant in the calling loop.
isAliased(const MemoryLocation & Loc1,Instruction * Inst1,Instruction * Inst2)1731 bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1,
1732 Instruction *Inst2) {
1733 // First check if the result is already in the cache.
1734 AliasCacheKey key = std::make_pair(Inst1, Inst2);
1735 Optional<bool> &result = AliasCache[key];
1736 if (result.hasValue()) {
1737 return result.getValue();
1738 }
1739 MemoryLocation Loc2 = getLocation(Inst2, AA);
1740 bool aliased = true;
1741 if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) {
1742 // Do the alias check.
1743 aliased = AA->alias(Loc1, Loc2);
1744 }
1745 // Store the result in the cache.
1746 result = aliased;
1747 return aliased;
1748 }
1749
1750 using AliasCacheKey = std::pair<Instruction *, Instruction *>;
1751
1752 /// Cache for alias results.
1753 /// TODO: consider moving this to the AliasAnalysis itself.
1754 DenseMap<AliasCacheKey, Optional<bool>> AliasCache;
1755
1756 /// Removes an instruction from its block and eventually deletes it.
1757 /// It's like Instruction::eraseFromParent() except that the actual deletion
1758 /// is delayed until BoUpSLP is destructed.
1759 /// This is required to ensure that there are no incorrect collisions in the
1760 /// AliasCache, which can happen if a new instruction is allocated at the
1761 /// same address as a previously deleted instruction.
eraseInstruction(Instruction * I,bool ReplaceOpsWithUndef=false)1762 void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) {
1763 auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first;
1764 It->getSecond() = It->getSecond() && ReplaceOpsWithUndef;
1765 }
1766
1767 /// Temporary store for deleted instructions. Instructions will be deleted
1768 /// eventually when the BoUpSLP is destructed.
1769 DenseMap<Instruction *, bool> DeletedInstructions;
1770
1771 /// A list of values that need to extracted out of the tree.
1772 /// This list holds pairs of (Internal Scalar : External User). External User
1773 /// can be nullptr, it means that this Internal Scalar will be used later,
1774 /// after vectorization.
1775 UserList ExternalUses;
1776
1777 /// Values used only by @llvm.assume calls.
1778 SmallPtrSet<const Value *, 32> EphValues;
1779
1780 /// Holds all of the instructions that we gathered.
1781 SetVector<Instruction *> GatherSeq;
1782
1783 /// A list of blocks that we are going to CSE.
1784 SetVector<BasicBlock *> CSEBlocks;
1785
1786 /// Contains all scheduling relevant data for an instruction.
1787 /// A ScheduleData either represents a single instruction or a member of an
1788 /// instruction bundle (= a group of instructions which is combined into a
1789 /// vector instruction).
1790 struct ScheduleData {
1791 // The initial value for the dependency counters. It means that the
1792 // dependencies are not calculated yet.
1793 enum { InvalidDeps = -1 };
1794
1795 ScheduleData() = default;
1796
initllvm::slpvectorizer::BoUpSLP::ScheduleData1797 void init(int BlockSchedulingRegionID, Value *OpVal) {
1798 FirstInBundle = this;
1799 NextInBundle = nullptr;
1800 NextLoadStore = nullptr;
1801 IsScheduled = false;
1802 SchedulingRegionID = BlockSchedulingRegionID;
1803 UnscheduledDepsInBundle = UnscheduledDeps;
1804 clearDependencies();
1805 OpValue = OpVal;
1806 TE = nullptr;
1807 Lane = -1;
1808 }
1809
1810 /// Returns true if the dependency information has been calculated.
hasValidDependenciesllvm::slpvectorizer::BoUpSLP::ScheduleData1811 bool hasValidDependencies() const { return Dependencies != InvalidDeps; }
1812
1813 /// Returns true for single instructions and for bundle representatives
1814 /// (= the head of a bundle).
isSchedulingEntityllvm::slpvectorizer::BoUpSLP::ScheduleData1815 bool isSchedulingEntity() const { return FirstInBundle == this; }
1816
1817 /// Returns true if it represents an instruction bundle and not only a
1818 /// single instruction.
isPartOfBundlellvm::slpvectorizer::BoUpSLP::ScheduleData1819 bool isPartOfBundle() const {
1820 return NextInBundle != nullptr || FirstInBundle != this;
1821 }
1822
1823 /// Returns true if it is ready for scheduling, i.e. it has no more
1824 /// unscheduled depending instructions/bundles.
isReadyllvm::slpvectorizer::BoUpSLP::ScheduleData1825 bool isReady() const {
1826 assert(isSchedulingEntity() &&
1827 "can't consider non-scheduling entity for ready list");
1828 return UnscheduledDepsInBundle == 0 && !IsScheduled;
1829 }
1830
1831 /// Modifies the number of unscheduled dependencies, also updating it for
1832 /// the whole bundle.
incrementUnscheduledDepsllvm::slpvectorizer::BoUpSLP::ScheduleData1833 int incrementUnscheduledDeps(int Incr) {
1834 UnscheduledDeps += Incr;
1835 return FirstInBundle->UnscheduledDepsInBundle += Incr;
1836 }
1837
1838 /// Sets the number of unscheduled dependencies to the number of
1839 /// dependencies.
resetUnscheduledDepsllvm::slpvectorizer::BoUpSLP::ScheduleData1840 void resetUnscheduledDeps() {
1841 incrementUnscheduledDeps(Dependencies - UnscheduledDeps);
1842 }
1843
1844 /// Clears all dependency information.
clearDependenciesllvm::slpvectorizer::BoUpSLP::ScheduleData1845 void clearDependencies() {
1846 Dependencies = InvalidDeps;
1847 resetUnscheduledDeps();
1848 MemoryDependencies.clear();
1849 }
1850
dumpllvm::slpvectorizer::BoUpSLP::ScheduleData1851 void dump(raw_ostream &os) const {
1852 if (!isSchedulingEntity()) {
1853 os << "/ " << *Inst;
1854 } else if (NextInBundle) {
1855 os << '[' << *Inst;
1856 ScheduleData *SD = NextInBundle;
1857 while (SD) {
1858 os << ';' << *SD->Inst;
1859 SD = SD->NextInBundle;
1860 }
1861 os << ']';
1862 } else {
1863 os << *Inst;
1864 }
1865 }
1866
1867 Instruction *Inst = nullptr;
1868
1869 /// Points to the head in an instruction bundle (and always to this for
1870 /// single instructions).
1871 ScheduleData *FirstInBundle = nullptr;
1872
1873 /// Single linked list of all instructions in a bundle. Null if it is a
1874 /// single instruction.
1875 ScheduleData *NextInBundle = nullptr;
1876
1877 /// Single linked list of all memory instructions (e.g. load, store, call)
1878 /// in the block - until the end of the scheduling region.
1879 ScheduleData *NextLoadStore = nullptr;
1880
1881 /// The dependent memory instructions.
1882 /// This list is derived on demand in calculateDependencies().
1883 SmallVector<ScheduleData *, 4> MemoryDependencies;
1884
1885 /// This ScheduleData is in the current scheduling region if this matches
1886 /// the current SchedulingRegionID of BlockScheduling.
1887 int SchedulingRegionID = 0;
1888
1889 /// Used for getting a "good" final ordering of instructions.
1890 int SchedulingPriority = 0;
1891
1892 /// The number of dependencies. Constitutes of the number of users of the
1893 /// instruction plus the number of dependent memory instructions (if any).
1894 /// This value is calculated on demand.
1895 /// If InvalidDeps, the number of dependencies is not calculated yet.
1896 int Dependencies = InvalidDeps;
1897
1898 /// The number of dependencies minus the number of dependencies of scheduled
1899 /// instructions. As soon as this is zero, the instruction/bundle gets ready
1900 /// for scheduling.
1901 /// Note that this is negative as long as Dependencies is not calculated.
1902 int UnscheduledDeps = InvalidDeps;
1903
1904 /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for
1905 /// single instructions.
1906 int UnscheduledDepsInBundle = InvalidDeps;
1907
1908 /// True if this instruction is scheduled (or considered as scheduled in the
1909 /// dry-run).
1910 bool IsScheduled = false;
1911
1912 /// Opcode of the current instruction in the schedule data.
1913 Value *OpValue = nullptr;
1914
1915 /// The TreeEntry that this instruction corresponds to.
1916 TreeEntry *TE = nullptr;
1917
1918 /// The lane of this node in the TreeEntry.
1919 int Lane = -1;
1920 };
1921
1922 #ifndef NDEBUG
operator <<(raw_ostream & os,const BoUpSLP::ScheduleData & SD)1923 friend inline raw_ostream &operator<<(raw_ostream &os,
1924 const BoUpSLP::ScheduleData &SD) {
1925 SD.dump(os);
1926 return os;
1927 }
1928 #endif
1929
1930 friend struct GraphTraits<BoUpSLP *>;
1931 friend struct DOTGraphTraits<BoUpSLP *>;
1932
1933 /// Contains all scheduling data for a basic block.
1934 struct BlockScheduling {
BlockSchedulingllvm::slpvectorizer::BoUpSLP::BlockScheduling1935 BlockScheduling(BasicBlock *BB)
1936 : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {}
1937
clearllvm::slpvectorizer::BoUpSLP::BlockScheduling1938 void clear() {
1939 ReadyInsts.clear();
1940 ScheduleStart = nullptr;
1941 ScheduleEnd = nullptr;
1942 FirstLoadStoreInRegion = nullptr;
1943 LastLoadStoreInRegion = nullptr;
1944
1945 // Reduce the maximum schedule region size by the size of the
1946 // previous scheduling run.
1947 ScheduleRegionSizeLimit -= ScheduleRegionSize;
1948 if (ScheduleRegionSizeLimit < MinScheduleRegionSize)
1949 ScheduleRegionSizeLimit = MinScheduleRegionSize;
1950 ScheduleRegionSize = 0;
1951
1952 // Make a new scheduling region, i.e. all existing ScheduleData is not
1953 // in the new region yet.
1954 ++SchedulingRegionID;
1955 }
1956
getScheduleDatallvm::slpvectorizer::BoUpSLP::BlockScheduling1957 ScheduleData *getScheduleData(Value *V) {
1958 ScheduleData *SD = ScheduleDataMap[V];
1959 if (SD && SD->SchedulingRegionID == SchedulingRegionID)
1960 return SD;
1961 return nullptr;
1962 }
1963
getScheduleDatallvm::slpvectorizer::BoUpSLP::BlockScheduling1964 ScheduleData *getScheduleData(Value *V, Value *Key) {
1965 if (V == Key)
1966 return getScheduleData(V);
1967 auto I = ExtraScheduleDataMap.find(V);
1968 if (I != ExtraScheduleDataMap.end()) {
1969 ScheduleData *SD = I->second[Key];
1970 if (SD && SD->SchedulingRegionID == SchedulingRegionID)
1971 return SD;
1972 }
1973 return nullptr;
1974 }
1975
isInSchedulingRegionllvm::slpvectorizer::BoUpSLP::BlockScheduling1976 bool isInSchedulingRegion(ScheduleData *SD) const {
1977 return SD->SchedulingRegionID == SchedulingRegionID;
1978 }
1979
1980 /// Marks an instruction as scheduled and puts all dependent ready
1981 /// instructions into the ready-list.
1982 template <typename ReadyListType>
schedulellvm::slpvectorizer::BoUpSLP::BlockScheduling1983 void schedule(ScheduleData *SD, ReadyListType &ReadyList) {
1984 SD->IsScheduled = true;
1985 LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n");
1986
1987 ScheduleData *BundleMember = SD;
1988 while (BundleMember) {
1989 if (BundleMember->Inst != BundleMember->OpValue) {
1990 BundleMember = BundleMember->NextInBundle;
1991 continue;
1992 }
1993 // Handle the def-use chain dependencies.
1994
1995 // Decrement the unscheduled counter and insert to ready list if ready.
1996 auto &&DecrUnsched = [this, &ReadyList](Instruction *I) {
1997 doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) {
1998 if (OpDef && OpDef->hasValidDependencies() &&
1999 OpDef->incrementUnscheduledDeps(-1) == 0) {
2000 // There are no more unscheduled dependencies after
2001 // decrementing, so we can put the dependent instruction
2002 // into the ready list.
2003 ScheduleData *DepBundle = OpDef->FirstInBundle;
2004 assert(!DepBundle->IsScheduled &&
2005 "already scheduled bundle gets ready");
2006 ReadyList.insert(DepBundle);
2007 LLVM_DEBUG(dbgs()
2008 << "SLP: gets ready (def): " << *DepBundle << "\n");
2009 }
2010 });
2011 };
2012
2013 // If BundleMember is a vector bundle, its operands may have been
2014 // reordered duiring buildTree(). We therefore need to get its operands
2015 // through the TreeEntry.
2016 if (TreeEntry *TE = BundleMember->TE) {
2017 int Lane = BundleMember->Lane;
2018 assert(Lane >= 0 && "Lane not set");
2019 for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands();
2020 OpIdx != NumOperands; ++OpIdx)
2021 if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane]))
2022 DecrUnsched(I);
2023 } else {
2024 // If BundleMember is a stand-alone instruction, no operand reordering
2025 // has taken place, so we directly access its operands.
2026 for (Use &U : BundleMember->Inst->operands())
2027 if (auto *I = dyn_cast<Instruction>(U.get()))
2028 DecrUnsched(I);
2029 }
2030 // Handle the memory dependencies.
2031 for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) {
2032 if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) {
2033 // There are no more unscheduled dependencies after decrementing,
2034 // so we can put the dependent instruction into the ready list.
2035 ScheduleData *DepBundle = MemoryDepSD->FirstInBundle;
2036 assert(!DepBundle->IsScheduled &&
2037 "already scheduled bundle gets ready");
2038 ReadyList.insert(DepBundle);
2039 LLVM_DEBUG(dbgs()
2040 << "SLP: gets ready (mem): " << *DepBundle << "\n");
2041 }
2042 }
2043 BundleMember = BundleMember->NextInBundle;
2044 }
2045 }
2046
doForAllOpcodesllvm::slpvectorizer::BoUpSLP::BlockScheduling2047 void doForAllOpcodes(Value *V,
2048 function_ref<void(ScheduleData *SD)> Action) {
2049 if (ScheduleData *SD = getScheduleData(V))
2050 Action(SD);
2051 auto I = ExtraScheduleDataMap.find(V);
2052 if (I != ExtraScheduleDataMap.end())
2053 for (auto &P : I->second)
2054 if (P.second->SchedulingRegionID == SchedulingRegionID)
2055 Action(P.second);
2056 }
2057
2058 /// Put all instructions into the ReadyList which are ready for scheduling.
2059 template <typename ReadyListType>
initialFillReadyListllvm::slpvectorizer::BoUpSLP::BlockScheduling2060 void initialFillReadyList(ReadyListType &ReadyList) {
2061 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
2062 doForAllOpcodes(I, [&](ScheduleData *SD) {
2063 if (SD->isSchedulingEntity() && SD->isReady()) {
2064 ReadyList.insert(SD);
2065 LLVM_DEBUG(dbgs()
2066 << "SLP: initially in ready list: " << *I << "\n");
2067 }
2068 });
2069 }
2070 }
2071
2072 /// Checks if a bundle of instructions can be scheduled, i.e. has no
2073 /// cyclic dependencies. This is only a dry-run, no instructions are
2074 /// actually moved at this stage.
2075 /// \returns the scheduling bundle. The returned Optional value is non-None
2076 /// if \p VL is allowed to be scheduled.
2077 Optional<ScheduleData *>
2078 tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP,
2079 const InstructionsState &S);
2080
2081 /// Un-bundles a group of instructions.
2082 void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue);
2083
2084 /// Allocates schedule data chunk.
2085 ScheduleData *allocateScheduleDataChunks();
2086
2087 /// Extends the scheduling region so that V is inside the region.
2088 /// \returns true if the region size is within the limit.
2089 bool extendSchedulingRegion(Value *V, const InstructionsState &S);
2090
2091 /// Initialize the ScheduleData structures for new instructions in the
2092 /// scheduling region.
2093 void initScheduleData(Instruction *FromI, Instruction *ToI,
2094 ScheduleData *PrevLoadStore,
2095 ScheduleData *NextLoadStore);
2096
2097 /// Updates the dependency information of a bundle and of all instructions/
2098 /// bundles which depend on the original bundle.
2099 void calculateDependencies(ScheduleData *SD, bool InsertInReadyList,
2100 BoUpSLP *SLP);
2101
2102 /// Sets all instruction in the scheduling region to un-scheduled.
2103 void resetSchedule();
2104
2105 BasicBlock *BB;
2106
2107 /// Simple memory allocation for ScheduleData.
2108 std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks;
2109
2110 /// The size of a ScheduleData array in ScheduleDataChunks.
2111 int ChunkSize;
2112
2113 /// The allocator position in the current chunk, which is the last entry
2114 /// of ScheduleDataChunks.
2115 int ChunkPos;
2116
2117 /// Attaches ScheduleData to Instruction.
2118 /// Note that the mapping survives during all vectorization iterations, i.e.
2119 /// ScheduleData structures are recycled.
2120 DenseMap<Value *, ScheduleData *> ScheduleDataMap;
2121
2122 /// Attaches ScheduleData to Instruction with the leading key.
2123 DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>>
2124 ExtraScheduleDataMap;
2125
2126 struct ReadyList : SmallVector<ScheduleData *, 8> {
insertllvm::slpvectorizer::BoUpSLP::BlockScheduling::ReadyList2127 void insert(ScheduleData *SD) { push_back(SD); }
2128 };
2129
2130 /// The ready-list for scheduling (only used for the dry-run).
2131 ReadyList ReadyInsts;
2132
2133 /// The first instruction of the scheduling region.
2134 Instruction *ScheduleStart = nullptr;
2135
2136 /// The first instruction _after_ the scheduling region.
2137 Instruction *ScheduleEnd = nullptr;
2138
2139 /// The first memory accessing instruction in the scheduling region
2140 /// (can be null).
2141 ScheduleData *FirstLoadStoreInRegion = nullptr;
2142
2143 /// The last memory accessing instruction in the scheduling region
2144 /// (can be null).
2145 ScheduleData *LastLoadStoreInRegion = nullptr;
2146
2147 /// The current size of the scheduling region.
2148 int ScheduleRegionSize = 0;
2149
2150 /// The maximum size allowed for the scheduling region.
2151 int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget;
2152
2153 /// The ID of the scheduling region. For a new vectorization iteration this
2154 /// is incremented which "removes" all ScheduleData from the region.
2155 // Make sure that the initial SchedulingRegionID is greater than the
2156 // initial SchedulingRegionID in ScheduleData (which is 0).
2157 int SchedulingRegionID = 1;
2158 };
2159
2160 /// Attaches the BlockScheduling structures to basic blocks.
2161 MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules;
2162
2163 /// Performs the "real" scheduling. Done before vectorization is actually
2164 /// performed in a basic block.
2165 void scheduleBlock(BlockScheduling *BS);
2166
2167 /// List of users to ignore during scheduling and that don't need extracting.
2168 ArrayRef<Value *> UserIgnoreList;
2169
2170 using OrdersType = SmallVector<unsigned, 4>;
2171 /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of
2172 /// sorted SmallVectors of unsigned.
2173 struct OrdersTypeDenseMapInfo {
getEmptyKeyllvm::slpvectorizer::BoUpSLP::OrdersTypeDenseMapInfo2174 static OrdersType getEmptyKey() {
2175 OrdersType V;
2176 V.push_back(~1U);
2177 return V;
2178 }
2179
getTombstoneKeyllvm::slpvectorizer::BoUpSLP::OrdersTypeDenseMapInfo2180 static OrdersType getTombstoneKey() {
2181 OrdersType V;
2182 V.push_back(~2U);
2183 return V;
2184 }
2185
getHashValuellvm::slpvectorizer::BoUpSLP::OrdersTypeDenseMapInfo2186 static unsigned getHashValue(const OrdersType &V) {
2187 return static_cast<unsigned>(hash_combine_range(V.begin(), V.end()));
2188 }
2189
isEqualllvm::slpvectorizer::BoUpSLP::OrdersTypeDenseMapInfo2190 static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) {
2191 return LHS == RHS;
2192 }
2193 };
2194
2195 /// Contains orders of operations along with the number of bundles that have
2196 /// operations in this order. It stores only those orders that require
2197 /// reordering, if reordering is not required it is counted using \a
2198 /// NumOpsWantToKeepOriginalOrder.
2199 DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder;
2200 /// Number of bundles that do not require reordering.
2201 unsigned NumOpsWantToKeepOriginalOrder = 0;
2202
2203 // Analysis and block reference.
2204 Function *F;
2205 ScalarEvolution *SE;
2206 TargetTransformInfo *TTI;
2207 TargetLibraryInfo *TLI;
2208 AliasAnalysis *AA;
2209 LoopInfo *LI;
2210 DominatorTree *DT;
2211 AssumptionCache *AC;
2212 DemandedBits *DB;
2213 const DataLayout *DL;
2214 OptimizationRemarkEmitter *ORE;
2215
2216 unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt.
2217 unsigned MinVecRegSize; // Set by cl::opt (default: 128).
2218
2219 /// Instruction builder to construct the vectorized tree.
2220 IRBuilder<> Builder;
2221
2222 /// A map of scalar integer values to the smallest bit width with which they
2223 /// can legally be represented. The values map to (width, signed) pairs,
2224 /// where "width" indicates the minimum bit width and "signed" is True if the
2225 /// value must be signed-extended, rather than zero-extended, back to its
2226 /// original width.
2227 MapVector<Value *, std::pair<uint64_t, bool>> MinBWs;
2228 };
2229
2230 } // end namespace slpvectorizer
2231
2232 template <> struct GraphTraits<BoUpSLP *> {
2233 using TreeEntry = BoUpSLP::TreeEntry;
2234
2235 /// NodeRef has to be a pointer per the GraphWriter.
2236 using NodeRef = TreeEntry *;
2237
2238 using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy;
2239
2240 /// Add the VectorizableTree to the index iterator to be able to return
2241 /// TreeEntry pointers.
2242 struct ChildIteratorType
2243 : public iterator_adaptor_base<
2244 ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> {
2245 ContainerTy &VectorizableTree;
2246
ChildIteratorTypellvm::GraphTraits::ChildIteratorType2247 ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W,
2248 ContainerTy &VT)
2249 : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {}
2250
operator *llvm::GraphTraits::ChildIteratorType2251 NodeRef operator*() { return I->UserTE; }
2252 };
2253
getEntryNodellvm::GraphTraits2254 static NodeRef getEntryNode(BoUpSLP &R) {
2255 return R.VectorizableTree[0].get();
2256 }
2257
child_beginllvm::GraphTraits2258 static ChildIteratorType child_begin(NodeRef N) {
2259 return {N->UserTreeIndices.begin(), N->Container};
2260 }
2261
child_endllvm::GraphTraits2262 static ChildIteratorType child_end(NodeRef N) {
2263 return {N->UserTreeIndices.end(), N->Container};
2264 }
2265
2266 /// For the node iterator we just need to turn the TreeEntry iterator into a
2267 /// TreeEntry* iterator so that it dereferences to NodeRef.
2268 class nodes_iterator {
2269 using ItTy = ContainerTy::iterator;
2270 ItTy It;
2271
2272 public:
nodes_iterator(const ItTy & It2)2273 nodes_iterator(const ItTy &It2) : It(It2) {}
operator *()2274 NodeRef operator*() { return It->get(); }
operator ++()2275 nodes_iterator operator++() {
2276 ++It;
2277 return *this;
2278 }
operator !=(const nodes_iterator & N2) const2279 bool operator!=(const nodes_iterator &N2) const { return N2.It != It; }
2280 };
2281
nodes_beginllvm::GraphTraits2282 static nodes_iterator nodes_begin(BoUpSLP *R) {
2283 return nodes_iterator(R->VectorizableTree.begin());
2284 }
2285
nodes_endllvm::GraphTraits2286 static nodes_iterator nodes_end(BoUpSLP *R) {
2287 return nodes_iterator(R->VectorizableTree.end());
2288 }
2289
sizellvm::GraphTraits2290 static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); }
2291 };
2292
2293 template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits {
2294 using TreeEntry = BoUpSLP::TreeEntry;
2295
DOTGraphTraitsllvm::DOTGraphTraits2296 DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {}
2297
getNodeLabelllvm::DOTGraphTraits2298 std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) {
2299 std::string Str;
2300 raw_string_ostream OS(Str);
2301 if (isSplat(Entry->Scalars)) {
2302 OS << "<splat> " << *Entry->Scalars[0];
2303 return Str;
2304 }
2305 for (auto V : Entry->Scalars) {
2306 OS << *V;
2307 if (std::any_of(
2308 R->ExternalUses.begin(), R->ExternalUses.end(),
2309 [&](const BoUpSLP::ExternalUser &EU) { return EU.Scalar == V; }))
2310 OS << " <extract>";
2311 OS << "\n";
2312 }
2313 return Str;
2314 }
2315
getNodeAttributesllvm::DOTGraphTraits2316 static std::string getNodeAttributes(const TreeEntry *Entry,
2317 const BoUpSLP *) {
2318 if (Entry->State == TreeEntry::NeedToGather)
2319 return "color=red";
2320 return "";
2321 }
2322 };
2323
2324 } // end namespace llvm
2325
~BoUpSLP()2326 BoUpSLP::~BoUpSLP() {
2327 for (const auto &Pair : DeletedInstructions) {
2328 // Replace operands of ignored instructions with Undefs in case if they were
2329 // marked for deletion.
2330 if (Pair.getSecond()) {
2331 Value *Undef = UndefValue::get(Pair.getFirst()->getType());
2332 Pair.getFirst()->replaceAllUsesWith(Undef);
2333 }
2334 Pair.getFirst()->dropAllReferences();
2335 }
2336 for (const auto &Pair : DeletedInstructions) {
2337 assert(Pair.getFirst()->use_empty() &&
2338 "trying to erase instruction with users.");
2339 Pair.getFirst()->eraseFromParent();
2340 }
2341 }
2342
eraseInstructions(ArrayRef<Value * > AV)2343 void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) {
2344 for (auto *V : AV) {
2345 if (auto *I = dyn_cast<Instruction>(V))
2346 eraseInstruction(I, /*ReplaceWithUndef=*/true);
2347 };
2348 }
2349
buildTree(ArrayRef<Value * > Roots,ArrayRef<Value * > UserIgnoreLst)2350 void BoUpSLP::buildTree(ArrayRef<Value *> Roots,
2351 ArrayRef<Value *> UserIgnoreLst) {
2352 ExtraValueToDebugLocsMap ExternallyUsedValues;
2353 buildTree(Roots, ExternallyUsedValues, UserIgnoreLst);
2354 }
2355
buildTree(ArrayRef<Value * > Roots,ExtraValueToDebugLocsMap & ExternallyUsedValues,ArrayRef<Value * > UserIgnoreLst)2356 void BoUpSLP::buildTree(ArrayRef<Value *> Roots,
2357 ExtraValueToDebugLocsMap &ExternallyUsedValues,
2358 ArrayRef<Value *> UserIgnoreLst) {
2359 deleteTree();
2360 UserIgnoreList = UserIgnoreLst;
2361 if (!allSameType(Roots))
2362 return;
2363 buildTree_rec(Roots, 0, EdgeInfo());
2364
2365 // Collect the values that we need to extract from the tree.
2366 for (auto &TEPtr : VectorizableTree) {
2367 TreeEntry *Entry = TEPtr.get();
2368
2369 // No need to handle users of gathered values.
2370 if (Entry->State == TreeEntry::NeedToGather)
2371 continue;
2372
2373 // For each lane:
2374 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) {
2375 Value *Scalar = Entry->Scalars[Lane];
2376 int FoundLane = Lane;
2377 if (!Entry->ReuseShuffleIndices.empty()) {
2378 FoundLane =
2379 std::distance(Entry->ReuseShuffleIndices.begin(),
2380 llvm::find(Entry->ReuseShuffleIndices, FoundLane));
2381 }
2382
2383 // Check if the scalar is externally used as an extra arg.
2384 auto ExtI = ExternallyUsedValues.find(Scalar);
2385 if (ExtI != ExternallyUsedValues.end()) {
2386 LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane "
2387 << Lane << " from " << *Scalar << ".\n");
2388 ExternalUses.emplace_back(Scalar, nullptr, FoundLane);
2389 }
2390 for (User *U : Scalar->users()) {
2391 LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n");
2392
2393 Instruction *UserInst = dyn_cast<Instruction>(U);
2394 if (!UserInst)
2395 continue;
2396
2397 // Skip in-tree scalars that become vectors
2398 if (TreeEntry *UseEntry = getTreeEntry(U)) {
2399 Value *UseScalar = UseEntry->Scalars[0];
2400 // Some in-tree scalars will remain as scalar in vectorized
2401 // instructions. If that is the case, the one in Lane 0 will
2402 // be used.
2403 if (UseScalar != U ||
2404 !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) {
2405 LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U
2406 << ".\n");
2407 assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state");
2408 continue;
2409 }
2410 }
2411
2412 // Ignore users in the user ignore list.
2413 if (is_contained(UserIgnoreList, UserInst))
2414 continue;
2415
2416 LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane "
2417 << Lane << " from " << *Scalar << ".\n");
2418 ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane));
2419 }
2420 }
2421 }
2422 }
2423
buildTree_rec(ArrayRef<Value * > VL,unsigned Depth,const EdgeInfo & UserTreeIdx)2424 void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth,
2425 const EdgeInfo &UserTreeIdx) {
2426 assert((allConstant(VL) || allSameType(VL)) && "Invalid types!");
2427
2428 InstructionsState S = getSameOpcode(VL);
2429 if (Depth == RecursionMaxDepth) {
2430 LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n");
2431 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2432 return;
2433 }
2434
2435 // Don't handle vectors.
2436 if (S.OpValue->getType()->isVectorTy()) {
2437 LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n");
2438 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2439 return;
2440 }
2441
2442 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue))
2443 if (SI->getValueOperand()->getType()->isVectorTy()) {
2444 LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n");
2445 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2446 return;
2447 }
2448
2449 // If all of the operands are identical or constant we have a simple solution.
2450 if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) {
2451 LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n");
2452 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2453 return;
2454 }
2455
2456 // We now know that this is a vector of instructions of the same type from
2457 // the same block.
2458
2459 // Don't vectorize ephemeral values.
2460 for (Value *V : VL) {
2461 if (EphValues.count(V)) {
2462 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V
2463 << ") is ephemeral.\n");
2464 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2465 return;
2466 }
2467 }
2468
2469 // Check if this is a duplicate of another entry.
2470 if (TreeEntry *E = getTreeEntry(S.OpValue)) {
2471 LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n");
2472 if (!E->isSame(VL)) {
2473 LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n");
2474 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2475 return;
2476 }
2477 // Record the reuse of the tree node. FIXME, currently this is only used to
2478 // properly draw the graph rather than for the actual vectorization.
2479 E->UserTreeIndices.push_back(UserTreeIdx);
2480 LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue
2481 << ".\n");
2482 return;
2483 }
2484
2485 // Check that none of the instructions in the bundle are already in the tree.
2486 for (Value *V : VL) {
2487 auto *I = dyn_cast<Instruction>(V);
2488 if (!I)
2489 continue;
2490 if (getTreeEntry(I)) {
2491 LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V
2492 << ") is already in tree.\n");
2493 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2494 return;
2495 }
2496 }
2497
2498 // If any of the scalars is marked as a value that needs to stay scalar, then
2499 // we need to gather the scalars.
2500 // The reduction nodes (stored in UserIgnoreList) also should stay scalar.
2501 for (Value *V : VL) {
2502 if (MustGather.count(V) || is_contained(UserIgnoreList, V)) {
2503 LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n");
2504 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2505 return;
2506 }
2507 }
2508
2509 // Check that all of the users of the scalars that we want to vectorize are
2510 // schedulable.
2511 auto *VL0 = cast<Instruction>(S.OpValue);
2512 BasicBlock *BB = VL0->getParent();
2513
2514 if (!DT->isReachableFromEntry(BB)) {
2515 // Don't go into unreachable blocks. They may contain instructions with
2516 // dependency cycles which confuse the final scheduling.
2517 LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n");
2518 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2519 return;
2520 }
2521
2522 // Check that every instruction appears once in this bundle.
2523 SmallVector<unsigned, 4> ReuseShuffleIndicies;
2524 SmallVector<Value *, 4> UniqueValues;
2525 DenseMap<Value *, unsigned> UniquePositions;
2526 for (Value *V : VL) {
2527 auto Res = UniquePositions.try_emplace(V, UniqueValues.size());
2528 ReuseShuffleIndicies.emplace_back(Res.first->second);
2529 if (Res.second)
2530 UniqueValues.emplace_back(V);
2531 }
2532 size_t NumUniqueScalarValues = UniqueValues.size();
2533 if (NumUniqueScalarValues == VL.size()) {
2534 ReuseShuffleIndicies.clear();
2535 } else {
2536 LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n");
2537 if (NumUniqueScalarValues <= 1 ||
2538 !llvm::isPowerOf2_32(NumUniqueScalarValues)) {
2539 LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n");
2540 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
2541 return;
2542 }
2543 VL = UniqueValues;
2544 }
2545
2546 auto &BSRef = BlocksSchedules[BB];
2547 if (!BSRef)
2548 BSRef = std::make_unique<BlockScheduling>(BB);
2549
2550 BlockScheduling &BS = *BSRef.get();
2551
2552 Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S);
2553 if (!Bundle) {
2554 LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n");
2555 assert((!BS.getScheduleData(VL0) ||
2556 !BS.getScheduleData(VL0)->isPartOfBundle()) &&
2557 "tryScheduleBundle should cancelScheduling on failure");
2558 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2559 ReuseShuffleIndicies);
2560 return;
2561 }
2562 LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n");
2563
2564 unsigned ShuffleOrOp = S.isAltShuffle() ?
2565 (unsigned) Instruction::ShuffleVector : S.getOpcode();
2566 switch (ShuffleOrOp) {
2567 case Instruction::PHI: {
2568 auto *PH = cast<PHINode>(VL0);
2569
2570 // Check for terminator values (e.g. invoke).
2571 for (unsigned j = 0; j < VL.size(); ++j)
2572 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) {
2573 Instruction *Term = dyn_cast<Instruction>(
2574 cast<PHINode>(VL[j])->getIncomingValueForBlock(
2575 PH->getIncomingBlock(i)));
2576 if (Term && Term->isTerminator()) {
2577 LLVM_DEBUG(dbgs()
2578 << "SLP: Need to swizzle PHINodes (terminator use).\n");
2579 BS.cancelScheduling(VL, VL0);
2580 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2581 ReuseShuffleIndicies);
2582 return;
2583 }
2584 }
2585
2586 TreeEntry *TE =
2587 newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies);
2588 LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n");
2589
2590 // Keeps the reordered operands to avoid code duplication.
2591 SmallVector<ValueList, 2> OperandsVec;
2592 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) {
2593 ValueList Operands;
2594 // Prepare the operand vector.
2595 for (Value *j : VL)
2596 Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock(
2597 PH->getIncomingBlock(i)));
2598 TE->setOperand(i, Operands);
2599 OperandsVec.push_back(Operands);
2600 }
2601 for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx)
2602 buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx});
2603 return;
2604 }
2605 case Instruction::ExtractValue:
2606 case Instruction::ExtractElement: {
2607 OrdersType CurrentOrder;
2608 bool Reuse = canReuseExtract(VL, VL0, CurrentOrder);
2609 if (Reuse) {
2610 LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n");
2611 ++NumOpsWantToKeepOriginalOrder;
2612 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2613 ReuseShuffleIndicies);
2614 // This is a special case, as it does not gather, but at the same time
2615 // we are not extending buildTree_rec() towards the operands.
2616 ValueList Op0;
2617 Op0.assign(VL.size(), VL0->getOperand(0));
2618 VectorizableTree.back()->setOperand(0, Op0);
2619 return;
2620 }
2621 if (!CurrentOrder.empty()) {
2622 LLVM_DEBUG({
2623 dbgs() << "SLP: Reusing or shuffling of reordered extract sequence "
2624 "with order";
2625 for (unsigned Idx : CurrentOrder)
2626 dbgs() << " " << Idx;
2627 dbgs() << "\n";
2628 });
2629 // Insert new order with initial value 0, if it does not exist,
2630 // otherwise return the iterator to the existing one.
2631 auto StoredCurrentOrderAndNum =
2632 NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first;
2633 ++StoredCurrentOrderAndNum->getSecond();
2634 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2635 ReuseShuffleIndicies,
2636 StoredCurrentOrderAndNum->getFirst());
2637 // This is a special case, as it does not gather, but at the same time
2638 // we are not extending buildTree_rec() towards the operands.
2639 ValueList Op0;
2640 Op0.assign(VL.size(), VL0->getOperand(0));
2641 VectorizableTree.back()->setOperand(0, Op0);
2642 return;
2643 }
2644 LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n");
2645 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2646 ReuseShuffleIndicies);
2647 BS.cancelScheduling(VL, VL0);
2648 return;
2649 }
2650 case Instruction::Load: {
2651 // Check that a vectorized load would load the same memory as a scalar
2652 // load. For example, we don't want to vectorize loads that are smaller
2653 // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM
2654 // treats loading/storing it as an i8 struct. If we vectorize loads/stores
2655 // from such a struct, we read/write packed bits disagreeing with the
2656 // unvectorized version.
2657 Type *ScalarTy = VL0->getType();
2658
2659 if (DL->getTypeSizeInBits(ScalarTy) !=
2660 DL->getTypeAllocSizeInBits(ScalarTy)) {
2661 BS.cancelScheduling(VL, VL0);
2662 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2663 ReuseShuffleIndicies);
2664 LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n");
2665 return;
2666 }
2667
2668 // Make sure all loads in the bundle are simple - we can't vectorize
2669 // atomic or volatile loads.
2670 SmallVector<Value *, 4> PointerOps(VL.size());
2671 auto POIter = PointerOps.begin();
2672 for (Value *V : VL) {
2673 auto *L = cast<LoadInst>(V);
2674 if (!L->isSimple()) {
2675 BS.cancelScheduling(VL, VL0);
2676 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2677 ReuseShuffleIndicies);
2678 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n");
2679 return;
2680 }
2681 *POIter = L->getPointerOperand();
2682 ++POIter;
2683 }
2684
2685 OrdersType CurrentOrder;
2686 // Check the order of pointer operands.
2687 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) {
2688 Value *Ptr0;
2689 Value *PtrN;
2690 if (CurrentOrder.empty()) {
2691 Ptr0 = PointerOps.front();
2692 PtrN = PointerOps.back();
2693 } else {
2694 Ptr0 = PointerOps[CurrentOrder.front()];
2695 PtrN = PointerOps[CurrentOrder.back()];
2696 }
2697 const SCEV *Scev0 = SE->getSCEV(Ptr0);
2698 const SCEV *ScevN = SE->getSCEV(PtrN);
2699 const auto *Diff =
2700 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0));
2701 uint64_t Size = DL->getTypeAllocSize(ScalarTy);
2702 // Check that the sorted loads are consecutive.
2703 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) {
2704 if (CurrentOrder.empty()) {
2705 // Original loads are consecutive and does not require reordering.
2706 ++NumOpsWantToKeepOriginalOrder;
2707 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S,
2708 UserTreeIdx, ReuseShuffleIndicies);
2709 TE->setOperandsInOrder();
2710 LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n");
2711 } else {
2712 // Need to reorder.
2713 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first;
2714 ++I->getSecond();
2715 TreeEntry *TE =
2716 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2717 ReuseShuffleIndicies, I->getFirst());
2718 TE->setOperandsInOrder();
2719 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n");
2720 }
2721 return;
2722 }
2723 }
2724
2725 LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n");
2726 BS.cancelScheduling(VL, VL0);
2727 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2728 ReuseShuffleIndicies);
2729 return;
2730 }
2731 case Instruction::ZExt:
2732 case Instruction::SExt:
2733 case Instruction::FPToUI:
2734 case Instruction::FPToSI:
2735 case Instruction::FPExt:
2736 case Instruction::PtrToInt:
2737 case Instruction::IntToPtr:
2738 case Instruction::SIToFP:
2739 case Instruction::UIToFP:
2740 case Instruction::Trunc:
2741 case Instruction::FPTrunc:
2742 case Instruction::BitCast: {
2743 Type *SrcTy = VL0->getOperand(0)->getType();
2744 for (Value *V : VL) {
2745 Type *Ty = cast<Instruction>(V)->getOperand(0)->getType();
2746 if (Ty != SrcTy || !isValidElementType(Ty)) {
2747 BS.cancelScheduling(VL, VL0);
2748 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2749 ReuseShuffleIndicies);
2750 LLVM_DEBUG(dbgs()
2751 << "SLP: Gathering casts with different src types.\n");
2752 return;
2753 }
2754 }
2755 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2756 ReuseShuffleIndicies);
2757 LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n");
2758
2759 TE->setOperandsInOrder();
2760 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
2761 ValueList Operands;
2762 // Prepare the operand vector.
2763 for (Value *V : VL)
2764 Operands.push_back(cast<Instruction>(V)->getOperand(i));
2765
2766 buildTree_rec(Operands, Depth + 1, {TE, i});
2767 }
2768 return;
2769 }
2770 case Instruction::ICmp:
2771 case Instruction::FCmp: {
2772 // Check that all of the compares have the same predicate.
2773 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate();
2774 CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0);
2775 Type *ComparedTy = VL0->getOperand(0)->getType();
2776 for (Value *V : VL) {
2777 CmpInst *Cmp = cast<CmpInst>(V);
2778 if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) ||
2779 Cmp->getOperand(0)->getType() != ComparedTy) {
2780 BS.cancelScheduling(VL, VL0);
2781 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2782 ReuseShuffleIndicies);
2783 LLVM_DEBUG(dbgs()
2784 << "SLP: Gathering cmp with different predicate.\n");
2785 return;
2786 }
2787 }
2788
2789 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2790 ReuseShuffleIndicies);
2791 LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n");
2792
2793 ValueList Left, Right;
2794 if (cast<CmpInst>(VL0)->isCommutative()) {
2795 // Commutative predicate - collect + sort operands of the instructions
2796 // so that each side is more likely to have the same opcode.
2797 assert(P0 == SwapP0 && "Commutative Predicate mismatch");
2798 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this);
2799 } else {
2800 // Collect operands - commute if it uses the swapped predicate.
2801 for (Value *V : VL) {
2802 auto *Cmp = cast<CmpInst>(V);
2803 Value *LHS = Cmp->getOperand(0);
2804 Value *RHS = Cmp->getOperand(1);
2805 if (Cmp->getPredicate() != P0)
2806 std::swap(LHS, RHS);
2807 Left.push_back(LHS);
2808 Right.push_back(RHS);
2809 }
2810 }
2811 TE->setOperand(0, Left);
2812 TE->setOperand(1, Right);
2813 buildTree_rec(Left, Depth + 1, {TE, 0});
2814 buildTree_rec(Right, Depth + 1, {TE, 1});
2815 return;
2816 }
2817 case Instruction::Select:
2818 case Instruction::FNeg:
2819 case Instruction::Add:
2820 case Instruction::FAdd:
2821 case Instruction::Sub:
2822 case Instruction::FSub:
2823 case Instruction::Mul:
2824 case Instruction::FMul:
2825 case Instruction::UDiv:
2826 case Instruction::SDiv:
2827 case Instruction::FDiv:
2828 case Instruction::URem:
2829 case Instruction::SRem:
2830 case Instruction::FRem:
2831 case Instruction::Shl:
2832 case Instruction::LShr:
2833 case Instruction::AShr:
2834 case Instruction::And:
2835 case Instruction::Or:
2836 case Instruction::Xor: {
2837 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2838 ReuseShuffleIndicies);
2839 LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n");
2840
2841 // Sort operands of the instructions so that each side is more likely to
2842 // have the same opcode.
2843 if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) {
2844 ValueList Left, Right;
2845 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this);
2846 TE->setOperand(0, Left);
2847 TE->setOperand(1, Right);
2848 buildTree_rec(Left, Depth + 1, {TE, 0});
2849 buildTree_rec(Right, Depth + 1, {TE, 1});
2850 return;
2851 }
2852
2853 TE->setOperandsInOrder();
2854 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
2855 ValueList Operands;
2856 // Prepare the operand vector.
2857 for (Value *j : VL)
2858 Operands.push_back(cast<Instruction>(j)->getOperand(i));
2859
2860 buildTree_rec(Operands, Depth + 1, {TE, i});
2861 }
2862 return;
2863 }
2864 case Instruction::GetElementPtr: {
2865 // We don't combine GEPs with complicated (nested) indexing.
2866 for (Value *V : VL) {
2867 if (cast<Instruction>(V)->getNumOperands() != 2) {
2868 LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n");
2869 BS.cancelScheduling(VL, VL0);
2870 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2871 ReuseShuffleIndicies);
2872 return;
2873 }
2874 }
2875
2876 // We can't combine several GEPs into one vector if they operate on
2877 // different types.
2878 Type *Ty0 = VL0->getOperand(0)->getType();
2879 for (Value *V : VL) {
2880 Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType();
2881 if (Ty0 != CurTy) {
2882 LLVM_DEBUG(dbgs()
2883 << "SLP: not-vectorizable GEP (different types).\n");
2884 BS.cancelScheduling(VL, VL0);
2885 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2886 ReuseShuffleIndicies);
2887 return;
2888 }
2889 }
2890
2891 // We don't combine GEPs with non-constant indexes.
2892 Type *Ty1 = VL0->getOperand(1)->getType();
2893 for (Value *V : VL) {
2894 auto Op = cast<Instruction>(V)->getOperand(1);
2895 if (!isa<ConstantInt>(Op) ||
2896 (Op->getType() != Ty1 &&
2897 Op->getType()->getScalarSizeInBits() >
2898 DL->getIndexSizeInBits(
2899 V->getType()->getPointerAddressSpace()))) {
2900 LLVM_DEBUG(dbgs()
2901 << "SLP: not-vectorizable GEP (non-constant indexes).\n");
2902 BS.cancelScheduling(VL, VL0);
2903 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2904 ReuseShuffleIndicies);
2905 return;
2906 }
2907 }
2908
2909 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2910 ReuseShuffleIndicies);
2911 LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n");
2912 TE->setOperandsInOrder();
2913 for (unsigned i = 0, e = 2; i < e; ++i) {
2914 ValueList Operands;
2915 // Prepare the operand vector.
2916 for (Value *V : VL)
2917 Operands.push_back(cast<Instruction>(V)->getOperand(i));
2918
2919 buildTree_rec(Operands, Depth + 1, {TE, i});
2920 }
2921 return;
2922 }
2923 case Instruction::Store: {
2924 // Check if the stores are consecutive or if we need to swizzle them.
2925 llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType();
2926 // Make sure all stores in the bundle are simple - we can't vectorize
2927 // atomic or volatile stores.
2928 SmallVector<Value *, 4> PointerOps(VL.size());
2929 ValueList Operands(VL.size());
2930 auto POIter = PointerOps.begin();
2931 auto OIter = Operands.begin();
2932 for (Value *V : VL) {
2933 auto *SI = cast<StoreInst>(V);
2934 if (!SI->isSimple()) {
2935 BS.cancelScheduling(VL, VL0);
2936 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2937 ReuseShuffleIndicies);
2938 LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n");
2939 return;
2940 }
2941 *POIter = SI->getPointerOperand();
2942 *OIter = SI->getValueOperand();
2943 ++POIter;
2944 ++OIter;
2945 }
2946
2947 OrdersType CurrentOrder;
2948 // Check the order of pointer operands.
2949 if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) {
2950 Value *Ptr0;
2951 Value *PtrN;
2952 if (CurrentOrder.empty()) {
2953 Ptr0 = PointerOps.front();
2954 PtrN = PointerOps.back();
2955 } else {
2956 Ptr0 = PointerOps[CurrentOrder.front()];
2957 PtrN = PointerOps[CurrentOrder.back()];
2958 }
2959 const SCEV *Scev0 = SE->getSCEV(Ptr0);
2960 const SCEV *ScevN = SE->getSCEV(PtrN);
2961 const auto *Diff =
2962 dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0));
2963 uint64_t Size = DL->getTypeAllocSize(ScalarTy);
2964 // Check that the sorted pointer operands are consecutive.
2965 if (Diff && Diff->getAPInt() == (VL.size() - 1) * Size) {
2966 if (CurrentOrder.empty()) {
2967 // Original stores are consecutive and does not require reordering.
2968 ++NumOpsWantToKeepOriginalOrder;
2969 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S,
2970 UserTreeIdx, ReuseShuffleIndicies);
2971 TE->setOperandsInOrder();
2972 buildTree_rec(Operands, Depth + 1, {TE, 0});
2973 LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n");
2974 } else {
2975 // Need to reorder.
2976 auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first;
2977 ++(I->getSecond());
2978 TreeEntry *TE =
2979 newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
2980 ReuseShuffleIndicies, I->getFirst());
2981 TE->setOperandsInOrder();
2982 buildTree_rec(Operands, Depth + 1, {TE, 0});
2983 LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n");
2984 }
2985 return;
2986 }
2987 }
2988
2989 BS.cancelScheduling(VL, VL0);
2990 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
2991 ReuseShuffleIndicies);
2992 LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n");
2993 return;
2994 }
2995 case Instruction::Call: {
2996 // Check if the calls are all to the same vectorizable intrinsic.
2997 CallInst *CI = cast<CallInst>(VL0);
2998 // Check if this is an Intrinsic call or something that can be
2999 // represented by an intrinsic call
3000 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
3001 if (!isTriviallyVectorizable(ID)) {
3002 BS.cancelScheduling(VL, VL0);
3003 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
3004 ReuseShuffleIndicies);
3005 LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n");
3006 return;
3007 }
3008 Function *Int = CI->getCalledFunction();
3009 unsigned NumArgs = CI->getNumArgOperands();
3010 SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr);
3011 for (unsigned j = 0; j != NumArgs; ++j)
3012 if (hasVectorInstrinsicScalarOpd(ID, j))
3013 ScalarArgs[j] = CI->getArgOperand(j);
3014 for (Value *V : VL) {
3015 CallInst *CI2 = dyn_cast<CallInst>(V);
3016 if (!CI2 || CI2->getCalledFunction() != Int ||
3017 getVectorIntrinsicIDForCall(CI2, TLI) != ID ||
3018 !CI->hasIdenticalOperandBundleSchema(*CI2)) {
3019 BS.cancelScheduling(VL, VL0);
3020 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
3021 ReuseShuffleIndicies);
3022 LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V
3023 << "\n");
3024 return;
3025 }
3026 // Some intrinsics have scalar arguments and should be same in order for
3027 // them to be vectorized.
3028 for (unsigned j = 0; j != NumArgs; ++j) {
3029 if (hasVectorInstrinsicScalarOpd(ID, j)) {
3030 Value *A1J = CI2->getArgOperand(j);
3031 if (ScalarArgs[j] != A1J) {
3032 BS.cancelScheduling(VL, VL0);
3033 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
3034 ReuseShuffleIndicies);
3035 LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI
3036 << " argument " << ScalarArgs[j] << "!=" << A1J
3037 << "\n");
3038 return;
3039 }
3040 }
3041 }
3042 // Verify that the bundle operands are identical between the two calls.
3043 if (CI->hasOperandBundles() &&
3044 !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(),
3045 CI->op_begin() + CI->getBundleOperandsEndIndex(),
3046 CI2->op_begin() + CI2->getBundleOperandsStartIndex())) {
3047 BS.cancelScheduling(VL, VL0);
3048 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
3049 ReuseShuffleIndicies);
3050 LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:"
3051 << *CI << "!=" << *V << '\n');
3052 return;
3053 }
3054 }
3055
3056 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
3057 ReuseShuffleIndicies);
3058 TE->setOperandsInOrder();
3059 for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) {
3060 ValueList Operands;
3061 // Prepare the operand vector.
3062 for (Value *V : VL) {
3063 auto *CI2 = cast<CallInst>(V);
3064 Operands.push_back(CI2->getArgOperand(i));
3065 }
3066 buildTree_rec(Operands, Depth + 1, {TE, i});
3067 }
3068 return;
3069 }
3070 case Instruction::ShuffleVector: {
3071 // If this is not an alternate sequence of opcode like add-sub
3072 // then do not vectorize this instruction.
3073 if (!S.isAltShuffle()) {
3074 BS.cancelScheduling(VL, VL0);
3075 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
3076 ReuseShuffleIndicies);
3077 LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n");
3078 return;
3079 }
3080 TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
3081 ReuseShuffleIndicies);
3082 LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n");
3083
3084 // Reorder operands if reordering would enable vectorization.
3085 if (isa<BinaryOperator>(VL0)) {
3086 ValueList Left, Right;
3087 reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this);
3088 TE->setOperand(0, Left);
3089 TE->setOperand(1, Right);
3090 buildTree_rec(Left, Depth + 1, {TE, 0});
3091 buildTree_rec(Right, Depth + 1, {TE, 1});
3092 return;
3093 }
3094
3095 TE->setOperandsInOrder();
3096 for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
3097 ValueList Operands;
3098 // Prepare the operand vector.
3099 for (Value *V : VL)
3100 Operands.push_back(cast<Instruction>(V)->getOperand(i));
3101
3102 buildTree_rec(Operands, Depth + 1, {TE, i});
3103 }
3104 return;
3105 }
3106 default:
3107 BS.cancelScheduling(VL, VL0);
3108 newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
3109 ReuseShuffleIndicies);
3110 LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n");
3111 return;
3112 }
3113 }
3114
canMapToVector(Type * T,const DataLayout & DL) const3115 unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const {
3116 unsigned N = 1;
3117 Type *EltTy = T;
3118
3119 while (isa<CompositeType>(EltTy)) {
3120 if (auto *ST = dyn_cast<StructType>(EltTy)) {
3121 // Check that struct is homogeneous.
3122 for (const auto *Ty : ST->elements())
3123 if (Ty != *ST->element_begin())
3124 return 0;
3125 N *= ST->getNumElements();
3126 EltTy = *ST->element_begin();
3127 } else {
3128 auto *SeqT = cast<SequentialType>(EltTy);
3129 N *= SeqT->getNumElements();
3130 EltTy = SeqT->getElementType();
3131 }
3132 }
3133
3134 if (!isValidElementType(EltTy))
3135 return 0;
3136 uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N));
3137 if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T))
3138 return 0;
3139 return N;
3140 }
3141
canReuseExtract(ArrayRef<Value * > VL,Value * OpValue,SmallVectorImpl<unsigned> & CurrentOrder) const3142 bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue,
3143 SmallVectorImpl<unsigned> &CurrentOrder) const {
3144 Instruction *E0 = cast<Instruction>(OpValue);
3145 assert(E0->getOpcode() == Instruction::ExtractElement ||
3146 E0->getOpcode() == Instruction::ExtractValue);
3147 assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode");
3148 // Check if all of the extracts come from the same vector and from the
3149 // correct offset.
3150 Value *Vec = E0->getOperand(0);
3151
3152 CurrentOrder.clear();
3153
3154 // We have to extract from a vector/aggregate with the same number of elements.
3155 unsigned NElts;
3156 if (E0->getOpcode() == Instruction::ExtractValue) {
3157 const DataLayout &DL = E0->getModule()->getDataLayout();
3158 NElts = canMapToVector(Vec->getType(), DL);
3159 if (!NElts)
3160 return false;
3161 // Check if load can be rewritten as load of vector.
3162 LoadInst *LI = dyn_cast<LoadInst>(Vec);
3163 if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size()))
3164 return false;
3165 } else {
3166 NElts = Vec->getType()->getVectorNumElements();
3167 }
3168
3169 if (NElts != VL.size())
3170 return false;
3171
3172 // Check that all of the indices extract from the correct offset.
3173 bool ShouldKeepOrder = true;
3174 unsigned E = VL.size();
3175 // Assign to all items the initial value E + 1 so we can check if the extract
3176 // instruction index was used already.
3177 // Also, later we can check that all the indices are used and we have a
3178 // consecutive access in the extract instructions, by checking that no
3179 // element of CurrentOrder still has value E + 1.
3180 CurrentOrder.assign(E, E + 1);
3181 unsigned I = 0;
3182 for (; I < E; ++I) {
3183 auto *Inst = cast<Instruction>(VL[I]);
3184 if (Inst->getOperand(0) != Vec)
3185 break;
3186 Optional<unsigned> Idx = getExtractIndex(Inst);
3187 if (!Idx)
3188 break;
3189 const unsigned ExtIdx = *Idx;
3190 if (ExtIdx != I) {
3191 if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1)
3192 break;
3193 ShouldKeepOrder = false;
3194 CurrentOrder[ExtIdx] = I;
3195 } else {
3196 if (CurrentOrder[I] != E + 1)
3197 break;
3198 CurrentOrder[I] = I;
3199 }
3200 }
3201 if (I < E) {
3202 CurrentOrder.clear();
3203 return false;
3204 }
3205
3206 return ShouldKeepOrder;
3207 }
3208
areAllUsersVectorized(Instruction * I) const3209 bool BoUpSLP::areAllUsersVectorized(Instruction *I) const {
3210 return I->hasOneUse() ||
3211 std::all_of(I->user_begin(), I->user_end(), [this](User *U) {
3212 return ScalarToTreeEntry.count(U) > 0;
3213 });
3214 }
3215
getEntryCost(TreeEntry * E)3216 int BoUpSLP::getEntryCost(TreeEntry *E) {
3217 ArrayRef<Value*> VL = E->Scalars;
3218
3219 Type *ScalarTy = VL[0]->getType();
3220 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0]))
3221 ScalarTy = SI->getValueOperand()->getType();
3222 else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0]))
3223 ScalarTy = CI->getOperand(0)->getType();
3224 VectorType *VecTy = VectorType::get(ScalarTy, VL.size());
3225
3226 // If we have computed a smaller type for the expression, update VecTy so
3227 // that the costs will be accurate.
3228 if (MinBWs.count(VL[0]))
3229 VecTy = VectorType::get(
3230 IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size());
3231
3232 unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size();
3233 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty();
3234 int ReuseShuffleCost = 0;
3235 if (NeedToShuffleReuses) {
3236 ReuseShuffleCost =
3237 TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
3238 }
3239 if (E->State == TreeEntry::NeedToGather) {
3240 if (allConstant(VL))
3241 return 0;
3242 if (isSplat(VL)) {
3243 return ReuseShuffleCost +
3244 TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0);
3245 }
3246 if (E->getOpcode() == Instruction::ExtractElement &&
3247 allSameType(VL) && allSameBlock(VL)) {
3248 Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL);
3249 if (ShuffleKind.hasValue()) {
3250 int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy);
3251 for (auto *V : VL) {
3252 // If all users of instruction are going to be vectorized and this
3253 // instruction itself is not going to be vectorized, consider this
3254 // instruction as dead and remove its cost from the final cost of the
3255 // vectorized tree.
3256 if (areAllUsersVectorized(cast<Instruction>(V)) &&
3257 !ScalarToTreeEntry.count(V)) {
3258 auto *IO = cast<ConstantInt>(
3259 cast<ExtractElementInst>(V)->getIndexOperand());
3260 Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy,
3261 IO->getZExtValue());
3262 }
3263 }
3264 return ReuseShuffleCost + Cost;
3265 }
3266 }
3267 return ReuseShuffleCost + getGatherCost(VL);
3268 }
3269 assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL");
3270 Instruction *VL0 = E->getMainOp();
3271 unsigned ShuffleOrOp =
3272 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode();
3273 switch (ShuffleOrOp) {
3274 case Instruction::PHI:
3275 return 0;
3276
3277 case Instruction::ExtractValue:
3278 case Instruction::ExtractElement:
3279 if (NeedToShuffleReuses) {
3280 unsigned Idx = 0;
3281 for (unsigned I : E->ReuseShuffleIndices) {
3282 if (ShuffleOrOp == Instruction::ExtractElement) {
3283 auto *IO = cast<ConstantInt>(
3284 cast<ExtractElementInst>(VL[I])->getIndexOperand());
3285 Idx = IO->getZExtValue();
3286 ReuseShuffleCost -= TTI->getVectorInstrCost(
3287 Instruction::ExtractElement, VecTy, Idx);
3288 } else {
3289 ReuseShuffleCost -= TTI->getVectorInstrCost(
3290 Instruction::ExtractElement, VecTy, Idx);
3291 ++Idx;
3292 }
3293 }
3294 Idx = ReuseShuffleNumbers;
3295 for (Value *V : VL) {
3296 if (ShuffleOrOp == Instruction::ExtractElement) {
3297 auto *IO = cast<ConstantInt>(
3298 cast<ExtractElementInst>(V)->getIndexOperand());
3299 Idx = IO->getZExtValue();
3300 } else {
3301 --Idx;
3302 }
3303 ReuseShuffleCost +=
3304 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx);
3305 }
3306 }
3307 if (E->State == TreeEntry::Vectorize) {
3308 int DeadCost = ReuseShuffleCost;
3309 if (!E->ReorderIndices.empty()) {
3310 // TODO: Merge this shuffle with the ReuseShuffleCost.
3311 DeadCost += TTI->getShuffleCost(
3312 TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
3313 }
3314 for (unsigned i = 0, e = VL.size(); i < e; ++i) {
3315 Instruction *E = cast<Instruction>(VL[i]);
3316 // If all users are going to be vectorized, instruction can be
3317 // considered as dead.
3318 // The same, if have only one user, it will be vectorized for sure.
3319 if (areAllUsersVectorized(E)) {
3320 // Take credit for instruction that will become dead.
3321 if (E->hasOneUse()) {
3322 Instruction *Ext = E->user_back();
3323 if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) &&
3324 all_of(Ext->users(),
3325 [](User *U) { return isa<GetElementPtrInst>(U); })) {
3326 // Use getExtractWithExtendCost() to calculate the cost of
3327 // extractelement/ext pair.
3328 DeadCost -= TTI->getExtractWithExtendCost(
3329 Ext->getOpcode(), Ext->getType(), VecTy, i);
3330 // Add back the cost of s|zext which is subtracted separately.
3331 DeadCost += TTI->getCastInstrCost(
3332 Ext->getOpcode(), Ext->getType(), E->getType(), Ext);
3333 continue;
3334 }
3335 }
3336 DeadCost -=
3337 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i);
3338 }
3339 }
3340 return DeadCost;
3341 }
3342 return ReuseShuffleCost + getGatherCost(VL);
3343
3344 case Instruction::ZExt:
3345 case Instruction::SExt:
3346 case Instruction::FPToUI:
3347 case Instruction::FPToSI:
3348 case Instruction::FPExt:
3349 case Instruction::PtrToInt:
3350 case Instruction::IntToPtr:
3351 case Instruction::SIToFP:
3352 case Instruction::UIToFP:
3353 case Instruction::Trunc:
3354 case Instruction::FPTrunc:
3355 case Instruction::BitCast: {
3356 Type *SrcTy = VL0->getOperand(0)->getType();
3357 int ScalarEltCost =
3358 TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, VL0);
3359 if (NeedToShuffleReuses) {
3360 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
3361 }
3362
3363 // Calculate the cost of this instruction.
3364 int ScalarCost = VL.size() * ScalarEltCost;
3365
3366 VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size());
3367 int VecCost = 0;
3368 // Check if the values are candidates to demote.
3369 if (!MinBWs.count(VL0) || VecTy != SrcVecTy) {
3370 VecCost = ReuseShuffleCost +
3371 TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy, VL0);
3372 }
3373 return VecCost - ScalarCost;
3374 }
3375 case Instruction::FCmp:
3376 case Instruction::ICmp:
3377 case Instruction::Select: {
3378 // Calculate the cost of this instruction.
3379 int ScalarEltCost = TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy,
3380 Builder.getInt1Ty(), VL0);
3381 if (NeedToShuffleReuses) {
3382 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
3383 }
3384 VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size());
3385 int ScalarCost = VecTy->getNumElements() * ScalarEltCost;
3386 int VecCost = TTI->getCmpSelInstrCost(E->getOpcode(), VecTy, MaskTy, VL0);
3387 return ReuseShuffleCost + VecCost - ScalarCost;
3388 }
3389 case Instruction::FNeg:
3390 case Instruction::Add:
3391 case Instruction::FAdd:
3392 case Instruction::Sub:
3393 case Instruction::FSub:
3394 case Instruction::Mul:
3395 case Instruction::FMul:
3396 case Instruction::UDiv:
3397 case Instruction::SDiv:
3398 case Instruction::FDiv:
3399 case Instruction::URem:
3400 case Instruction::SRem:
3401 case Instruction::FRem:
3402 case Instruction::Shl:
3403 case Instruction::LShr:
3404 case Instruction::AShr:
3405 case Instruction::And:
3406 case Instruction::Or:
3407 case Instruction::Xor: {
3408 // Certain instructions can be cheaper to vectorize if they have a
3409 // constant second vector operand.
3410 TargetTransformInfo::OperandValueKind Op1VK =
3411 TargetTransformInfo::OK_AnyValue;
3412 TargetTransformInfo::OperandValueKind Op2VK =
3413 TargetTransformInfo::OK_UniformConstantValue;
3414 TargetTransformInfo::OperandValueProperties Op1VP =
3415 TargetTransformInfo::OP_None;
3416 TargetTransformInfo::OperandValueProperties Op2VP =
3417 TargetTransformInfo::OP_PowerOf2;
3418
3419 // If all operands are exactly the same ConstantInt then set the
3420 // operand kind to OK_UniformConstantValue.
3421 // If instead not all operands are constants, then set the operand kind
3422 // to OK_AnyValue. If all operands are constants but not the same,
3423 // then set the operand kind to OK_NonUniformConstantValue.
3424 ConstantInt *CInt0 = nullptr;
3425 for (unsigned i = 0, e = VL.size(); i < e; ++i) {
3426 const Instruction *I = cast<Instruction>(VL[i]);
3427 unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0;
3428 ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx));
3429 if (!CInt) {
3430 Op2VK = TargetTransformInfo::OK_AnyValue;
3431 Op2VP = TargetTransformInfo::OP_None;
3432 break;
3433 }
3434 if (Op2VP == TargetTransformInfo::OP_PowerOf2 &&
3435 !CInt->getValue().isPowerOf2())
3436 Op2VP = TargetTransformInfo::OP_None;
3437 if (i == 0) {
3438 CInt0 = CInt;
3439 continue;
3440 }
3441 if (CInt0 != CInt)
3442 Op2VK = TargetTransformInfo::OK_NonUniformConstantValue;
3443 }
3444
3445 SmallVector<const Value *, 4> Operands(VL0->operand_values());
3446 int ScalarEltCost = TTI->getArithmeticInstrCost(
3447 E->getOpcode(), ScalarTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands, VL0);
3448 if (NeedToShuffleReuses) {
3449 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
3450 }
3451 int ScalarCost = VecTy->getNumElements() * ScalarEltCost;
3452 int VecCost = TTI->getArithmeticInstrCost(
3453 E->getOpcode(), VecTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands, VL0);
3454 return ReuseShuffleCost + VecCost - ScalarCost;
3455 }
3456 case Instruction::GetElementPtr: {
3457 TargetTransformInfo::OperandValueKind Op1VK =
3458 TargetTransformInfo::OK_AnyValue;
3459 TargetTransformInfo::OperandValueKind Op2VK =
3460 TargetTransformInfo::OK_UniformConstantValue;
3461
3462 int ScalarEltCost =
3463 TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK);
3464 if (NeedToShuffleReuses) {
3465 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
3466 }
3467 int ScalarCost = VecTy->getNumElements() * ScalarEltCost;
3468 int VecCost =
3469 TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK);
3470 return ReuseShuffleCost + VecCost - ScalarCost;
3471 }
3472 case Instruction::Load: {
3473 // Cost of wide load - cost of scalar loads.
3474 MaybeAlign alignment(cast<LoadInst>(VL0)->getAlignment());
3475 int ScalarEltCost =
3476 TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0);
3477 if (NeedToShuffleReuses) {
3478 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
3479 }
3480 int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost;
3481 int VecLdCost =
3482 TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, VL0);
3483 if (!E->ReorderIndices.empty()) {
3484 // TODO: Merge this shuffle with the ReuseShuffleCost.
3485 VecLdCost += TTI->getShuffleCost(
3486 TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
3487 }
3488 return ReuseShuffleCost + VecLdCost - ScalarLdCost;
3489 }
3490 case Instruction::Store: {
3491 // We know that we can merge the stores. Calculate the cost.
3492 bool IsReorder = !E->ReorderIndices.empty();
3493 auto *SI =
3494 cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0);
3495 MaybeAlign Alignment(SI->getAlignment());
3496 int ScalarEltCost =
3497 TTI->getMemoryOpCost(Instruction::Store, ScalarTy, Alignment, 0, VL0);
3498 if (NeedToShuffleReuses)
3499 ReuseShuffleCost = -(ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
3500 int ScalarStCost = VecTy->getNumElements() * ScalarEltCost;
3501 int VecStCost = TTI->getMemoryOpCost(Instruction::Store,
3502 VecTy, Alignment, 0, VL0);
3503 if (IsReorder) {
3504 // TODO: Merge this shuffle with the ReuseShuffleCost.
3505 VecStCost += TTI->getShuffleCost(
3506 TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
3507 }
3508 return ReuseShuffleCost + VecStCost - ScalarStCost;
3509 }
3510 case Instruction::Call: {
3511 CallInst *CI = cast<CallInst>(VL0);
3512 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
3513
3514 // Calculate the cost of the scalar and vector calls.
3515 SmallVector<Type *, 4> ScalarTys;
3516 for (unsigned op = 0, opc = CI->getNumArgOperands(); op != opc; ++op)
3517 ScalarTys.push_back(CI->getArgOperand(op)->getType());
3518
3519 FastMathFlags FMF;
3520 if (auto *FPMO = dyn_cast<FPMathOperator>(CI))
3521 FMF = FPMO->getFastMathFlags();
3522
3523 int ScalarEltCost =
3524 TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF);
3525 if (NeedToShuffleReuses) {
3526 ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
3527 }
3528 int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost;
3529
3530 SmallVector<Value *, 4> Args(CI->arg_operands());
3531 int VecCallCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF,
3532 VecTy->getNumElements());
3533
3534 LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost
3535 << " (" << VecCallCost << "-" << ScalarCallCost << ")"
3536 << " for " << *CI << "\n");
3537
3538 return ReuseShuffleCost + VecCallCost - ScalarCallCost;
3539 }
3540 case Instruction::ShuffleVector: {
3541 assert(E->isAltShuffle() &&
3542 ((Instruction::isBinaryOp(E->getOpcode()) &&
3543 Instruction::isBinaryOp(E->getAltOpcode())) ||
3544 (Instruction::isCast(E->getOpcode()) &&
3545 Instruction::isCast(E->getAltOpcode()))) &&
3546 "Invalid Shuffle Vector Operand");
3547 int ScalarCost = 0;
3548 if (NeedToShuffleReuses) {
3549 for (unsigned Idx : E->ReuseShuffleIndices) {
3550 Instruction *I = cast<Instruction>(VL[Idx]);
3551 ReuseShuffleCost -= TTI->getInstructionCost(
3552 I, TargetTransformInfo::TCK_RecipThroughput);
3553 }
3554 for (Value *V : VL) {
3555 Instruction *I = cast<Instruction>(V);
3556 ReuseShuffleCost += TTI->getInstructionCost(
3557 I, TargetTransformInfo::TCK_RecipThroughput);
3558 }
3559 }
3560 for (Value *V : VL) {
3561 Instruction *I = cast<Instruction>(V);
3562 assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode");
3563 ScalarCost += TTI->getInstructionCost(
3564 I, TargetTransformInfo::TCK_RecipThroughput);
3565 }
3566 // VecCost is equal to sum of the cost of creating 2 vectors
3567 // and the cost of creating shuffle.
3568 int VecCost = 0;
3569 if (Instruction::isBinaryOp(E->getOpcode())) {
3570 VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy);
3571 VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy);
3572 } else {
3573 Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType();
3574 Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType();
3575 VectorType *Src0Ty = VectorType::get(Src0SclTy, VL.size());
3576 VectorType *Src1Ty = VectorType::get(Src1SclTy, VL.size());
3577 VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty);
3578 VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty);
3579 }
3580 VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0);
3581 return ReuseShuffleCost + VecCost - ScalarCost;
3582 }
3583 default:
3584 llvm_unreachable("Unknown instruction");
3585 }
3586 }
3587
isFullyVectorizableTinyTree() const3588 bool BoUpSLP::isFullyVectorizableTinyTree() const {
3589 LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height "
3590 << VectorizableTree.size() << " is fully vectorizable .\n");
3591
3592 // We only handle trees of heights 1 and 2.
3593 if (VectorizableTree.size() == 1 &&
3594 VectorizableTree[0]->State == TreeEntry::Vectorize)
3595 return true;
3596
3597 if (VectorizableTree.size() != 2)
3598 return false;
3599
3600 // Handle splat and all-constants stores.
3601 if (VectorizableTree[0]->State == TreeEntry::Vectorize &&
3602 (allConstant(VectorizableTree[1]->Scalars) ||
3603 isSplat(VectorizableTree[1]->Scalars)))
3604 return true;
3605
3606 // Gathering cost would be too much for tiny trees.
3607 if (VectorizableTree[0]->State == TreeEntry::NeedToGather ||
3608 VectorizableTree[1]->State == TreeEntry::NeedToGather)
3609 return false;
3610
3611 return true;
3612 }
3613
isLoadCombineReductionCandidate(unsigned RdxOpcode) const3614 bool BoUpSLP::isLoadCombineReductionCandidate(unsigned RdxOpcode) const {
3615 if (RdxOpcode != Instruction::Or)
3616 return false;
3617
3618 unsigned NumElts = VectorizableTree[0]->Scalars.size();
3619 Value *FirstReduced = VectorizableTree[0]->Scalars[0];
3620
3621 // Look past the reduction to find a source value. Arbitrarily follow the
3622 // path through operand 0 of any 'or'. Also, peek through optional
3623 // shift-left-by-constant.
3624 Value *ZextLoad = FirstReduced;
3625 while (match(ZextLoad, m_Or(m_Value(), m_Value())) ||
3626 match(ZextLoad, m_Shl(m_Value(), m_Constant())))
3627 ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0);
3628
3629 // Check if the input to the reduction is an extended load.
3630 Value *LoadPtr;
3631 if (!match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr)))))
3632 return false;
3633
3634 // Require that the total load bit width is a legal integer type.
3635 // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target.
3636 // But <16 x i8> --> i128 is not, so the backend probably can't reduce it.
3637 Type *SrcTy = LoadPtr->getType()->getPointerElementType();
3638 unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts;
3639 LLVMContext &Context = FirstReduced->getContext();
3640 if (!TTI->isTypeLegal(IntegerType::get(Context, LoadBitWidth)))
3641 return false;
3642
3643 // Everything matched - assume that we can fold the whole sequence using
3644 // load combining.
3645 LLVM_DEBUG(dbgs() << "SLP: Assume load combining for scalar reduction of "
3646 << *(cast<Instruction>(FirstReduced)) << "\n");
3647
3648 return true;
3649 }
3650
isTreeTinyAndNotFullyVectorizable() const3651 bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const {
3652 // We can vectorize the tree if its size is greater than or equal to the
3653 // minimum size specified by the MinTreeSize command line option.
3654 if (VectorizableTree.size() >= MinTreeSize)
3655 return false;
3656
3657 // If we have a tiny tree (a tree whose size is less than MinTreeSize), we
3658 // can vectorize it if we can prove it fully vectorizable.
3659 if (isFullyVectorizableTinyTree())
3660 return false;
3661
3662 assert(VectorizableTree.empty()
3663 ? ExternalUses.empty()
3664 : true && "We shouldn't have any external users");
3665
3666 // Otherwise, we can't vectorize the tree. It is both tiny and not fully
3667 // vectorizable.
3668 return true;
3669 }
3670
getSpillCost() const3671 int BoUpSLP::getSpillCost() const {
3672 // Walk from the bottom of the tree to the top, tracking which values are
3673 // live. When we see a call instruction that is not part of our tree,
3674 // query TTI to see if there is a cost to keeping values live over it
3675 // (for example, if spills and fills are required).
3676 unsigned BundleWidth = VectorizableTree.front()->Scalars.size();
3677 int Cost = 0;
3678
3679 SmallPtrSet<Instruction*, 4> LiveValues;
3680 Instruction *PrevInst = nullptr;
3681
3682 for (const auto &TEPtr : VectorizableTree) {
3683 Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]);
3684 if (!Inst)
3685 continue;
3686
3687 if (!PrevInst) {
3688 PrevInst = Inst;
3689 continue;
3690 }
3691
3692 // Update LiveValues.
3693 LiveValues.erase(PrevInst);
3694 for (auto &J : PrevInst->operands()) {
3695 if (isa<Instruction>(&*J) && getTreeEntry(&*J))
3696 LiveValues.insert(cast<Instruction>(&*J));
3697 }
3698
3699 LLVM_DEBUG({
3700 dbgs() << "SLP: #LV: " << LiveValues.size();
3701 for (auto *X : LiveValues)
3702 dbgs() << " " << X->getName();
3703 dbgs() << ", Looking at ";
3704 Inst->dump();
3705 });
3706
3707 // Now find the sequence of instructions between PrevInst and Inst.
3708 unsigned NumCalls = 0;
3709 BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(),
3710 PrevInstIt =
3711 PrevInst->getIterator().getReverse();
3712 while (InstIt != PrevInstIt) {
3713 if (PrevInstIt == PrevInst->getParent()->rend()) {
3714 PrevInstIt = Inst->getParent()->rbegin();
3715 continue;
3716 }
3717
3718 // Debug information does not impact spill cost.
3719 if ((isa<CallInst>(&*PrevInstIt) &&
3720 !isa<DbgInfoIntrinsic>(&*PrevInstIt)) &&
3721 &*PrevInstIt != PrevInst)
3722 NumCalls++;
3723
3724 ++PrevInstIt;
3725 }
3726
3727 if (NumCalls) {
3728 SmallVector<Type*, 4> V;
3729 for (auto *II : LiveValues)
3730 V.push_back(VectorType::get(II->getType(), BundleWidth));
3731 Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V);
3732 }
3733
3734 PrevInst = Inst;
3735 }
3736
3737 return Cost;
3738 }
3739
getTreeCost()3740 int BoUpSLP::getTreeCost() {
3741 int Cost = 0;
3742 LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size "
3743 << VectorizableTree.size() << ".\n");
3744
3745 unsigned BundleWidth = VectorizableTree[0]->Scalars.size();
3746
3747 for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) {
3748 TreeEntry &TE = *VectorizableTree[I].get();
3749
3750 // We create duplicate tree entries for gather sequences that have multiple
3751 // uses. However, we should not compute the cost of duplicate sequences.
3752 // For example, if we have a build vector (i.e., insertelement sequence)
3753 // that is used by more than one vector instruction, we only need to
3754 // compute the cost of the insertelement instructions once. The redundant
3755 // instructions will be eliminated by CSE.
3756 //
3757 // We should consider not creating duplicate tree entries for gather
3758 // sequences, and instead add additional edges to the tree representing
3759 // their uses. Since such an approach results in fewer total entries,
3760 // existing heuristics based on tree size may yield different results.
3761 //
3762 if (TE.State == TreeEntry::NeedToGather &&
3763 std::any_of(std::next(VectorizableTree.begin(), I + 1),
3764 VectorizableTree.end(),
3765 [TE](const std::unique_ptr<TreeEntry> &EntryPtr) {
3766 return EntryPtr->State == TreeEntry::NeedToGather &&
3767 EntryPtr->isSame(TE.Scalars);
3768 }))
3769 continue;
3770
3771 int C = getEntryCost(&TE);
3772 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C
3773 << " for bundle that starts with " << *TE.Scalars[0]
3774 << ".\n");
3775 Cost += C;
3776 }
3777
3778 SmallPtrSet<Value *, 16> ExtractCostCalculated;
3779 int ExtractCost = 0;
3780 for (ExternalUser &EU : ExternalUses) {
3781 // We only add extract cost once for the same scalar.
3782 if (!ExtractCostCalculated.insert(EU.Scalar).second)
3783 continue;
3784
3785 // Uses by ephemeral values are free (because the ephemeral value will be
3786 // removed prior to code generation, and so the extraction will be
3787 // removed as well).
3788 if (EphValues.count(EU.User))
3789 continue;
3790
3791 // If we plan to rewrite the tree in a smaller type, we will need to sign
3792 // extend the extracted value back to the original type. Here, we account
3793 // for the extract and the added cost of the sign extend if needed.
3794 auto *VecTy = VectorType::get(EU.Scalar->getType(), BundleWidth);
3795 auto *ScalarRoot = VectorizableTree[0]->Scalars[0];
3796 if (MinBWs.count(ScalarRoot)) {
3797 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first);
3798 auto Extend =
3799 MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt;
3800 VecTy = VectorType::get(MinTy, BundleWidth);
3801 ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(),
3802 VecTy, EU.Lane);
3803 } else {
3804 ExtractCost +=
3805 TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane);
3806 }
3807 }
3808
3809 int SpillCost = getSpillCost();
3810 Cost += SpillCost + ExtractCost;
3811
3812 std::string Str;
3813 {
3814 raw_string_ostream OS(Str);
3815 OS << "SLP: Spill Cost = " << SpillCost << ".\n"
3816 << "SLP: Extract Cost = " << ExtractCost << ".\n"
3817 << "SLP: Total Cost = " << Cost << ".\n";
3818 }
3819 LLVM_DEBUG(dbgs() << Str);
3820
3821 if (ViewSLPTree)
3822 ViewGraph(this, "SLP" + F->getName(), false, Str);
3823
3824 return Cost;
3825 }
3826
getGatherCost(Type * Ty,const DenseSet<unsigned> & ShuffledIndices) const3827 int BoUpSLP::getGatherCost(Type *Ty,
3828 const DenseSet<unsigned> &ShuffledIndices) const {
3829 int Cost = 0;
3830 for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i)
3831 if (!ShuffledIndices.count(i))
3832 Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i);
3833 if (!ShuffledIndices.empty())
3834 Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty);
3835 return Cost;
3836 }
3837
getGatherCost(ArrayRef<Value * > VL) const3838 int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const {
3839 // Find the type of the operands in VL.
3840 Type *ScalarTy = VL[0]->getType();
3841 if (StoreInst *SI = dyn_cast<StoreInst>(VL[0]))
3842 ScalarTy = SI->getValueOperand()->getType();
3843 VectorType *VecTy = VectorType::get(ScalarTy, VL.size());
3844 // Find the cost of inserting/extracting values from the vector.
3845 // Check if the same elements are inserted several times and count them as
3846 // shuffle candidates.
3847 DenseSet<unsigned> ShuffledElements;
3848 DenseSet<Value *> UniqueElements;
3849 // Iterate in reverse order to consider insert elements with the high cost.
3850 for (unsigned I = VL.size(); I > 0; --I) {
3851 unsigned Idx = I - 1;
3852 if (!UniqueElements.insert(VL[Idx]).second)
3853 ShuffledElements.insert(Idx);
3854 }
3855 return getGatherCost(VecTy, ShuffledElements);
3856 }
3857
3858 // Perform operand reordering on the instructions in VL and return the reordered
3859 // operands in Left and Right.
reorderInputsAccordingToOpcode(ArrayRef<Value * > VL,SmallVectorImpl<Value * > & Left,SmallVectorImpl<Value * > & Right,const DataLayout & DL,ScalarEvolution & SE,const BoUpSLP & R)3860 void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL,
3861 SmallVectorImpl<Value *> &Left,
3862 SmallVectorImpl<Value *> &Right,
3863 const DataLayout &DL,
3864 ScalarEvolution &SE,
3865 const BoUpSLP &R) {
3866 if (VL.empty())
3867 return;
3868 VLOperands Ops(VL, DL, SE, R);
3869 // Reorder the operands in place.
3870 Ops.reorder();
3871 Left = Ops.getVL(0);
3872 Right = Ops.getVL(1);
3873 }
3874
setInsertPointAfterBundle(TreeEntry * E)3875 void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) {
3876 // Get the basic block this bundle is in. All instructions in the bundle
3877 // should be in this block.
3878 auto *Front = E->getMainOp();
3879 auto *BB = Front->getParent();
3880 assert(llvm::all_of(make_range(E->Scalars.begin(), E->Scalars.end()),
3881 [=](Value *V) -> bool {
3882 auto *I = cast<Instruction>(V);
3883 return !E->isOpcodeOrAlt(I) || I->getParent() == BB;
3884 }));
3885
3886 // The last instruction in the bundle in program order.
3887 Instruction *LastInst = nullptr;
3888
3889 // Find the last instruction. The common case should be that BB has been
3890 // scheduled, and the last instruction is VL.back(). So we start with
3891 // VL.back() and iterate over schedule data until we reach the end of the
3892 // bundle. The end of the bundle is marked by null ScheduleData.
3893 if (BlocksSchedules.count(BB)) {
3894 auto *Bundle =
3895 BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back()));
3896 if (Bundle && Bundle->isPartOfBundle())
3897 for (; Bundle; Bundle = Bundle->NextInBundle)
3898 if (Bundle->OpValue == Bundle->Inst)
3899 LastInst = Bundle->Inst;
3900 }
3901
3902 // LastInst can still be null at this point if there's either not an entry
3903 // for BB in BlocksSchedules or there's no ScheduleData available for
3904 // VL.back(). This can be the case if buildTree_rec aborts for various
3905 // reasons (e.g., the maximum recursion depth is reached, the maximum region
3906 // size is reached, etc.). ScheduleData is initialized in the scheduling
3907 // "dry-run".
3908 //
3909 // If this happens, we can still find the last instruction by brute force. We
3910 // iterate forwards from Front (inclusive) until we either see all
3911 // instructions in the bundle or reach the end of the block. If Front is the
3912 // last instruction in program order, LastInst will be set to Front, and we
3913 // will visit all the remaining instructions in the block.
3914 //
3915 // One of the reasons we exit early from buildTree_rec is to place an upper
3916 // bound on compile-time. Thus, taking an additional compile-time hit here is
3917 // not ideal. However, this should be exceedingly rare since it requires that
3918 // we both exit early from buildTree_rec and that the bundle be out-of-order
3919 // (causing us to iterate all the way to the end of the block).
3920 if (!LastInst) {
3921 SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end());
3922 for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) {
3923 if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I))
3924 LastInst = &I;
3925 if (Bundle.empty())
3926 break;
3927 }
3928 }
3929 assert(LastInst && "Failed to find last instruction in bundle");
3930
3931 // Set the insertion point after the last instruction in the bundle. Set the
3932 // debug location to Front.
3933 Builder.SetInsertPoint(BB, ++LastInst->getIterator());
3934 Builder.SetCurrentDebugLocation(Front->getDebugLoc());
3935 }
3936
Gather(ArrayRef<Value * > VL,VectorType * Ty)3937 Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) {
3938 Value *Vec = UndefValue::get(Ty);
3939 // Generate the 'InsertElement' instruction.
3940 for (unsigned i = 0; i < Ty->getNumElements(); ++i) {
3941 Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i));
3942 if (auto *Insrt = dyn_cast<InsertElementInst>(Vec)) {
3943 GatherSeq.insert(Insrt);
3944 CSEBlocks.insert(Insrt->getParent());
3945
3946 // Add to our 'need-to-extract' list.
3947 if (TreeEntry *E = getTreeEntry(VL[i])) {
3948 // Find which lane we need to extract.
3949 int FoundLane = -1;
3950 for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) {
3951 // Is this the lane of the scalar that we are looking for ?
3952 if (E->Scalars[Lane] == VL[i]) {
3953 FoundLane = Lane;
3954 break;
3955 }
3956 }
3957 assert(FoundLane >= 0 && "Could not find the correct lane");
3958 if (!E->ReuseShuffleIndices.empty()) {
3959 FoundLane =
3960 std::distance(E->ReuseShuffleIndices.begin(),
3961 llvm::find(E->ReuseShuffleIndices, FoundLane));
3962 }
3963 ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane));
3964 }
3965 }
3966 }
3967
3968 return Vec;
3969 }
3970
vectorizeTree(ArrayRef<Value * > VL)3971 Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) {
3972 InstructionsState S = getSameOpcode(VL);
3973 if (S.getOpcode()) {
3974 if (TreeEntry *E = getTreeEntry(S.OpValue)) {
3975 if (E->isSame(VL)) {
3976 Value *V = vectorizeTree(E);
3977 if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) {
3978 // We need to get the vectorized value but without shuffle.
3979 if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) {
3980 V = SV->getOperand(0);
3981 } else {
3982 // Reshuffle to get only unique values.
3983 SmallVector<unsigned, 4> UniqueIdxs;
3984 SmallSet<unsigned, 4> UsedIdxs;
3985 for(unsigned Idx : E->ReuseShuffleIndices)
3986 if (UsedIdxs.insert(Idx).second)
3987 UniqueIdxs.emplace_back(Idx);
3988 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()),
3989 UniqueIdxs);
3990 }
3991 }
3992 return V;
3993 }
3994 }
3995 }
3996
3997 Type *ScalarTy = S.OpValue->getType();
3998 if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue))
3999 ScalarTy = SI->getValueOperand()->getType();
4000
4001 // Check that every instruction appears once in this bundle.
4002 SmallVector<unsigned, 4> ReuseShuffleIndicies;
4003 SmallVector<Value *, 4> UniqueValues;
4004 if (VL.size() > 2) {
4005 DenseMap<Value *, unsigned> UniquePositions;
4006 for (Value *V : VL) {
4007 auto Res = UniquePositions.try_emplace(V, UniqueValues.size());
4008 ReuseShuffleIndicies.emplace_back(Res.first->second);
4009 if (Res.second || isa<Constant>(V))
4010 UniqueValues.emplace_back(V);
4011 }
4012 // Do not shuffle single element or if number of unique values is not power
4013 // of 2.
4014 if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 ||
4015 !llvm::isPowerOf2_32(UniqueValues.size()))
4016 ReuseShuffleIndicies.clear();
4017 else
4018 VL = UniqueValues;
4019 }
4020 VectorType *VecTy = VectorType::get(ScalarTy, VL.size());
4021
4022 Value *V = Gather(VL, VecTy);
4023 if (!ReuseShuffleIndicies.empty()) {
4024 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4025 ReuseShuffleIndicies, "shuffle");
4026 if (auto *I = dyn_cast<Instruction>(V)) {
4027 GatherSeq.insert(I);
4028 CSEBlocks.insert(I->getParent());
4029 }
4030 }
4031 return V;
4032 }
4033
inversePermutation(ArrayRef<unsigned> Indices,SmallVectorImpl<unsigned> & Mask)4034 static void inversePermutation(ArrayRef<unsigned> Indices,
4035 SmallVectorImpl<unsigned> &Mask) {
4036 Mask.clear();
4037 const unsigned E = Indices.size();
4038 Mask.resize(E);
4039 for (unsigned I = 0; I < E; ++I)
4040 Mask[Indices[I]] = I;
4041 }
4042
vectorizeTree(TreeEntry * E)4043 Value *BoUpSLP::vectorizeTree(TreeEntry *E) {
4044 IRBuilder<>::InsertPointGuard Guard(Builder);
4045
4046 if (E->VectorizedValue) {
4047 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n");
4048 return E->VectorizedValue;
4049 }
4050
4051 Instruction *VL0 = E->getMainOp();
4052 Type *ScalarTy = VL0->getType();
4053 if (StoreInst *SI = dyn_cast<StoreInst>(VL0))
4054 ScalarTy = SI->getValueOperand()->getType();
4055 VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size());
4056
4057 bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty();
4058
4059 if (E->State == TreeEntry::NeedToGather) {
4060 setInsertPointAfterBundle(E);
4061 auto *V = Gather(E->Scalars, VecTy);
4062 if (NeedToShuffleReuses) {
4063 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4064 E->ReuseShuffleIndices, "shuffle");
4065 if (auto *I = dyn_cast<Instruction>(V)) {
4066 GatherSeq.insert(I);
4067 CSEBlocks.insert(I->getParent());
4068 }
4069 }
4070 E->VectorizedValue = V;
4071 return V;
4072 }
4073
4074 unsigned ShuffleOrOp =
4075 E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode();
4076 switch (ShuffleOrOp) {
4077 case Instruction::PHI: {
4078 auto *PH = cast<PHINode>(VL0);
4079 Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI());
4080 Builder.SetCurrentDebugLocation(PH->getDebugLoc());
4081 PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues());
4082 Value *V = NewPhi;
4083 if (NeedToShuffleReuses) {
4084 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4085 E->ReuseShuffleIndices, "shuffle");
4086 }
4087 E->VectorizedValue = V;
4088
4089 // PHINodes may have multiple entries from the same block. We want to
4090 // visit every block once.
4091 SmallPtrSet<BasicBlock*, 4> VisitedBBs;
4092
4093 for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) {
4094 ValueList Operands;
4095 BasicBlock *IBB = PH->getIncomingBlock(i);
4096
4097 if (!VisitedBBs.insert(IBB).second) {
4098 NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB);
4099 continue;
4100 }
4101
4102 Builder.SetInsertPoint(IBB->getTerminator());
4103 Builder.SetCurrentDebugLocation(PH->getDebugLoc());
4104 Value *Vec = vectorizeTree(E->getOperand(i));
4105 NewPhi->addIncoming(Vec, IBB);
4106 }
4107
4108 assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() &&
4109 "Invalid number of incoming values");
4110 return V;
4111 }
4112
4113 case Instruction::ExtractElement: {
4114 if (E->State == TreeEntry::Vectorize) {
4115 Value *V = E->getSingleOperand(0);
4116 if (!E->ReorderIndices.empty()) {
4117 OrdersType Mask;
4118 inversePermutation(E->ReorderIndices, Mask);
4119 Builder.SetInsertPoint(VL0);
4120 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask,
4121 "reorder_shuffle");
4122 }
4123 if (NeedToShuffleReuses) {
4124 // TODO: Merge this shuffle with the ReorderShuffleMask.
4125 if (E->ReorderIndices.empty())
4126 Builder.SetInsertPoint(VL0);
4127 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4128 E->ReuseShuffleIndices, "shuffle");
4129 }
4130 E->VectorizedValue = V;
4131 return V;
4132 }
4133 setInsertPointAfterBundle(E);
4134 auto *V = Gather(E->Scalars, VecTy);
4135 if (NeedToShuffleReuses) {
4136 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4137 E->ReuseShuffleIndices, "shuffle");
4138 if (auto *I = dyn_cast<Instruction>(V)) {
4139 GatherSeq.insert(I);
4140 CSEBlocks.insert(I->getParent());
4141 }
4142 }
4143 E->VectorizedValue = V;
4144 return V;
4145 }
4146 case Instruction::ExtractValue: {
4147 if (E->State == TreeEntry::Vectorize) {
4148 LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0));
4149 Builder.SetInsertPoint(LI);
4150 PointerType *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace());
4151 Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy);
4152 LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlignment());
4153 Value *NewV = propagateMetadata(V, E->Scalars);
4154 if (!E->ReorderIndices.empty()) {
4155 OrdersType Mask;
4156 inversePermutation(E->ReorderIndices, Mask);
4157 NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask,
4158 "reorder_shuffle");
4159 }
4160 if (NeedToShuffleReuses) {
4161 // TODO: Merge this shuffle with the ReorderShuffleMask.
4162 NewV = Builder.CreateShuffleVector(
4163 NewV, UndefValue::get(VecTy), E->ReuseShuffleIndices, "shuffle");
4164 }
4165 E->VectorizedValue = NewV;
4166 return NewV;
4167 }
4168 setInsertPointAfterBundle(E);
4169 auto *V = Gather(E->Scalars, VecTy);
4170 if (NeedToShuffleReuses) {
4171 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4172 E->ReuseShuffleIndices, "shuffle");
4173 if (auto *I = dyn_cast<Instruction>(V)) {
4174 GatherSeq.insert(I);
4175 CSEBlocks.insert(I->getParent());
4176 }
4177 }
4178 E->VectorizedValue = V;
4179 return V;
4180 }
4181 case Instruction::ZExt:
4182 case Instruction::SExt:
4183 case Instruction::FPToUI:
4184 case Instruction::FPToSI:
4185 case Instruction::FPExt:
4186 case Instruction::PtrToInt:
4187 case Instruction::IntToPtr:
4188 case Instruction::SIToFP:
4189 case Instruction::UIToFP:
4190 case Instruction::Trunc:
4191 case Instruction::FPTrunc:
4192 case Instruction::BitCast: {
4193 setInsertPointAfterBundle(E);
4194
4195 Value *InVec = vectorizeTree(E->getOperand(0));
4196
4197 if (E->VectorizedValue) {
4198 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
4199 return E->VectorizedValue;
4200 }
4201
4202 auto *CI = cast<CastInst>(VL0);
4203 Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy);
4204 if (NeedToShuffleReuses) {
4205 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4206 E->ReuseShuffleIndices, "shuffle");
4207 }
4208 E->VectorizedValue = V;
4209 ++NumVectorInstructions;
4210 return V;
4211 }
4212 case Instruction::FCmp:
4213 case Instruction::ICmp: {
4214 setInsertPointAfterBundle(E);
4215
4216 Value *L = vectorizeTree(E->getOperand(0));
4217 Value *R = vectorizeTree(E->getOperand(1));
4218
4219 if (E->VectorizedValue) {
4220 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
4221 return E->VectorizedValue;
4222 }
4223
4224 CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate();
4225 Value *V;
4226 if (E->getOpcode() == Instruction::FCmp)
4227 V = Builder.CreateFCmp(P0, L, R);
4228 else
4229 V = Builder.CreateICmp(P0, L, R);
4230
4231 propagateIRFlags(V, E->Scalars, VL0);
4232 if (NeedToShuffleReuses) {
4233 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4234 E->ReuseShuffleIndices, "shuffle");
4235 }
4236 E->VectorizedValue = V;
4237 ++NumVectorInstructions;
4238 return V;
4239 }
4240 case Instruction::Select: {
4241 setInsertPointAfterBundle(E);
4242
4243 Value *Cond = vectorizeTree(E->getOperand(0));
4244 Value *True = vectorizeTree(E->getOperand(1));
4245 Value *False = vectorizeTree(E->getOperand(2));
4246
4247 if (E->VectorizedValue) {
4248 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
4249 return E->VectorizedValue;
4250 }
4251
4252 Value *V = Builder.CreateSelect(Cond, True, False);
4253 if (NeedToShuffleReuses) {
4254 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4255 E->ReuseShuffleIndices, "shuffle");
4256 }
4257 E->VectorizedValue = V;
4258 ++NumVectorInstructions;
4259 return V;
4260 }
4261 case Instruction::FNeg: {
4262 setInsertPointAfterBundle(E);
4263
4264 Value *Op = vectorizeTree(E->getOperand(0));
4265
4266 if (E->VectorizedValue) {
4267 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
4268 return E->VectorizedValue;
4269 }
4270
4271 Value *V = Builder.CreateUnOp(
4272 static_cast<Instruction::UnaryOps>(E->getOpcode()), Op);
4273 propagateIRFlags(V, E->Scalars, VL0);
4274 if (auto *I = dyn_cast<Instruction>(V))
4275 V = propagateMetadata(I, E->Scalars);
4276
4277 if (NeedToShuffleReuses) {
4278 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4279 E->ReuseShuffleIndices, "shuffle");
4280 }
4281 E->VectorizedValue = V;
4282 ++NumVectorInstructions;
4283
4284 return V;
4285 }
4286 case Instruction::Add:
4287 case Instruction::FAdd:
4288 case Instruction::Sub:
4289 case Instruction::FSub:
4290 case Instruction::Mul:
4291 case Instruction::FMul:
4292 case Instruction::UDiv:
4293 case Instruction::SDiv:
4294 case Instruction::FDiv:
4295 case Instruction::URem:
4296 case Instruction::SRem:
4297 case Instruction::FRem:
4298 case Instruction::Shl:
4299 case Instruction::LShr:
4300 case Instruction::AShr:
4301 case Instruction::And:
4302 case Instruction::Or:
4303 case Instruction::Xor: {
4304 setInsertPointAfterBundle(E);
4305
4306 Value *LHS = vectorizeTree(E->getOperand(0));
4307 Value *RHS = vectorizeTree(E->getOperand(1));
4308
4309 if (E->VectorizedValue) {
4310 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
4311 return E->VectorizedValue;
4312 }
4313
4314 Value *V = Builder.CreateBinOp(
4315 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS,
4316 RHS);
4317 propagateIRFlags(V, E->Scalars, VL0);
4318 if (auto *I = dyn_cast<Instruction>(V))
4319 V = propagateMetadata(I, E->Scalars);
4320
4321 if (NeedToShuffleReuses) {
4322 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4323 E->ReuseShuffleIndices, "shuffle");
4324 }
4325 E->VectorizedValue = V;
4326 ++NumVectorInstructions;
4327
4328 return V;
4329 }
4330 case Instruction::Load: {
4331 // Loads are inserted at the head of the tree because we don't want to
4332 // sink them all the way down past store instructions.
4333 bool IsReorder = E->updateStateIfReorder();
4334 if (IsReorder)
4335 VL0 = E->getMainOp();
4336 setInsertPointAfterBundle(E);
4337
4338 LoadInst *LI = cast<LoadInst>(VL0);
4339 Type *ScalarLoadTy = LI->getType();
4340 unsigned AS = LI->getPointerAddressSpace();
4341
4342 Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(),
4343 VecTy->getPointerTo(AS));
4344
4345 // The pointer operand uses an in-tree scalar so we add the new BitCast to
4346 // ExternalUses list to make sure that an extract will be generated in the
4347 // future.
4348 Value *PO = LI->getPointerOperand();
4349 if (getTreeEntry(PO))
4350 ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0));
4351
4352 MaybeAlign Alignment = MaybeAlign(LI->getAlignment());
4353 LI = Builder.CreateLoad(VecTy, VecPtr);
4354 if (!Alignment)
4355 Alignment = MaybeAlign(DL->getABITypeAlignment(ScalarLoadTy));
4356 LI->setAlignment(Alignment);
4357 Value *V = propagateMetadata(LI, E->Scalars);
4358 if (IsReorder) {
4359 OrdersType Mask;
4360 inversePermutation(E->ReorderIndices, Mask);
4361 V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()),
4362 Mask, "reorder_shuffle");
4363 }
4364 if (NeedToShuffleReuses) {
4365 // TODO: Merge this shuffle with the ReorderShuffleMask.
4366 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4367 E->ReuseShuffleIndices, "shuffle");
4368 }
4369 E->VectorizedValue = V;
4370 ++NumVectorInstructions;
4371 return V;
4372 }
4373 case Instruction::Store: {
4374 bool IsReorder = !E->ReorderIndices.empty();
4375 auto *SI = cast<StoreInst>(
4376 IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0);
4377 unsigned Alignment = SI->getAlignment();
4378 unsigned AS = SI->getPointerAddressSpace();
4379
4380 setInsertPointAfterBundle(E);
4381
4382 Value *VecValue = vectorizeTree(E->getOperand(0));
4383 if (IsReorder) {
4384 OrdersType Mask;
4385 inversePermutation(E->ReorderIndices, Mask);
4386 VecValue = Builder.CreateShuffleVector(
4387 VecValue, UndefValue::get(VecValue->getType()), E->ReorderIndices,
4388 "reorder_shuffle");
4389 }
4390 Value *ScalarPtr = SI->getPointerOperand();
4391 Value *VecPtr = Builder.CreateBitCast(
4392 ScalarPtr, VecValue->getType()->getPointerTo(AS));
4393 StoreInst *ST = Builder.CreateStore(VecValue, VecPtr);
4394
4395 // The pointer operand uses an in-tree scalar, so add the new BitCast to
4396 // ExternalUses to make sure that an extract will be generated in the
4397 // future.
4398 if (getTreeEntry(ScalarPtr))
4399 ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0));
4400
4401 if (!Alignment)
4402 Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType());
4403
4404 ST->setAlignment(Align(Alignment));
4405 Value *V = propagateMetadata(ST, E->Scalars);
4406 if (NeedToShuffleReuses) {
4407 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4408 E->ReuseShuffleIndices, "shuffle");
4409 }
4410 E->VectorizedValue = V;
4411 ++NumVectorInstructions;
4412 return V;
4413 }
4414 case Instruction::GetElementPtr: {
4415 setInsertPointAfterBundle(E);
4416
4417 Value *Op0 = vectorizeTree(E->getOperand(0));
4418
4419 std::vector<Value *> OpVecs;
4420 for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e;
4421 ++j) {
4422 ValueList &VL = E->getOperand(j);
4423 // Need to cast all elements to the same type before vectorization to
4424 // avoid crash.
4425 Type *VL0Ty = VL0->getOperand(j)->getType();
4426 Type *Ty = llvm::all_of(
4427 VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); })
4428 ? VL0Ty
4429 : DL->getIndexType(cast<GetElementPtrInst>(VL0)
4430 ->getPointerOperandType()
4431 ->getScalarType());
4432 for (Value *&V : VL) {
4433 auto *CI = cast<ConstantInt>(V);
4434 V = ConstantExpr::getIntegerCast(CI, Ty,
4435 CI->getValue().isSignBitSet());
4436 }
4437 Value *OpVec = vectorizeTree(VL);
4438 OpVecs.push_back(OpVec);
4439 }
4440
4441 Value *V = Builder.CreateGEP(
4442 cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs);
4443 if (Instruction *I = dyn_cast<Instruction>(V))
4444 V = propagateMetadata(I, E->Scalars);
4445
4446 if (NeedToShuffleReuses) {
4447 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4448 E->ReuseShuffleIndices, "shuffle");
4449 }
4450 E->VectorizedValue = V;
4451 ++NumVectorInstructions;
4452
4453 return V;
4454 }
4455 case Instruction::Call: {
4456 CallInst *CI = cast<CallInst>(VL0);
4457 setInsertPointAfterBundle(E);
4458
4459 Intrinsic::ID IID = Intrinsic::not_intrinsic;
4460 if (Function *FI = CI->getCalledFunction())
4461 IID = FI->getIntrinsicID();
4462
4463 Value *ScalarArg = nullptr;
4464 std::vector<Value *> OpVecs;
4465 for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) {
4466 ValueList OpVL;
4467 // Some intrinsics have scalar arguments. This argument should not be
4468 // vectorized.
4469 if (hasVectorInstrinsicScalarOpd(IID, j)) {
4470 CallInst *CEI = cast<CallInst>(VL0);
4471 ScalarArg = CEI->getArgOperand(j);
4472 OpVecs.push_back(CEI->getArgOperand(j));
4473 continue;
4474 }
4475
4476 Value *OpVec = vectorizeTree(E->getOperand(j));
4477 LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n");
4478 OpVecs.push_back(OpVec);
4479 }
4480
4481 Module *M = F->getParent();
4482 Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
4483 Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) };
4484 Function *CF = Intrinsic::getDeclaration(M, ID, Tys);
4485 SmallVector<OperandBundleDef, 1> OpBundles;
4486 CI->getOperandBundlesAsDefs(OpBundles);
4487 Value *V = Builder.CreateCall(CF, OpVecs, OpBundles);
4488
4489 // The scalar argument uses an in-tree scalar so we add the new vectorized
4490 // call to ExternalUses list to make sure that an extract will be
4491 // generated in the future.
4492 if (ScalarArg && getTreeEntry(ScalarArg))
4493 ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0));
4494
4495 propagateIRFlags(V, E->Scalars, VL0);
4496 if (NeedToShuffleReuses) {
4497 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4498 E->ReuseShuffleIndices, "shuffle");
4499 }
4500 E->VectorizedValue = V;
4501 ++NumVectorInstructions;
4502 return V;
4503 }
4504 case Instruction::ShuffleVector: {
4505 assert(E->isAltShuffle() &&
4506 ((Instruction::isBinaryOp(E->getOpcode()) &&
4507 Instruction::isBinaryOp(E->getAltOpcode())) ||
4508 (Instruction::isCast(E->getOpcode()) &&
4509 Instruction::isCast(E->getAltOpcode()))) &&
4510 "Invalid Shuffle Vector Operand");
4511
4512 Value *LHS = nullptr, *RHS = nullptr;
4513 if (Instruction::isBinaryOp(E->getOpcode())) {
4514 setInsertPointAfterBundle(E);
4515 LHS = vectorizeTree(E->getOperand(0));
4516 RHS = vectorizeTree(E->getOperand(1));
4517 } else {
4518 setInsertPointAfterBundle(E);
4519 LHS = vectorizeTree(E->getOperand(0));
4520 }
4521
4522 if (E->VectorizedValue) {
4523 LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
4524 return E->VectorizedValue;
4525 }
4526
4527 Value *V0, *V1;
4528 if (Instruction::isBinaryOp(E->getOpcode())) {
4529 V0 = Builder.CreateBinOp(
4530 static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS);
4531 V1 = Builder.CreateBinOp(
4532 static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS);
4533 } else {
4534 V0 = Builder.CreateCast(
4535 static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy);
4536 V1 = Builder.CreateCast(
4537 static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy);
4538 }
4539
4540 // Create shuffle to take alternate operations from the vector.
4541 // Also, gather up main and alt scalar ops to propagate IR flags to
4542 // each vector operation.
4543 ValueList OpScalars, AltScalars;
4544 unsigned e = E->Scalars.size();
4545 SmallVector<Constant *, 8> Mask(e);
4546 for (unsigned i = 0; i < e; ++i) {
4547 auto *OpInst = cast<Instruction>(E->Scalars[i]);
4548 assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode");
4549 if (OpInst->getOpcode() == E->getAltOpcode()) {
4550 Mask[i] = Builder.getInt32(e + i);
4551 AltScalars.push_back(E->Scalars[i]);
4552 } else {
4553 Mask[i] = Builder.getInt32(i);
4554 OpScalars.push_back(E->Scalars[i]);
4555 }
4556 }
4557
4558 Value *ShuffleMask = ConstantVector::get(Mask);
4559 propagateIRFlags(V0, OpScalars);
4560 propagateIRFlags(V1, AltScalars);
4561
4562 Value *V = Builder.CreateShuffleVector(V0, V1, ShuffleMask);
4563 if (Instruction *I = dyn_cast<Instruction>(V))
4564 V = propagateMetadata(I, E->Scalars);
4565 if (NeedToShuffleReuses) {
4566 V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
4567 E->ReuseShuffleIndices, "shuffle");
4568 }
4569 E->VectorizedValue = V;
4570 ++NumVectorInstructions;
4571
4572 return V;
4573 }
4574 default:
4575 llvm_unreachable("unknown inst");
4576 }
4577 return nullptr;
4578 }
4579
vectorizeTree()4580 Value *BoUpSLP::vectorizeTree() {
4581 ExtraValueToDebugLocsMap ExternallyUsedValues;
4582 return vectorizeTree(ExternallyUsedValues);
4583 }
4584
4585 Value *
vectorizeTree(ExtraValueToDebugLocsMap & ExternallyUsedValues)4586 BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) {
4587 // All blocks must be scheduled before any instructions are inserted.
4588 for (auto &BSIter : BlocksSchedules) {
4589 scheduleBlock(BSIter.second.get());
4590 }
4591
4592 Builder.SetInsertPoint(&F->getEntryBlock().front());
4593 auto *VectorRoot = vectorizeTree(VectorizableTree[0].get());
4594
4595 // If the vectorized tree can be rewritten in a smaller type, we truncate the
4596 // vectorized root. InstCombine will then rewrite the entire expression. We
4597 // sign extend the extracted values below.
4598 auto *ScalarRoot = VectorizableTree[0]->Scalars[0];
4599 if (MinBWs.count(ScalarRoot)) {
4600 if (auto *I = dyn_cast<Instruction>(VectorRoot))
4601 Builder.SetInsertPoint(&*++BasicBlock::iterator(I));
4602 auto BundleWidth = VectorizableTree[0]->Scalars.size();
4603 auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first);
4604 auto *VecTy = VectorType::get(MinTy, BundleWidth);
4605 auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy);
4606 VectorizableTree[0]->VectorizedValue = Trunc;
4607 }
4608
4609 LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size()
4610 << " values .\n");
4611
4612 // If necessary, sign-extend or zero-extend ScalarRoot to the larger type
4613 // specified by ScalarType.
4614 auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) {
4615 if (!MinBWs.count(ScalarRoot))
4616 return Ex;
4617 if (MinBWs[ScalarRoot].second)
4618 return Builder.CreateSExt(Ex, ScalarType);
4619 return Builder.CreateZExt(Ex, ScalarType);
4620 };
4621
4622 // Extract all of the elements with the external uses.
4623 for (const auto &ExternalUse : ExternalUses) {
4624 Value *Scalar = ExternalUse.Scalar;
4625 llvm::User *User = ExternalUse.User;
4626
4627 // Skip users that we already RAUW. This happens when one instruction
4628 // has multiple uses of the same value.
4629 if (User && !is_contained(Scalar->users(), User))
4630 continue;
4631 TreeEntry *E = getTreeEntry(Scalar);
4632 assert(E && "Invalid scalar");
4633 assert(E->State == TreeEntry::Vectorize && "Extracting from a gather list");
4634
4635 Value *Vec = E->VectorizedValue;
4636 assert(Vec && "Can't find vectorizable value");
4637
4638 Value *Lane = Builder.getInt32(ExternalUse.Lane);
4639 // If User == nullptr, the Scalar is used as extra arg. Generate
4640 // ExtractElement instruction and update the record for this scalar in
4641 // ExternallyUsedValues.
4642 if (!User) {
4643 assert(ExternallyUsedValues.count(Scalar) &&
4644 "Scalar with nullptr as an external user must be registered in "
4645 "ExternallyUsedValues map");
4646 if (auto *VecI = dyn_cast<Instruction>(Vec)) {
4647 Builder.SetInsertPoint(VecI->getParent(),
4648 std::next(VecI->getIterator()));
4649 } else {
4650 Builder.SetInsertPoint(&F->getEntryBlock().front());
4651 }
4652 Value *Ex = Builder.CreateExtractElement(Vec, Lane);
4653 Ex = extend(ScalarRoot, Ex, Scalar->getType());
4654 CSEBlocks.insert(cast<Instruction>(Scalar)->getParent());
4655 auto &Locs = ExternallyUsedValues[Scalar];
4656 ExternallyUsedValues.insert({Ex, Locs});
4657 ExternallyUsedValues.erase(Scalar);
4658 // Required to update internally referenced instructions.
4659 Scalar->replaceAllUsesWith(Ex);
4660 continue;
4661 }
4662
4663 // Generate extracts for out-of-tree users.
4664 // Find the insertion point for the extractelement lane.
4665 if (auto *VecI = dyn_cast<Instruction>(Vec)) {
4666 if (PHINode *PH = dyn_cast<PHINode>(User)) {
4667 for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) {
4668 if (PH->getIncomingValue(i) == Scalar) {
4669 Instruction *IncomingTerminator =
4670 PH->getIncomingBlock(i)->getTerminator();
4671 if (isa<CatchSwitchInst>(IncomingTerminator)) {
4672 Builder.SetInsertPoint(VecI->getParent(),
4673 std::next(VecI->getIterator()));
4674 } else {
4675 Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator());
4676 }
4677 Value *Ex = Builder.CreateExtractElement(Vec, Lane);
4678 Ex = extend(ScalarRoot, Ex, Scalar->getType());
4679 CSEBlocks.insert(PH->getIncomingBlock(i));
4680 PH->setOperand(i, Ex);
4681 }
4682 }
4683 } else {
4684 Builder.SetInsertPoint(cast<Instruction>(User));
4685 Value *Ex = Builder.CreateExtractElement(Vec, Lane);
4686 Ex = extend(ScalarRoot, Ex, Scalar->getType());
4687 CSEBlocks.insert(cast<Instruction>(User)->getParent());
4688 User->replaceUsesOfWith(Scalar, Ex);
4689 }
4690 } else {
4691 Builder.SetInsertPoint(&F->getEntryBlock().front());
4692 Value *Ex = Builder.CreateExtractElement(Vec, Lane);
4693 Ex = extend(ScalarRoot, Ex, Scalar->getType());
4694 CSEBlocks.insert(&F->getEntryBlock());
4695 User->replaceUsesOfWith(Scalar, Ex);
4696 }
4697
4698 LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n");
4699 }
4700
4701 // For each vectorized value:
4702 for (auto &TEPtr : VectorizableTree) {
4703 TreeEntry *Entry = TEPtr.get();
4704
4705 // No need to handle users of gathered values.
4706 if (Entry->State == TreeEntry::NeedToGather)
4707 continue;
4708
4709 assert(Entry->VectorizedValue && "Can't find vectorizable value");
4710
4711 // For each lane:
4712 for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) {
4713 Value *Scalar = Entry->Scalars[Lane];
4714
4715 #ifndef NDEBUG
4716 Type *Ty = Scalar->getType();
4717 if (!Ty->isVoidTy()) {
4718 for (User *U : Scalar->users()) {
4719 LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n");
4720
4721 // It is legal to delete users in the ignorelist.
4722 assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) &&
4723 "Deleting out-of-tree value");
4724 }
4725 }
4726 #endif
4727 LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n");
4728 eraseInstruction(cast<Instruction>(Scalar));
4729 }
4730 }
4731
4732 Builder.ClearInsertionPoint();
4733
4734 return VectorizableTree[0]->VectorizedValue;
4735 }
4736
optimizeGatherSequence()4737 void BoUpSLP::optimizeGatherSequence() {
4738 LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size()
4739 << " gather sequences instructions.\n");
4740 // LICM InsertElementInst sequences.
4741 for (Instruction *I : GatherSeq) {
4742 if (isDeleted(I))
4743 continue;
4744
4745 // Check if this block is inside a loop.
4746 Loop *L = LI->getLoopFor(I->getParent());
4747 if (!L)
4748 continue;
4749
4750 // Check if it has a preheader.
4751 BasicBlock *PreHeader = L->getLoopPreheader();
4752 if (!PreHeader)
4753 continue;
4754
4755 // If the vector or the element that we insert into it are
4756 // instructions that are defined in this basic block then we can't
4757 // hoist this instruction.
4758 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0));
4759 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1));
4760 if (Op0 && L->contains(Op0))
4761 continue;
4762 if (Op1 && L->contains(Op1))
4763 continue;
4764
4765 // We can hoist this instruction. Move it to the pre-header.
4766 I->moveBefore(PreHeader->getTerminator());
4767 }
4768
4769 // Make a list of all reachable blocks in our CSE queue.
4770 SmallVector<const DomTreeNode *, 8> CSEWorkList;
4771 CSEWorkList.reserve(CSEBlocks.size());
4772 for (BasicBlock *BB : CSEBlocks)
4773 if (DomTreeNode *N = DT->getNode(BB)) {
4774 assert(DT->isReachableFromEntry(N));
4775 CSEWorkList.push_back(N);
4776 }
4777
4778 // Sort blocks by domination. This ensures we visit a block after all blocks
4779 // dominating it are visited.
4780 llvm::stable_sort(CSEWorkList,
4781 [this](const DomTreeNode *A, const DomTreeNode *B) {
4782 return DT->properlyDominates(A, B);
4783 });
4784
4785 // Perform O(N^2) search over the gather sequences and merge identical
4786 // instructions. TODO: We can further optimize this scan if we split the
4787 // instructions into different buckets based on the insert lane.
4788 SmallVector<Instruction *, 16> Visited;
4789 for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) {
4790 assert((I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) &&
4791 "Worklist not sorted properly!");
4792 BasicBlock *BB = (*I)->getBlock();
4793 // For all instructions in blocks containing gather sequences:
4794 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) {
4795 Instruction *In = &*it++;
4796 if (isDeleted(In))
4797 continue;
4798 if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In))
4799 continue;
4800
4801 // Check if we can replace this instruction with any of the
4802 // visited instructions.
4803 for (Instruction *v : Visited) {
4804 if (In->isIdenticalTo(v) &&
4805 DT->dominates(v->getParent(), In->getParent())) {
4806 In->replaceAllUsesWith(v);
4807 eraseInstruction(In);
4808 In = nullptr;
4809 break;
4810 }
4811 }
4812 if (In) {
4813 assert(!is_contained(Visited, In));
4814 Visited.push_back(In);
4815 }
4816 }
4817 }
4818 CSEBlocks.clear();
4819 GatherSeq.clear();
4820 }
4821
4822 // Groups the instructions to a bundle (which is then a single scheduling entity)
4823 // and schedules instructions until the bundle gets ready.
4824 Optional<BoUpSLP::ScheduleData *>
tryScheduleBundle(ArrayRef<Value * > VL,BoUpSLP * SLP,const InstructionsState & S)4825 BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP,
4826 const InstructionsState &S) {
4827 if (isa<PHINode>(S.OpValue))
4828 return nullptr;
4829
4830 // Initialize the instruction bundle.
4831 Instruction *OldScheduleEnd = ScheduleEnd;
4832 ScheduleData *PrevInBundle = nullptr;
4833 ScheduleData *Bundle = nullptr;
4834 bool ReSchedule = false;
4835 LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n");
4836
4837 // Make sure that the scheduling region contains all
4838 // instructions of the bundle.
4839 for (Value *V : VL) {
4840 if (!extendSchedulingRegion(V, S))
4841 return None;
4842 }
4843
4844 for (Value *V : VL) {
4845 ScheduleData *BundleMember = getScheduleData(V);
4846 assert(BundleMember &&
4847 "no ScheduleData for bundle member (maybe not in same basic block)");
4848 if (BundleMember->IsScheduled) {
4849 // A bundle member was scheduled as single instruction before and now
4850 // needs to be scheduled as part of the bundle. We just get rid of the
4851 // existing schedule.
4852 LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember
4853 << " was already scheduled\n");
4854 ReSchedule = true;
4855 }
4856 assert(BundleMember->isSchedulingEntity() &&
4857 "bundle member already part of other bundle");
4858 if (PrevInBundle) {
4859 PrevInBundle->NextInBundle = BundleMember;
4860 } else {
4861 Bundle = BundleMember;
4862 }
4863 BundleMember->UnscheduledDepsInBundle = 0;
4864 Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps;
4865
4866 // Group the instructions to a bundle.
4867 BundleMember->FirstInBundle = Bundle;
4868 PrevInBundle = BundleMember;
4869 }
4870 if (ScheduleEnd != OldScheduleEnd) {
4871 // The scheduling region got new instructions at the lower end (or it is a
4872 // new region for the first bundle). This makes it necessary to
4873 // recalculate all dependencies.
4874 // It is seldom that this needs to be done a second time after adding the
4875 // initial bundle to the region.
4876 for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
4877 doForAllOpcodes(I, [](ScheduleData *SD) {
4878 SD->clearDependencies();
4879 });
4880 }
4881 ReSchedule = true;
4882 }
4883 if (ReSchedule) {
4884 resetSchedule();
4885 initialFillReadyList(ReadyInsts);
4886 }
4887 assert(Bundle && "Failed to find schedule bundle");
4888
4889 LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block "
4890 << BB->getName() << "\n");
4891
4892 calculateDependencies(Bundle, true, SLP);
4893
4894 // Now try to schedule the new bundle. As soon as the bundle is "ready" it
4895 // means that there are no cyclic dependencies and we can schedule it.
4896 // Note that's important that we don't "schedule" the bundle yet (see
4897 // cancelScheduling).
4898 while (!Bundle->isReady() && !ReadyInsts.empty()) {
4899
4900 ScheduleData *pickedSD = ReadyInsts.back();
4901 ReadyInsts.pop_back();
4902
4903 if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) {
4904 schedule(pickedSD, ReadyInsts);
4905 }
4906 }
4907 if (!Bundle->isReady()) {
4908 cancelScheduling(VL, S.OpValue);
4909 return None;
4910 }
4911 return Bundle;
4912 }
4913
cancelScheduling(ArrayRef<Value * > VL,Value * OpValue)4914 void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL,
4915 Value *OpValue) {
4916 if (isa<PHINode>(OpValue))
4917 return;
4918
4919 ScheduleData *Bundle = getScheduleData(OpValue);
4920 LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n");
4921 assert(!Bundle->IsScheduled &&
4922 "Can't cancel bundle which is already scheduled");
4923 assert(Bundle->isSchedulingEntity() && Bundle->isPartOfBundle() &&
4924 "tried to unbundle something which is not a bundle");
4925
4926 // Un-bundle: make single instructions out of the bundle.
4927 ScheduleData *BundleMember = Bundle;
4928 while (BundleMember) {
4929 assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links");
4930 BundleMember->FirstInBundle = BundleMember;
4931 ScheduleData *Next = BundleMember->NextInBundle;
4932 BundleMember->NextInBundle = nullptr;
4933 BundleMember->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps;
4934 if (BundleMember->UnscheduledDepsInBundle == 0) {
4935 ReadyInsts.insert(BundleMember);
4936 }
4937 BundleMember = Next;
4938 }
4939 }
4940
allocateScheduleDataChunks()4941 BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() {
4942 // Allocate a new ScheduleData for the instruction.
4943 if (ChunkPos >= ChunkSize) {
4944 ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize));
4945 ChunkPos = 0;
4946 }
4947 return &(ScheduleDataChunks.back()[ChunkPos++]);
4948 }
4949
extendSchedulingRegion(Value * V,const InstructionsState & S)4950 bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V,
4951 const InstructionsState &S) {
4952 if (getScheduleData(V, isOneOf(S, V)))
4953 return true;
4954 Instruction *I = dyn_cast<Instruction>(V);
4955 assert(I && "bundle member must be an instruction");
4956 assert(!isa<PHINode>(I) && "phi nodes don't need to be scheduled");
4957 auto &&CheckSheduleForI = [this, &S](Instruction *I) -> bool {
4958 ScheduleData *ISD = getScheduleData(I);
4959 if (!ISD)
4960 return false;
4961 assert(isInSchedulingRegion(ISD) &&
4962 "ScheduleData not in scheduling region");
4963 ScheduleData *SD = allocateScheduleDataChunks();
4964 SD->Inst = I;
4965 SD->init(SchedulingRegionID, S.OpValue);
4966 ExtraScheduleDataMap[I][S.OpValue] = SD;
4967 return true;
4968 };
4969 if (CheckSheduleForI(I))
4970 return true;
4971 if (!ScheduleStart) {
4972 // It's the first instruction in the new region.
4973 initScheduleData(I, I->getNextNode(), nullptr, nullptr);
4974 ScheduleStart = I;
4975 ScheduleEnd = I->getNextNode();
4976 if (isOneOf(S, I) != I)
4977 CheckSheduleForI(I);
4978 assert(ScheduleEnd && "tried to vectorize a terminator?");
4979 LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n");
4980 return true;
4981 }
4982 // Search up and down at the same time, because we don't know if the new
4983 // instruction is above or below the existing scheduling region.
4984 BasicBlock::reverse_iterator UpIter =
4985 ++ScheduleStart->getIterator().getReverse();
4986 BasicBlock::reverse_iterator UpperEnd = BB->rend();
4987 BasicBlock::iterator DownIter = ScheduleEnd->getIterator();
4988 BasicBlock::iterator LowerEnd = BB->end();
4989 while (true) {
4990 if (++ScheduleRegionSize > ScheduleRegionSizeLimit) {
4991 LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n");
4992 return false;
4993 }
4994
4995 if (UpIter != UpperEnd) {
4996 if (&*UpIter == I) {
4997 initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion);
4998 ScheduleStart = I;
4999 if (isOneOf(S, I) != I)
5000 CheckSheduleForI(I);
5001 LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I
5002 << "\n");
5003 return true;
5004 }
5005 ++UpIter;
5006 }
5007 if (DownIter != LowerEnd) {
5008 if (&*DownIter == I) {
5009 initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion,
5010 nullptr);
5011 ScheduleEnd = I->getNextNode();
5012 if (isOneOf(S, I) != I)
5013 CheckSheduleForI(I);
5014 assert(ScheduleEnd && "tried to vectorize a terminator?");
5015 LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I
5016 << "\n");
5017 return true;
5018 }
5019 ++DownIter;
5020 }
5021 assert((UpIter != UpperEnd || DownIter != LowerEnd) &&
5022 "instruction not found in block");
5023 }
5024 return true;
5025 }
5026
initScheduleData(Instruction * FromI,Instruction * ToI,ScheduleData * PrevLoadStore,ScheduleData * NextLoadStore)5027 void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI,
5028 Instruction *ToI,
5029 ScheduleData *PrevLoadStore,
5030 ScheduleData *NextLoadStore) {
5031 ScheduleData *CurrentLoadStore = PrevLoadStore;
5032 for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) {
5033 ScheduleData *SD = ScheduleDataMap[I];
5034 if (!SD) {
5035 SD = allocateScheduleDataChunks();
5036 ScheduleDataMap[I] = SD;
5037 SD->Inst = I;
5038 }
5039 assert(!isInSchedulingRegion(SD) &&
5040 "new ScheduleData already in scheduling region");
5041 SD->init(SchedulingRegionID, I);
5042
5043 if (I->mayReadOrWriteMemory() &&
5044 (!isa<IntrinsicInst>(I) ||
5045 cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect)) {
5046 // Update the linked list of memory accessing instructions.
5047 if (CurrentLoadStore) {
5048 CurrentLoadStore->NextLoadStore = SD;
5049 } else {
5050 FirstLoadStoreInRegion = SD;
5051 }
5052 CurrentLoadStore = SD;
5053 }
5054 }
5055 if (NextLoadStore) {
5056 if (CurrentLoadStore)
5057 CurrentLoadStore->NextLoadStore = NextLoadStore;
5058 } else {
5059 LastLoadStoreInRegion = CurrentLoadStore;
5060 }
5061 }
5062
calculateDependencies(ScheduleData * SD,bool InsertInReadyList,BoUpSLP * SLP)5063 void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD,
5064 bool InsertInReadyList,
5065 BoUpSLP *SLP) {
5066 assert(SD->isSchedulingEntity());
5067
5068 SmallVector<ScheduleData *, 10> WorkList;
5069 WorkList.push_back(SD);
5070
5071 while (!WorkList.empty()) {
5072 ScheduleData *SD = WorkList.back();
5073 WorkList.pop_back();
5074
5075 ScheduleData *BundleMember = SD;
5076 while (BundleMember) {
5077 assert(isInSchedulingRegion(BundleMember));
5078 if (!BundleMember->hasValidDependencies()) {
5079
5080 LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember
5081 << "\n");
5082 BundleMember->Dependencies = 0;
5083 BundleMember->resetUnscheduledDeps();
5084
5085 // Handle def-use chain dependencies.
5086 if (BundleMember->OpValue != BundleMember->Inst) {
5087 ScheduleData *UseSD = getScheduleData(BundleMember->Inst);
5088 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) {
5089 BundleMember->Dependencies++;
5090 ScheduleData *DestBundle = UseSD->FirstInBundle;
5091 if (!DestBundle->IsScheduled)
5092 BundleMember->incrementUnscheduledDeps(1);
5093 if (!DestBundle->hasValidDependencies())
5094 WorkList.push_back(DestBundle);
5095 }
5096 } else {
5097 for (User *U : BundleMember->Inst->users()) {
5098 if (isa<Instruction>(U)) {
5099 ScheduleData *UseSD = getScheduleData(U);
5100 if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) {
5101 BundleMember->Dependencies++;
5102 ScheduleData *DestBundle = UseSD->FirstInBundle;
5103 if (!DestBundle->IsScheduled)
5104 BundleMember->incrementUnscheduledDeps(1);
5105 if (!DestBundle->hasValidDependencies())
5106 WorkList.push_back(DestBundle);
5107 }
5108 } else {
5109 // I'm not sure if this can ever happen. But we need to be safe.
5110 // This lets the instruction/bundle never be scheduled and
5111 // eventually disable vectorization.
5112 BundleMember->Dependencies++;
5113 BundleMember->incrementUnscheduledDeps(1);
5114 }
5115 }
5116 }
5117
5118 // Handle the memory dependencies.
5119 ScheduleData *DepDest = BundleMember->NextLoadStore;
5120 if (DepDest) {
5121 Instruction *SrcInst = BundleMember->Inst;
5122 MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA);
5123 bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory();
5124 unsigned numAliased = 0;
5125 unsigned DistToSrc = 1;
5126
5127 while (DepDest) {
5128 assert(isInSchedulingRegion(DepDest));
5129
5130 // We have two limits to reduce the complexity:
5131 // 1) AliasedCheckLimit: It's a small limit to reduce calls to
5132 // SLP->isAliased (which is the expensive part in this loop).
5133 // 2) MaxMemDepDistance: It's for very large blocks and it aborts
5134 // the whole loop (even if the loop is fast, it's quadratic).
5135 // It's important for the loop break condition (see below) to
5136 // check this limit even between two read-only instructions.
5137 if (DistToSrc >= MaxMemDepDistance ||
5138 ((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) &&
5139 (numAliased >= AliasedCheckLimit ||
5140 SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) {
5141
5142 // We increment the counter only if the locations are aliased
5143 // (instead of counting all alias checks). This gives a better
5144 // balance between reduced runtime and accurate dependencies.
5145 numAliased++;
5146
5147 DepDest->MemoryDependencies.push_back(BundleMember);
5148 BundleMember->Dependencies++;
5149 ScheduleData *DestBundle = DepDest->FirstInBundle;
5150 if (!DestBundle->IsScheduled) {
5151 BundleMember->incrementUnscheduledDeps(1);
5152 }
5153 if (!DestBundle->hasValidDependencies()) {
5154 WorkList.push_back(DestBundle);
5155 }
5156 }
5157 DepDest = DepDest->NextLoadStore;
5158
5159 // Example, explaining the loop break condition: Let's assume our
5160 // starting instruction is i0 and MaxMemDepDistance = 3.
5161 //
5162 // +--------v--v--v
5163 // i0,i1,i2,i3,i4,i5,i6,i7,i8
5164 // +--------^--^--^
5165 //
5166 // MaxMemDepDistance let us stop alias-checking at i3 and we add
5167 // dependencies from i0 to i3,i4,.. (even if they are not aliased).
5168 // Previously we already added dependencies from i3 to i6,i7,i8
5169 // (because of MaxMemDepDistance). As we added a dependency from
5170 // i0 to i3, we have transitive dependencies from i0 to i6,i7,i8
5171 // and we can abort this loop at i6.
5172 if (DistToSrc >= 2 * MaxMemDepDistance)
5173 break;
5174 DistToSrc++;
5175 }
5176 }
5177 }
5178 BundleMember = BundleMember->NextInBundle;
5179 }
5180 if (InsertInReadyList && SD->isReady()) {
5181 ReadyInsts.push_back(SD);
5182 LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst
5183 << "\n");
5184 }
5185 }
5186 }
5187
resetSchedule()5188 void BoUpSLP::BlockScheduling::resetSchedule() {
5189 assert(ScheduleStart &&
5190 "tried to reset schedule on block which has not been scheduled");
5191 for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
5192 doForAllOpcodes(I, [&](ScheduleData *SD) {
5193 assert(isInSchedulingRegion(SD) &&
5194 "ScheduleData not in scheduling region");
5195 SD->IsScheduled = false;
5196 SD->resetUnscheduledDeps();
5197 });
5198 }
5199 ReadyInsts.clear();
5200 }
5201
scheduleBlock(BlockScheduling * BS)5202 void BoUpSLP::scheduleBlock(BlockScheduling *BS) {
5203 if (!BS->ScheduleStart)
5204 return;
5205
5206 LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n");
5207
5208 BS->resetSchedule();
5209
5210 // For the real scheduling we use a more sophisticated ready-list: it is
5211 // sorted by the original instruction location. This lets the final schedule
5212 // be as close as possible to the original instruction order.
5213 struct ScheduleDataCompare {
5214 bool operator()(ScheduleData *SD1, ScheduleData *SD2) const {
5215 return SD2->SchedulingPriority < SD1->SchedulingPriority;
5216 }
5217 };
5218 std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts;
5219
5220 // Ensure that all dependency data is updated and fill the ready-list with
5221 // initial instructions.
5222 int Idx = 0;
5223 int NumToSchedule = 0;
5224 for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd;
5225 I = I->getNextNode()) {
5226 BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) {
5227 assert(SD->isPartOfBundle() ==
5228 (getTreeEntry(SD->Inst) != nullptr) &&
5229 "scheduler and vectorizer bundle mismatch");
5230 SD->FirstInBundle->SchedulingPriority = Idx++;
5231 if (SD->isSchedulingEntity()) {
5232 BS->calculateDependencies(SD, false, this);
5233 NumToSchedule++;
5234 }
5235 });
5236 }
5237 BS->initialFillReadyList(ReadyInsts);
5238
5239 Instruction *LastScheduledInst = BS->ScheduleEnd;
5240
5241 // Do the "real" scheduling.
5242 while (!ReadyInsts.empty()) {
5243 ScheduleData *picked = *ReadyInsts.begin();
5244 ReadyInsts.erase(ReadyInsts.begin());
5245
5246 // Move the scheduled instruction(s) to their dedicated places, if not
5247 // there yet.
5248 ScheduleData *BundleMember = picked;
5249 while (BundleMember) {
5250 Instruction *pickedInst = BundleMember->Inst;
5251 if (LastScheduledInst->getNextNode() != pickedInst) {
5252 BS->BB->getInstList().remove(pickedInst);
5253 BS->BB->getInstList().insert(LastScheduledInst->getIterator(),
5254 pickedInst);
5255 }
5256 LastScheduledInst = pickedInst;
5257 BundleMember = BundleMember->NextInBundle;
5258 }
5259
5260 BS->schedule(picked, ReadyInsts);
5261 NumToSchedule--;
5262 }
5263 assert(NumToSchedule == 0 && "could not schedule all instructions");
5264
5265 // Avoid duplicate scheduling of the block.
5266 BS->ScheduleStart = nullptr;
5267 }
5268
getVectorElementSize(Value * V) const5269 unsigned BoUpSLP::getVectorElementSize(Value *V) const {
5270 // If V is a store, just return the width of the stored value without
5271 // traversing the expression tree. This is the common case.
5272 if (auto *Store = dyn_cast<StoreInst>(V))
5273 return DL->getTypeSizeInBits(Store->getValueOperand()->getType());
5274
5275 // If V is not a store, we can traverse the expression tree to find loads
5276 // that feed it. The type of the loaded value may indicate a more suitable
5277 // width than V's type. We want to base the vector element size on the width
5278 // of memory operations where possible.
5279 SmallVector<Instruction *, 16> Worklist;
5280 SmallPtrSet<Instruction *, 16> Visited;
5281 if (auto *I = dyn_cast<Instruction>(V))
5282 Worklist.push_back(I);
5283
5284 // Traverse the expression tree in bottom-up order looking for loads. If we
5285 // encounter an instruction we don't yet handle, we give up.
5286 auto MaxWidth = 0u;
5287 auto FoundUnknownInst = false;
5288 while (!Worklist.empty() && !FoundUnknownInst) {
5289 auto *I = Worklist.pop_back_val();
5290 Visited.insert(I);
5291
5292 // We should only be looking at scalar instructions here. If the current
5293 // instruction has a vector type, give up.
5294 auto *Ty = I->getType();
5295 if (isa<VectorType>(Ty))
5296 FoundUnknownInst = true;
5297
5298 // If the current instruction is a load, update MaxWidth to reflect the
5299 // width of the loaded value.
5300 else if (isa<LoadInst>(I))
5301 MaxWidth = std::max<unsigned>(MaxWidth, DL->getTypeSizeInBits(Ty));
5302
5303 // Otherwise, we need to visit the operands of the instruction. We only
5304 // handle the interesting cases from buildTree here. If an operand is an
5305 // instruction we haven't yet visited, we add it to the worklist.
5306 else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) ||
5307 isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) {
5308 for (Use &U : I->operands())
5309 if (auto *J = dyn_cast<Instruction>(U.get()))
5310 if (!Visited.count(J))
5311 Worklist.push_back(J);
5312 }
5313
5314 // If we don't yet handle the instruction, give up.
5315 else
5316 FoundUnknownInst = true;
5317 }
5318
5319 // If we didn't encounter a memory access in the expression tree, or if we
5320 // gave up for some reason, just return the width of V.
5321 if (!MaxWidth || FoundUnknownInst)
5322 return DL->getTypeSizeInBits(V->getType());
5323
5324 // Otherwise, return the maximum width we found.
5325 return MaxWidth;
5326 }
5327
5328 // Determine if a value V in a vectorizable expression Expr can be demoted to a
5329 // smaller type with a truncation. We collect the values that will be demoted
5330 // in ToDemote and additional roots that require investigating in Roots.
collectValuesToDemote(Value * V,SmallPtrSetImpl<Value * > & Expr,SmallVectorImpl<Value * > & ToDemote,SmallVectorImpl<Value * > & Roots)5331 static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr,
5332 SmallVectorImpl<Value *> &ToDemote,
5333 SmallVectorImpl<Value *> &Roots) {
5334 // We can always demote constants.
5335 if (isa<Constant>(V)) {
5336 ToDemote.push_back(V);
5337 return true;
5338 }
5339
5340 // If the value is not an instruction in the expression with only one use, it
5341 // cannot be demoted.
5342 auto *I = dyn_cast<Instruction>(V);
5343 if (!I || !I->hasOneUse() || !Expr.count(I))
5344 return false;
5345
5346 switch (I->getOpcode()) {
5347
5348 // We can always demote truncations and extensions. Since truncations can
5349 // seed additional demotion, we save the truncated value.
5350 case Instruction::Trunc:
5351 Roots.push_back(I->getOperand(0));
5352 break;
5353 case Instruction::ZExt:
5354 case Instruction::SExt:
5355 break;
5356
5357 // We can demote certain binary operations if we can demote both of their
5358 // operands.
5359 case Instruction::Add:
5360 case Instruction::Sub:
5361 case Instruction::Mul:
5362 case Instruction::And:
5363 case Instruction::Or:
5364 case Instruction::Xor:
5365 if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) ||
5366 !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots))
5367 return false;
5368 break;
5369
5370 // We can demote selects if we can demote their true and false values.
5371 case Instruction::Select: {
5372 SelectInst *SI = cast<SelectInst>(I);
5373 if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) ||
5374 !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots))
5375 return false;
5376 break;
5377 }
5378
5379 // We can demote phis if we can demote all their incoming operands. Note that
5380 // we don't need to worry about cycles since we ensure single use above.
5381 case Instruction::PHI: {
5382 PHINode *PN = cast<PHINode>(I);
5383 for (Value *IncValue : PN->incoming_values())
5384 if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots))
5385 return false;
5386 break;
5387 }
5388
5389 // Otherwise, conservatively give up.
5390 default:
5391 return false;
5392 }
5393
5394 // Record the value that we can demote.
5395 ToDemote.push_back(V);
5396 return true;
5397 }
5398
computeMinimumValueSizes()5399 void BoUpSLP::computeMinimumValueSizes() {
5400 // If there are no external uses, the expression tree must be rooted by a
5401 // store. We can't demote in-memory values, so there is nothing to do here.
5402 if (ExternalUses.empty())
5403 return;
5404
5405 // We only attempt to truncate integer expressions.
5406 auto &TreeRoot = VectorizableTree[0]->Scalars;
5407 auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType());
5408 if (!TreeRootIT)
5409 return;
5410
5411 // If the expression is not rooted by a store, these roots should have
5412 // external uses. We will rely on InstCombine to rewrite the expression in
5413 // the narrower type. However, InstCombine only rewrites single-use values.
5414 // This means that if a tree entry other than a root is used externally, it
5415 // must have multiple uses and InstCombine will not rewrite it. The code
5416 // below ensures that only the roots are used externally.
5417 SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end());
5418 for (auto &EU : ExternalUses)
5419 if (!Expr.erase(EU.Scalar))
5420 return;
5421 if (!Expr.empty())
5422 return;
5423
5424 // Collect the scalar values of the vectorizable expression. We will use this
5425 // context to determine which values can be demoted. If we see a truncation,
5426 // we mark it as seeding another demotion.
5427 for (auto &EntryPtr : VectorizableTree)
5428 Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end());
5429
5430 // Ensure the roots of the vectorizable tree don't form a cycle. They must
5431 // have a single external user that is not in the vectorizable tree.
5432 for (auto *Root : TreeRoot)
5433 if (!Root->hasOneUse() || Expr.count(*Root->user_begin()))
5434 return;
5435
5436 // Conservatively determine if we can actually truncate the roots of the
5437 // expression. Collect the values that can be demoted in ToDemote and
5438 // additional roots that require investigating in Roots.
5439 SmallVector<Value *, 32> ToDemote;
5440 SmallVector<Value *, 4> Roots;
5441 for (auto *Root : TreeRoot)
5442 if (!collectValuesToDemote(Root, Expr, ToDemote, Roots))
5443 return;
5444
5445 // The maximum bit width required to represent all the values that can be
5446 // demoted without loss of precision. It would be safe to truncate the roots
5447 // of the expression to this width.
5448 auto MaxBitWidth = 8u;
5449
5450 // We first check if all the bits of the roots are demanded. If they're not,
5451 // we can truncate the roots to this narrower type.
5452 for (auto *Root : TreeRoot) {
5453 auto Mask = DB->getDemandedBits(cast<Instruction>(Root));
5454 MaxBitWidth = std::max<unsigned>(
5455 Mask.getBitWidth() - Mask.countLeadingZeros(), MaxBitWidth);
5456 }
5457
5458 // True if the roots can be zero-extended back to their original type, rather
5459 // than sign-extended. We know that if the leading bits are not demanded, we
5460 // can safely zero-extend. So we initialize IsKnownPositive to True.
5461 bool IsKnownPositive = true;
5462
5463 // If all the bits of the roots are demanded, we can try a little harder to
5464 // compute a narrower type. This can happen, for example, if the roots are
5465 // getelementptr indices. InstCombine promotes these indices to the pointer
5466 // width. Thus, all their bits are technically demanded even though the
5467 // address computation might be vectorized in a smaller type.
5468 //
5469 // We start by looking at each entry that can be demoted. We compute the
5470 // maximum bit width required to store the scalar by using ValueTracking to
5471 // compute the number of high-order bits we can truncate.
5472 if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) &&
5473 llvm::all_of(TreeRoot, [](Value *R) {
5474 assert(R->hasOneUse() && "Root should have only one use!");
5475 return isa<GetElementPtrInst>(R->user_back());
5476 })) {
5477 MaxBitWidth = 8u;
5478
5479 // Determine if the sign bit of all the roots is known to be zero. If not,
5480 // IsKnownPositive is set to False.
5481 IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) {
5482 KnownBits Known = computeKnownBits(R, *DL);
5483 return Known.isNonNegative();
5484 });
5485
5486 // Determine the maximum number of bits required to store the scalar
5487 // values.
5488 for (auto *Scalar : ToDemote) {
5489 auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT);
5490 auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType());
5491 MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth);
5492 }
5493
5494 // If we can't prove that the sign bit is zero, we must add one to the
5495 // maximum bit width to account for the unknown sign bit. This preserves
5496 // the existing sign bit so we can safely sign-extend the root back to the
5497 // original type. Otherwise, if we know the sign bit is zero, we will
5498 // zero-extend the root instead.
5499 //
5500 // FIXME: This is somewhat suboptimal, as there will be cases where adding
5501 // one to the maximum bit width will yield a larger-than-necessary
5502 // type. In general, we need to add an extra bit only if we can't
5503 // prove that the upper bit of the original type is equal to the
5504 // upper bit of the proposed smaller type. If these two bits are the
5505 // same (either zero or one) we know that sign-extending from the
5506 // smaller type will result in the same value. Here, since we can't
5507 // yet prove this, we are just making the proposed smaller type
5508 // larger to ensure correctness.
5509 if (!IsKnownPositive)
5510 ++MaxBitWidth;
5511 }
5512
5513 // Round MaxBitWidth up to the next power-of-two.
5514 if (!isPowerOf2_64(MaxBitWidth))
5515 MaxBitWidth = NextPowerOf2(MaxBitWidth);
5516
5517 // If the maximum bit width we compute is less than the with of the roots'
5518 // type, we can proceed with the narrowing. Otherwise, do nothing.
5519 if (MaxBitWidth >= TreeRootIT->getBitWidth())
5520 return;
5521
5522 // If we can truncate the root, we must collect additional values that might
5523 // be demoted as a result. That is, those seeded by truncations we will
5524 // modify.
5525 while (!Roots.empty())
5526 collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots);
5527
5528 // Finally, map the values we can demote to the maximum bit with we computed.
5529 for (auto *Scalar : ToDemote)
5530 MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive);
5531 }
5532
5533 namespace {
5534
5535 /// The SLPVectorizer Pass.
5536 struct SLPVectorizer : public FunctionPass {
5537 SLPVectorizerPass Impl;
5538
5539 /// Pass identification, replacement for typeid
5540 static char ID;
5541
SLPVectorizer__anoncd21379e1711::SLPVectorizer5542 explicit SLPVectorizer() : FunctionPass(ID) {
5543 initializeSLPVectorizerPass(*PassRegistry::getPassRegistry());
5544 }
5545
doInitialization__anoncd21379e1711::SLPVectorizer5546 bool doInitialization(Module &M) override {
5547 return false;
5548 }
5549
runOnFunction__anoncd21379e1711::SLPVectorizer5550 bool runOnFunction(Function &F) override {
5551 if (skipFunction(F))
5552 return false;
5553
5554 auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
5555 auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
5556 auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>();
5557 auto *TLI = TLIP ? &TLIP->getTLI(F) : nullptr;
5558 auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
5559 auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
5560 auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
5561 auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
5562 auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits();
5563 auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE();
5564
5565 return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE);
5566 }
5567
getAnalysisUsage__anoncd21379e1711::SLPVectorizer5568 void getAnalysisUsage(AnalysisUsage &AU) const override {
5569 FunctionPass::getAnalysisUsage(AU);
5570 AU.addRequired<AssumptionCacheTracker>();
5571 AU.addRequired<ScalarEvolutionWrapperPass>();
5572 AU.addRequired<AAResultsWrapperPass>();
5573 AU.addRequired<TargetTransformInfoWrapperPass>();
5574 AU.addRequired<LoopInfoWrapperPass>();
5575 AU.addRequired<DominatorTreeWrapperPass>();
5576 AU.addRequired<DemandedBitsWrapperPass>();
5577 AU.addRequired<OptimizationRemarkEmitterWrapperPass>();
5578 AU.addPreserved<LoopInfoWrapperPass>();
5579 AU.addPreserved<DominatorTreeWrapperPass>();
5580 AU.addPreserved<AAResultsWrapperPass>();
5581 AU.addPreserved<GlobalsAAWrapperPass>();
5582 AU.setPreservesCFG();
5583 }
5584 };
5585
5586 } // end anonymous namespace
5587
run(Function & F,FunctionAnalysisManager & AM)5588 PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) {
5589 auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F);
5590 auto *TTI = &AM.getResult<TargetIRAnalysis>(F);
5591 auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F);
5592 auto *AA = &AM.getResult<AAManager>(F);
5593 auto *LI = &AM.getResult<LoopAnalysis>(F);
5594 auto *DT = &AM.getResult<DominatorTreeAnalysis>(F);
5595 auto *AC = &AM.getResult<AssumptionAnalysis>(F);
5596 auto *DB = &AM.getResult<DemandedBitsAnalysis>(F);
5597 auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F);
5598
5599 bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE);
5600 if (!Changed)
5601 return PreservedAnalyses::all();
5602
5603 PreservedAnalyses PA;
5604 PA.preserveSet<CFGAnalyses>();
5605 PA.preserve<AAManager>();
5606 PA.preserve<GlobalsAA>();
5607 return PA;
5608 }
5609
runImpl(Function & F,ScalarEvolution * SE_,TargetTransformInfo * TTI_,TargetLibraryInfo * TLI_,AliasAnalysis * AA_,LoopInfo * LI_,DominatorTree * DT_,AssumptionCache * AC_,DemandedBits * DB_,OptimizationRemarkEmitter * ORE_)5610 bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_,
5611 TargetTransformInfo *TTI_,
5612 TargetLibraryInfo *TLI_, AliasAnalysis *AA_,
5613 LoopInfo *LI_, DominatorTree *DT_,
5614 AssumptionCache *AC_, DemandedBits *DB_,
5615 OptimizationRemarkEmitter *ORE_) {
5616 SE = SE_;
5617 TTI = TTI_;
5618 TLI = TLI_;
5619 AA = AA_;
5620 LI = LI_;
5621 DT = DT_;
5622 AC = AC_;
5623 DB = DB_;
5624 DL = &F.getParent()->getDataLayout();
5625
5626 Stores.clear();
5627 GEPs.clear();
5628 bool Changed = false;
5629
5630 // If the target claims to have no vector registers don't attempt
5631 // vectorization.
5632 if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true)))
5633 return false;
5634
5635 // Don't vectorize when the attribute NoImplicitFloat is used.
5636 if (F.hasFnAttribute(Attribute::NoImplicitFloat))
5637 return false;
5638
5639 LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n");
5640
5641 // Use the bottom up slp vectorizer to construct chains that start with
5642 // store instructions.
5643 BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_);
5644
5645 // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to
5646 // delete instructions.
5647
5648 // Scan the blocks in the function in post order.
5649 for (auto BB : post_order(&F.getEntryBlock())) {
5650 collectSeedInstructions(BB);
5651
5652 // Vectorize trees that end at stores.
5653 if (!Stores.empty()) {
5654 LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size()
5655 << " underlying objects.\n");
5656 Changed |= vectorizeStoreChains(R);
5657 }
5658
5659 // Vectorize trees that end at reductions.
5660 Changed |= vectorizeChainsInBlock(BB, R);
5661
5662 // Vectorize the index computations of getelementptr instructions. This
5663 // is primarily intended to catch gather-like idioms ending at
5664 // non-consecutive loads.
5665 if (!GEPs.empty()) {
5666 LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size()
5667 << " underlying objects.\n");
5668 Changed |= vectorizeGEPIndices(BB, R);
5669 }
5670 }
5671
5672 if (Changed) {
5673 R.optimizeGatherSequence();
5674 LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n");
5675 LLVM_DEBUG(verifyFunction(F));
5676 }
5677 return Changed;
5678 }
5679
vectorizeStoreChain(ArrayRef<Value * > Chain,BoUpSLP & R,unsigned Idx)5680 bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R,
5681 unsigned Idx) {
5682 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size()
5683 << "\n");
5684 const unsigned Sz = R.getVectorElementSize(Chain[0]);
5685 const unsigned MinVF = R.getMinVecRegSize() / Sz;
5686 unsigned VF = Chain.size();
5687
5688 if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF)
5689 return false;
5690
5691 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx
5692 << "\n");
5693
5694 R.buildTree(Chain);
5695 Optional<ArrayRef<unsigned>> Order = R.bestOrder();
5696 // TODO: Handle orders of size less than number of elements in the vector.
5697 if (Order && Order->size() == Chain.size()) {
5698 // TODO: reorder tree nodes without tree rebuilding.
5699 SmallVector<Value *, 4> ReorderedOps(Chain.rbegin(), Chain.rend());
5700 llvm::transform(*Order, ReorderedOps.begin(),
5701 [Chain](const unsigned Idx) { return Chain[Idx]; });
5702 R.buildTree(ReorderedOps);
5703 }
5704 if (R.isTreeTinyAndNotFullyVectorizable())
5705 return false;
5706
5707 R.computeMinimumValueSizes();
5708
5709 int Cost = R.getTreeCost();
5710
5711 LLVM_DEBUG(dbgs() << "SLP: Found cost=" << Cost << " for VF=" << VF << "\n");
5712 if (Cost < -SLPCostThreshold) {
5713 LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost=" << Cost << "\n");
5714
5715 using namespace ore;
5716
5717 R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized",
5718 cast<StoreInst>(Chain[0]))
5719 << "Stores SLP vectorized with cost " << NV("Cost", Cost)
5720 << " and with tree size "
5721 << NV("TreeSize", R.getTreeSize()));
5722
5723 R.vectorizeTree();
5724 return true;
5725 }
5726
5727 return false;
5728 }
5729
vectorizeStores(ArrayRef<StoreInst * > Stores,BoUpSLP & R)5730 bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores,
5731 BoUpSLP &R) {
5732 // We may run into multiple chains that merge into a single chain. We mark the
5733 // stores that we vectorized so that we don't visit the same store twice.
5734 BoUpSLP::ValueSet VectorizedStores;
5735 bool Changed = false;
5736
5737 int E = Stores.size();
5738 SmallBitVector Tails(E, false);
5739 SmallVector<int, 16> ConsecutiveChain(E, E + 1);
5740 int MaxIter = MaxStoreLookup.getValue();
5741 int IterCnt;
5742 auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter,
5743 &ConsecutiveChain](int K, int Idx) {
5744 if (IterCnt >= MaxIter)
5745 return true;
5746 ++IterCnt;
5747 if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE))
5748 return false;
5749
5750 Tails.set(Idx);
5751 ConsecutiveChain[K] = Idx;
5752 return true;
5753 };
5754 // Do a quadratic search on all of the given stores in reverse order and find
5755 // all of the pairs of stores that follow each other.
5756 for (int Idx = E - 1; Idx >= 0; --Idx) {
5757 // If a store has multiple consecutive store candidates, search according
5758 // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ...
5759 // This is because usually pairing with immediate succeeding or preceding
5760 // candidate create the best chance to find slp vectorization opportunity.
5761 const int MaxLookDepth = std::max(E - Idx, Idx + 1);
5762 IterCnt = 0;
5763 for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset)
5764 if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) ||
5765 (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx)))
5766 break;
5767 }
5768
5769 // For stores that start but don't end a link in the chain:
5770 for (int Cnt = E; Cnt > 0; --Cnt) {
5771 int I = Cnt - 1;
5772 if (ConsecutiveChain[I] == E + 1 || Tails.test(I))
5773 continue;
5774 // We found a store instr that starts a chain. Now follow the chain and try
5775 // to vectorize it.
5776 BoUpSLP::ValueList Operands;
5777 // Collect the chain into a list.
5778 while (I != E + 1 && !VectorizedStores.count(Stores[I])) {
5779 Operands.push_back(Stores[I]);
5780 // Move to the next value in the chain.
5781 I = ConsecutiveChain[I];
5782 }
5783
5784 // If a vector register can't hold 1 element, we are done.
5785 unsigned MaxVecRegSize = R.getMaxVecRegSize();
5786 unsigned EltSize = R.getVectorElementSize(Stores[0]);
5787 if (MaxVecRegSize % EltSize != 0)
5788 continue;
5789
5790 unsigned MaxElts = MaxVecRegSize / EltSize;
5791 // FIXME: Is division-by-2 the correct step? Should we assert that the
5792 // register size is a power-of-2?
5793 unsigned StartIdx = 0;
5794 for (unsigned Size = llvm::PowerOf2Ceil(MaxElts); Size >= 2; Size /= 2) {
5795 for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) {
5796 ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size);
5797 if (!VectorizedStores.count(Slice.front()) &&
5798 !VectorizedStores.count(Slice.back()) &&
5799 vectorizeStoreChain(Slice, R, Cnt)) {
5800 // Mark the vectorized stores so that we don't vectorize them again.
5801 VectorizedStores.insert(Slice.begin(), Slice.end());
5802 Changed = true;
5803 // If we vectorized initial block, no need to try to vectorize it
5804 // again.
5805 if (Cnt == StartIdx)
5806 StartIdx += Size;
5807 Cnt += Size;
5808 continue;
5809 }
5810 ++Cnt;
5811 }
5812 // Check if the whole array was vectorized already - exit.
5813 if (StartIdx >= Operands.size())
5814 break;
5815 }
5816 }
5817
5818 return Changed;
5819 }
5820
collectSeedInstructions(BasicBlock * BB)5821 void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) {
5822 // Initialize the collections. We will make a single pass over the block.
5823 Stores.clear();
5824 GEPs.clear();
5825
5826 // Visit the store and getelementptr instructions in BB and organize them in
5827 // Stores and GEPs according to the underlying objects of their pointer
5828 // operands.
5829 for (Instruction &I : *BB) {
5830 // Ignore store instructions that are volatile or have a pointer operand
5831 // that doesn't point to a scalar type.
5832 if (auto *SI = dyn_cast<StoreInst>(&I)) {
5833 if (!SI->isSimple())
5834 continue;
5835 if (!isValidElementType(SI->getValueOperand()->getType()))
5836 continue;
5837 Stores[GetUnderlyingObject(SI->getPointerOperand(), *DL)].push_back(SI);
5838 }
5839
5840 // Ignore getelementptr instructions that have more than one index, a
5841 // constant index, or a pointer operand that doesn't point to a scalar
5842 // type.
5843 else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) {
5844 auto Idx = GEP->idx_begin()->get();
5845 if (GEP->getNumIndices() > 1 || isa<Constant>(Idx))
5846 continue;
5847 if (!isValidElementType(Idx->getType()))
5848 continue;
5849 if (GEP->getType()->isVectorTy())
5850 continue;
5851 GEPs[GEP->getPointerOperand()].push_back(GEP);
5852 }
5853 }
5854 }
5855
tryToVectorizePair(Value * A,Value * B,BoUpSLP & R)5856 bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) {
5857 if (!A || !B)
5858 return false;
5859 Value *VL[] = { A, B };
5860 return tryToVectorizeList(VL, R, /*UserCost=*/0, true);
5861 }
5862
tryToVectorizeList(ArrayRef<Value * > VL,BoUpSLP & R,int UserCost,bool AllowReorder)5863 bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R,
5864 int UserCost, bool AllowReorder) {
5865 if (VL.size() < 2)
5866 return false;
5867
5868 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = "
5869 << VL.size() << ".\n");
5870
5871 // Check that all of the parts are scalar instructions of the same type,
5872 // we permit an alternate opcode via InstructionsState.
5873 InstructionsState S = getSameOpcode(VL);
5874 if (!S.getOpcode())
5875 return false;
5876
5877 Instruction *I0 = cast<Instruction>(S.OpValue);
5878 unsigned Sz = R.getVectorElementSize(I0);
5879 unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz);
5880 unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF);
5881 if (MaxVF < 2) {
5882 R.getORE()->emit([&]() {
5883 return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0)
5884 << "Cannot SLP vectorize list: vectorization factor "
5885 << "less than 2 is not supported";
5886 });
5887 return false;
5888 }
5889
5890 for (Value *V : VL) {
5891 Type *Ty = V->getType();
5892 if (!isValidElementType(Ty)) {
5893 // NOTE: the following will give user internal llvm type name, which may
5894 // not be useful.
5895 R.getORE()->emit([&]() {
5896 std::string type_str;
5897 llvm::raw_string_ostream rso(type_str);
5898 Ty->print(rso);
5899 return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0)
5900 << "Cannot SLP vectorize list: type "
5901 << rso.str() + " is unsupported by vectorizer";
5902 });
5903 return false;
5904 }
5905 }
5906
5907 bool Changed = false;
5908 bool CandidateFound = false;
5909 int MinCost = SLPCostThreshold;
5910
5911 unsigned NextInst = 0, MaxInst = VL.size();
5912 for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF; VF /= 2) {
5913 // No actual vectorization should happen, if number of parts is the same as
5914 // provided vectorization factor (i.e. the scalar type is used for vector
5915 // code during codegen).
5916 auto *VecTy = VectorType::get(VL[0]->getType(), VF);
5917 if (TTI->getNumberOfParts(VecTy) == VF)
5918 continue;
5919 for (unsigned I = NextInst; I < MaxInst; ++I) {
5920 unsigned OpsWidth = 0;
5921
5922 if (I + VF > MaxInst)
5923 OpsWidth = MaxInst - I;
5924 else
5925 OpsWidth = VF;
5926
5927 if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2)
5928 break;
5929
5930 ArrayRef<Value *> Ops = VL.slice(I, OpsWidth);
5931 // Check that a previous iteration of this loop did not delete the Value.
5932 if (llvm::any_of(Ops, [&R](Value *V) {
5933 auto *I = dyn_cast<Instruction>(V);
5934 return I && R.isDeleted(I);
5935 }))
5936 continue;
5937
5938 LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations "
5939 << "\n");
5940
5941 R.buildTree(Ops);
5942 Optional<ArrayRef<unsigned>> Order = R.bestOrder();
5943 // TODO: check if we can allow reordering for more cases.
5944 if (AllowReorder && Order) {
5945 // TODO: reorder tree nodes without tree rebuilding.
5946 // Conceptually, there is nothing actually preventing us from trying to
5947 // reorder a larger list. In fact, we do exactly this when vectorizing
5948 // reductions. However, at this point, we only expect to get here when
5949 // there are exactly two operations.
5950 assert(Ops.size() == 2);
5951 Value *ReorderedOps[] = {Ops[1], Ops[0]};
5952 R.buildTree(ReorderedOps, None);
5953 }
5954 if (R.isTreeTinyAndNotFullyVectorizable())
5955 continue;
5956
5957 R.computeMinimumValueSizes();
5958 int Cost = R.getTreeCost() - UserCost;
5959 CandidateFound = true;
5960 MinCost = std::min(MinCost, Cost);
5961
5962 if (Cost < -SLPCostThreshold) {
5963 LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n");
5964 R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList",
5965 cast<Instruction>(Ops[0]))
5966 << "SLP vectorized with cost " << ore::NV("Cost", Cost)
5967 << " and with tree size "
5968 << ore::NV("TreeSize", R.getTreeSize()));
5969
5970 R.vectorizeTree();
5971 // Move to the next bundle.
5972 I += VF - 1;
5973 NextInst = I + 1;
5974 Changed = true;
5975 }
5976 }
5977 }
5978
5979 if (!Changed && CandidateFound) {
5980 R.getORE()->emit([&]() {
5981 return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0)
5982 << "List vectorization was possible but not beneficial with cost "
5983 << ore::NV("Cost", MinCost) << " >= "
5984 << ore::NV("Treshold", -SLPCostThreshold);
5985 });
5986 } else if (!Changed) {
5987 R.getORE()->emit([&]() {
5988 return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0)
5989 << "Cannot SLP vectorize list: vectorization was impossible"
5990 << " with available vectorization factors";
5991 });
5992 }
5993 return Changed;
5994 }
5995
tryToVectorize(Instruction * I,BoUpSLP & R)5996 bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) {
5997 if (!I)
5998 return false;
5999
6000 if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I))
6001 return false;
6002
6003 Value *P = I->getParent();
6004
6005 // Vectorize in current basic block only.
6006 auto *Op0 = dyn_cast<Instruction>(I->getOperand(0));
6007 auto *Op1 = dyn_cast<Instruction>(I->getOperand(1));
6008 if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P)
6009 return false;
6010
6011 // Try to vectorize V.
6012 if (tryToVectorizePair(Op0, Op1, R))
6013 return true;
6014
6015 auto *A = dyn_cast<BinaryOperator>(Op0);
6016 auto *B = dyn_cast<BinaryOperator>(Op1);
6017 // Try to skip B.
6018 if (B && B->hasOneUse()) {
6019 auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0));
6020 auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1));
6021 if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R))
6022 return true;
6023 if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R))
6024 return true;
6025 }
6026
6027 // Try to skip A.
6028 if (A && A->hasOneUse()) {
6029 auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0));
6030 auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1));
6031 if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R))
6032 return true;
6033 if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R))
6034 return true;
6035 }
6036 return false;
6037 }
6038
6039 /// Generate a shuffle mask to be used in a reduction tree.
6040 ///
6041 /// \param VecLen The length of the vector to be reduced.
6042 /// \param NumEltsToRdx The number of elements that should be reduced in the
6043 /// vector.
6044 /// \param IsPairwise Whether the reduction is a pairwise or splitting
6045 /// reduction. A pairwise reduction will generate a mask of
6046 /// <0,2,...> or <1,3,..> while a splitting reduction will generate
6047 /// <2,3, undef,undef> for a vector of 4 and NumElts = 2.
6048 /// \param IsLeft True will generate a mask of even elements, odd otherwise.
createRdxShuffleMask(unsigned VecLen,unsigned NumEltsToRdx,bool IsPairwise,bool IsLeft,IRBuilder<> & Builder)6049 static Value *createRdxShuffleMask(unsigned VecLen, unsigned NumEltsToRdx,
6050 bool IsPairwise, bool IsLeft,
6051 IRBuilder<> &Builder) {
6052 assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask");
6053
6054 SmallVector<Constant *, 32> ShuffleMask(
6055 VecLen, UndefValue::get(Builder.getInt32Ty()));
6056
6057 if (IsPairwise)
6058 // Build a mask of 0, 2, ... (left) or 1, 3, ... (right).
6059 for (unsigned i = 0; i != NumEltsToRdx; ++i)
6060 ShuffleMask[i] = Builder.getInt32(2 * i + !IsLeft);
6061 else
6062 // Move the upper half of the vector to the lower half.
6063 for (unsigned i = 0; i != NumEltsToRdx; ++i)
6064 ShuffleMask[i] = Builder.getInt32(NumEltsToRdx + i);
6065
6066 return ConstantVector::get(ShuffleMask);
6067 }
6068
6069 namespace {
6070
6071 /// Model horizontal reductions.
6072 ///
6073 /// A horizontal reduction is a tree of reduction operations (currently add and
6074 /// fadd) that has operations that can be put into a vector as its leaf.
6075 /// For example, this tree:
6076 ///
6077 /// mul mul mul mul
6078 /// \ / \ /
6079 /// + +
6080 /// \ /
6081 /// +
6082 /// This tree has "mul" as its reduced values and "+" as its reduction
6083 /// operations. A reduction might be feeding into a store or a binary operation
6084 /// feeding a phi.
6085 /// ...
6086 /// \ /
6087 /// +
6088 /// |
6089 /// phi +=
6090 ///
6091 /// Or:
6092 /// ...
6093 /// \ /
6094 /// +
6095 /// |
6096 /// *p =
6097 ///
6098 class HorizontalReduction {
6099 using ReductionOpsType = SmallVector<Value *, 16>;
6100 using ReductionOpsListType = SmallVector<ReductionOpsType, 2>;
6101 ReductionOpsListType ReductionOps;
6102 SmallVector<Value *, 32> ReducedVals;
6103 // Use map vector to make stable output.
6104 MapVector<Instruction *, Value *> ExtraArgs;
6105
6106 /// Kind of the reduction data.
6107 enum ReductionKind {
6108 RK_None, /// Not a reduction.
6109 RK_Arithmetic, /// Binary reduction data.
6110 RK_Min, /// Minimum reduction data.
6111 RK_UMin, /// Unsigned minimum reduction data.
6112 RK_Max, /// Maximum reduction data.
6113 RK_UMax, /// Unsigned maximum reduction data.
6114 };
6115
6116 /// Contains info about operation, like its opcode, left and right operands.
6117 class OperationData {
6118 /// Opcode of the instruction.
6119 unsigned Opcode = 0;
6120
6121 /// Left operand of the reduction operation.
6122 Value *LHS = nullptr;
6123
6124 /// Right operand of the reduction operation.
6125 Value *RHS = nullptr;
6126
6127 /// Kind of the reduction operation.
6128 ReductionKind Kind = RK_None;
6129
6130 /// True if float point min/max reduction has no NaNs.
6131 bool NoNaN = false;
6132
6133 /// Checks if the reduction operation can be vectorized.
isVectorizable() const6134 bool isVectorizable() const {
6135 return LHS && RHS &&
6136 // We currently only support add/mul/logical && min/max reductions.
6137 ((Kind == RK_Arithmetic &&
6138 (Opcode == Instruction::Add || Opcode == Instruction::FAdd ||
6139 Opcode == Instruction::Mul || Opcode == Instruction::FMul ||
6140 Opcode == Instruction::And || Opcode == Instruction::Or ||
6141 Opcode == Instruction::Xor)) ||
6142 ((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) &&
6143 (Kind == RK_Min || Kind == RK_Max)) ||
6144 (Opcode == Instruction::ICmp &&
6145 (Kind == RK_UMin || Kind == RK_UMax)));
6146 }
6147
6148 /// Creates reduction operation with the current opcode.
createOp(IRBuilder<> & Builder,const Twine & Name) const6149 Value *createOp(IRBuilder<> &Builder, const Twine &Name) const {
6150 assert(isVectorizable() &&
6151 "Expected add|fadd or min/max reduction operation.");
6152 Value *Cmp = nullptr;
6153 switch (Kind) {
6154 case RK_Arithmetic:
6155 return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS,
6156 Name);
6157 case RK_Min:
6158 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS)
6159 : Builder.CreateFCmpOLT(LHS, RHS);
6160 return Builder.CreateSelect(Cmp, LHS, RHS, Name);
6161 case RK_Max:
6162 Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS)
6163 : Builder.CreateFCmpOGT(LHS, RHS);
6164 return Builder.CreateSelect(Cmp, LHS, RHS, Name);
6165 case RK_UMin:
6166 assert(Opcode == Instruction::ICmp && "Expected integer types.");
6167 Cmp = Builder.CreateICmpULT(LHS, RHS);
6168 return Builder.CreateSelect(Cmp, LHS, RHS, Name);
6169 case RK_UMax:
6170 assert(Opcode == Instruction::ICmp && "Expected integer types.");
6171 Cmp = Builder.CreateICmpUGT(LHS, RHS);
6172 return Builder.CreateSelect(Cmp, LHS, RHS, Name);
6173 case RK_None:
6174 break;
6175 }
6176 llvm_unreachable("Unknown reduction operation.");
6177 }
6178
6179 public:
6180 explicit OperationData() = default;
6181
6182 /// Construction for reduced values. They are identified by opcode only and
6183 /// don't have associated LHS/RHS values.
OperationData(Value * V)6184 explicit OperationData(Value *V) {
6185 if (auto *I = dyn_cast<Instruction>(V))
6186 Opcode = I->getOpcode();
6187 }
6188
6189 /// Constructor for reduction operations with opcode and its left and
6190 /// right operands.
OperationData(unsigned Opcode,Value * LHS,Value * RHS,ReductionKind Kind,bool NoNaN=false)6191 OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind,
6192 bool NoNaN = false)
6193 : Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) {
6194 assert(Kind != RK_None && "One of the reduction operations is expected.");
6195 }
6196
operator bool() const6197 explicit operator bool() const { return Opcode; }
6198
6199 /// Return true if this operation is any kind of minimum or maximum.
isMinMax() const6200 bool isMinMax() const {
6201 switch (Kind) {
6202 case RK_Arithmetic:
6203 return false;
6204 case RK_Min:
6205 case RK_Max:
6206 case RK_UMin:
6207 case RK_UMax:
6208 return true;
6209 case RK_None:
6210 break;
6211 }
6212 llvm_unreachable("Reduction kind is not set");
6213 }
6214
6215 /// Get the index of the first operand.
getFirstOperandIndex() const6216 unsigned getFirstOperandIndex() const {
6217 assert(!!*this && "The opcode is not set.");
6218 // We allow calling this before 'Kind' is set, so handle that specially.
6219 if (Kind == RK_None)
6220 return 0;
6221 return isMinMax() ? 1 : 0;
6222 }
6223
6224 /// Total number of operands in the reduction operation.
getNumberOfOperands() const6225 unsigned getNumberOfOperands() const {
6226 assert(Kind != RK_None && !!*this && LHS && RHS &&
6227 "Expected reduction operation.");
6228 return isMinMax() ? 3 : 2;
6229 }
6230
6231 /// Checks if the operation has the same parent as \p P.
hasSameParent(Instruction * I,Value * P,bool IsRedOp) const6232 bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const {
6233 assert(Kind != RK_None && !!*this && LHS && RHS &&
6234 "Expected reduction operation.");
6235 if (!IsRedOp)
6236 return I->getParent() == P;
6237 if (isMinMax()) {
6238 // SelectInst must be used twice while the condition op must have single
6239 // use only.
6240 auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition());
6241 return I->getParent() == P && Cmp && Cmp->getParent() == P;
6242 }
6243 // Arithmetic reduction operation must be used once only.
6244 return I->getParent() == P;
6245 }
6246
6247 /// Expected number of uses for reduction operations/reduced values.
hasRequiredNumberOfUses(Instruction * I,bool IsReductionOp) const6248 bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const {
6249 assert(Kind != RK_None && !!*this && LHS && RHS &&
6250 "Expected reduction operation.");
6251 if (isMinMax())
6252 return I->hasNUses(2) &&
6253 (!IsReductionOp ||
6254 cast<SelectInst>(I)->getCondition()->hasOneUse());
6255 return I->hasOneUse();
6256 }
6257
6258 /// Initializes the list of reduction operations.
initReductionOps(ReductionOpsListType & ReductionOps)6259 void initReductionOps(ReductionOpsListType &ReductionOps) {
6260 assert(Kind != RK_None && !!*this && LHS && RHS &&
6261 "Expected reduction operation.");
6262 if (isMinMax())
6263 ReductionOps.assign(2, ReductionOpsType());
6264 else
6265 ReductionOps.assign(1, ReductionOpsType());
6266 }
6267
6268 /// Add all reduction operations for the reduction instruction \p I.
addReductionOps(Instruction * I,ReductionOpsListType & ReductionOps)6269 void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) {
6270 assert(Kind != RK_None && !!*this && LHS && RHS &&
6271 "Expected reduction operation.");
6272 if (isMinMax()) {
6273 ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition());
6274 ReductionOps[1].emplace_back(I);
6275 } else {
6276 ReductionOps[0].emplace_back(I);
6277 }
6278 }
6279
6280 /// Checks if instruction is associative and can be vectorized.
isAssociative(Instruction * I) const6281 bool isAssociative(Instruction *I) const {
6282 assert(Kind != RK_None && *this && LHS && RHS &&
6283 "Expected reduction operation.");
6284 switch (Kind) {
6285 case RK_Arithmetic:
6286 return I->isAssociative();
6287 case RK_Min:
6288 case RK_Max:
6289 return Opcode == Instruction::ICmp ||
6290 cast<Instruction>(I->getOperand(0))->isFast();
6291 case RK_UMin:
6292 case RK_UMax:
6293 assert(Opcode == Instruction::ICmp &&
6294 "Only integer compare operation is expected.");
6295 return true;
6296 case RK_None:
6297 break;
6298 }
6299 llvm_unreachable("Reduction kind is not set");
6300 }
6301
6302 /// Checks if the reduction operation can be vectorized.
isVectorizable(Instruction * I) const6303 bool isVectorizable(Instruction *I) const {
6304 return isVectorizable() && isAssociative(I);
6305 }
6306
6307 /// Checks if two operation data are both a reduction op or both a reduced
6308 /// value.
operator ==(const OperationData & OD) const6309 bool operator==(const OperationData &OD) const {
6310 assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) &&
6311 "One of the comparing operations is incorrect.");
6312 return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode);
6313 }
operator !=(const OperationData & OD) const6314 bool operator!=(const OperationData &OD) const { return !(*this == OD); }
clear()6315 void clear() {
6316 Opcode = 0;
6317 LHS = nullptr;
6318 RHS = nullptr;
6319 Kind = RK_None;
6320 NoNaN = false;
6321 }
6322
6323 /// Get the opcode of the reduction operation.
getOpcode() const6324 unsigned getOpcode() const {
6325 assert(isVectorizable() && "Expected vectorizable operation.");
6326 return Opcode;
6327 }
6328
6329 /// Get kind of reduction data.
getKind() const6330 ReductionKind getKind() const { return Kind; }
getLHS() const6331 Value *getLHS() const { return LHS; }
getRHS() const6332 Value *getRHS() const { return RHS; }
getConditionType() const6333 Type *getConditionType() const {
6334 return isMinMax() ? CmpInst::makeCmpResultType(LHS->getType()) : nullptr;
6335 }
6336
6337 /// Creates reduction operation with the current opcode with the IR flags
6338 /// from \p ReductionOps.
createOp(IRBuilder<> & Builder,const Twine & Name,const ReductionOpsListType & ReductionOps) const6339 Value *createOp(IRBuilder<> &Builder, const Twine &Name,
6340 const ReductionOpsListType &ReductionOps) const {
6341 assert(isVectorizable() &&
6342 "Expected add|fadd or min/max reduction operation.");
6343 auto *Op = createOp(Builder, Name);
6344 switch (Kind) {
6345 case RK_Arithmetic:
6346 propagateIRFlags(Op, ReductionOps[0]);
6347 return Op;
6348 case RK_Min:
6349 case RK_Max:
6350 case RK_UMin:
6351 case RK_UMax:
6352 if (auto *SI = dyn_cast<SelectInst>(Op))
6353 propagateIRFlags(SI->getCondition(), ReductionOps[0]);
6354 propagateIRFlags(Op, ReductionOps[1]);
6355 return Op;
6356 case RK_None:
6357 break;
6358 }
6359 llvm_unreachable("Unknown reduction operation.");
6360 }
6361 /// Creates reduction operation with the current opcode with the IR flags
6362 /// from \p I.
createOp(IRBuilder<> & Builder,const Twine & Name,Instruction * I) const6363 Value *createOp(IRBuilder<> &Builder, const Twine &Name,
6364 Instruction *I) const {
6365 assert(isVectorizable() &&
6366 "Expected add|fadd or min/max reduction operation.");
6367 auto *Op = createOp(Builder, Name);
6368 switch (Kind) {
6369 case RK_Arithmetic:
6370 propagateIRFlags(Op, I);
6371 return Op;
6372 case RK_Min:
6373 case RK_Max:
6374 case RK_UMin:
6375 case RK_UMax:
6376 if (auto *SI = dyn_cast<SelectInst>(Op)) {
6377 propagateIRFlags(SI->getCondition(),
6378 cast<SelectInst>(I)->getCondition());
6379 }
6380 propagateIRFlags(Op, I);
6381 return Op;
6382 case RK_None:
6383 break;
6384 }
6385 llvm_unreachable("Unknown reduction operation.");
6386 }
6387
getFlags() const6388 TargetTransformInfo::ReductionFlags getFlags() const {
6389 TargetTransformInfo::ReductionFlags Flags;
6390 Flags.NoNaN = NoNaN;
6391 switch (Kind) {
6392 case RK_Arithmetic:
6393 break;
6394 case RK_Min:
6395 Flags.IsSigned = Opcode == Instruction::ICmp;
6396 Flags.IsMaxOp = false;
6397 break;
6398 case RK_Max:
6399 Flags.IsSigned = Opcode == Instruction::ICmp;
6400 Flags.IsMaxOp = true;
6401 break;
6402 case RK_UMin:
6403 Flags.IsSigned = false;
6404 Flags.IsMaxOp = false;
6405 break;
6406 case RK_UMax:
6407 Flags.IsSigned = false;
6408 Flags.IsMaxOp = true;
6409 break;
6410 case RK_None:
6411 llvm_unreachable("Reduction kind is not set");
6412 }
6413 return Flags;
6414 }
6415 };
6416
6417 WeakTrackingVH ReductionRoot;
6418
6419 /// The operation data of the reduction operation.
6420 OperationData ReductionData;
6421
6422 /// The operation data of the values we perform a reduction on.
6423 OperationData ReducedValueData;
6424
6425 /// Should we model this reduction as a pairwise reduction tree or a tree that
6426 /// splits the vector in halves and adds those halves.
6427 bool IsPairwiseReduction = false;
6428
6429 /// Checks if the ParentStackElem.first should be marked as a reduction
6430 /// operation with an extra argument or as extra argument itself.
markExtraArg(std::pair<Instruction *,unsigned> & ParentStackElem,Value * ExtraArg)6431 void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem,
6432 Value *ExtraArg) {
6433 if (ExtraArgs.count(ParentStackElem.first)) {
6434 ExtraArgs[ParentStackElem.first] = nullptr;
6435 // We ran into something like:
6436 // ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg.
6437 // The whole ParentStackElem.first should be considered as an extra value
6438 // in this case.
6439 // Do not perform analysis of remaining operands of ParentStackElem.first
6440 // instruction, this whole instruction is an extra argument.
6441 ParentStackElem.second = ParentStackElem.first->getNumOperands();
6442 } else {
6443 // We ran into something like:
6444 // ParentStackElem.first += ... + ExtraArg + ...
6445 ExtraArgs[ParentStackElem.first] = ExtraArg;
6446 }
6447 }
6448
getOperationData(Value * V)6449 static OperationData getOperationData(Value *V) {
6450 if (!V)
6451 return OperationData();
6452
6453 Value *LHS;
6454 Value *RHS;
6455 if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) {
6456 return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS,
6457 RK_Arithmetic);
6458 }
6459 if (auto *Select = dyn_cast<SelectInst>(V)) {
6460 // Look for a min/max pattern.
6461 if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) {
6462 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin);
6463 } else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) {
6464 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min);
6465 } else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) ||
6466 m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) {
6467 return OperationData(
6468 Instruction::FCmp, LHS, RHS, RK_Min,
6469 cast<Instruction>(Select->getCondition())->hasNoNaNs());
6470 } else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) {
6471 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax);
6472 } else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) {
6473 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max);
6474 } else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) ||
6475 m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) {
6476 return OperationData(
6477 Instruction::FCmp, LHS, RHS, RK_Max,
6478 cast<Instruction>(Select->getCondition())->hasNoNaNs());
6479 } else {
6480 // Try harder: look for min/max pattern based on instructions producing
6481 // same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2).
6482 // During the intermediate stages of SLP, it's very common to have
6483 // pattern like this (since optimizeGatherSequence is run only once
6484 // at the end):
6485 // %1 = extractelement <2 x i32> %a, i32 0
6486 // %2 = extractelement <2 x i32> %a, i32 1
6487 // %cond = icmp sgt i32 %1, %2
6488 // %3 = extractelement <2 x i32> %a, i32 0
6489 // %4 = extractelement <2 x i32> %a, i32 1
6490 // %select = select i1 %cond, i32 %3, i32 %4
6491 CmpInst::Predicate Pred;
6492 Instruction *L1;
6493 Instruction *L2;
6494
6495 LHS = Select->getTrueValue();
6496 RHS = Select->getFalseValue();
6497 Value *Cond = Select->getCondition();
6498
6499 // TODO: Support inverse predicates.
6500 if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) {
6501 if (!isa<ExtractElementInst>(RHS) ||
6502 !L2->isIdenticalTo(cast<Instruction>(RHS)))
6503 return OperationData(V);
6504 } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) {
6505 if (!isa<ExtractElementInst>(LHS) ||
6506 !L1->isIdenticalTo(cast<Instruction>(LHS)))
6507 return OperationData(V);
6508 } else {
6509 if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS))
6510 return OperationData(V);
6511 if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) ||
6512 !L1->isIdenticalTo(cast<Instruction>(LHS)) ||
6513 !L2->isIdenticalTo(cast<Instruction>(RHS)))
6514 return OperationData(V);
6515 }
6516 switch (Pred) {
6517 default:
6518 return OperationData(V);
6519
6520 case CmpInst::ICMP_ULT:
6521 case CmpInst::ICMP_ULE:
6522 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin);
6523
6524 case CmpInst::ICMP_SLT:
6525 case CmpInst::ICMP_SLE:
6526 return OperationData(Instruction::ICmp, LHS, RHS, RK_Min);
6527
6528 case CmpInst::FCMP_OLT:
6529 case CmpInst::FCMP_OLE:
6530 case CmpInst::FCMP_ULT:
6531 case CmpInst::FCMP_ULE:
6532 return OperationData(Instruction::FCmp, LHS, RHS, RK_Min,
6533 cast<Instruction>(Cond)->hasNoNaNs());
6534
6535 case CmpInst::ICMP_UGT:
6536 case CmpInst::ICMP_UGE:
6537 return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax);
6538
6539 case CmpInst::ICMP_SGT:
6540 case CmpInst::ICMP_SGE:
6541 return OperationData(Instruction::ICmp, LHS, RHS, RK_Max);
6542
6543 case CmpInst::FCMP_OGT:
6544 case CmpInst::FCMP_OGE:
6545 case CmpInst::FCMP_UGT:
6546 case CmpInst::FCMP_UGE:
6547 return OperationData(Instruction::FCmp, LHS, RHS, RK_Max,
6548 cast<Instruction>(Cond)->hasNoNaNs());
6549 }
6550 }
6551 }
6552 return OperationData(V);
6553 }
6554
6555 public:
6556 HorizontalReduction() = default;
6557
6558 /// Try to find a reduction tree.
matchAssociativeReduction(PHINode * Phi,Instruction * B)6559 bool matchAssociativeReduction(PHINode *Phi, Instruction *B) {
6560 assert((!Phi || is_contained(Phi->operands(), B)) &&
6561 "Thi phi needs to use the binary operator");
6562
6563 ReductionData = getOperationData(B);
6564
6565 // We could have a initial reductions that is not an add.
6566 // r *= v1 + v2 + v3 + v4
6567 // In such a case start looking for a tree rooted in the first '+'.
6568 if (Phi) {
6569 if (ReductionData.getLHS() == Phi) {
6570 Phi = nullptr;
6571 B = dyn_cast<Instruction>(ReductionData.getRHS());
6572 ReductionData = getOperationData(B);
6573 } else if (ReductionData.getRHS() == Phi) {
6574 Phi = nullptr;
6575 B = dyn_cast<Instruction>(ReductionData.getLHS());
6576 ReductionData = getOperationData(B);
6577 }
6578 }
6579
6580 if (!ReductionData.isVectorizable(B))
6581 return false;
6582
6583 Type *Ty = B->getType();
6584 if (!isValidElementType(Ty))
6585 return false;
6586 if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy())
6587 return false;
6588
6589 ReducedValueData.clear();
6590 ReductionRoot = B;
6591
6592 // Post order traverse the reduction tree starting at B. We only handle true
6593 // trees containing only binary operators.
6594 SmallVector<std::pair<Instruction *, unsigned>, 32> Stack;
6595 Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex()));
6596 ReductionData.initReductionOps(ReductionOps);
6597 while (!Stack.empty()) {
6598 Instruction *TreeN = Stack.back().first;
6599 unsigned EdgeToVist = Stack.back().second++;
6600 OperationData OpData = getOperationData(TreeN);
6601 bool IsReducedValue = OpData != ReductionData;
6602
6603 // Postorder vist.
6604 if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) {
6605 if (IsReducedValue)
6606 ReducedVals.push_back(TreeN);
6607 else {
6608 auto I = ExtraArgs.find(TreeN);
6609 if (I != ExtraArgs.end() && !I->second) {
6610 // Check if TreeN is an extra argument of its parent operation.
6611 if (Stack.size() <= 1) {
6612 // TreeN can't be an extra argument as it is a root reduction
6613 // operation.
6614 return false;
6615 }
6616 // Yes, TreeN is an extra argument, do not add it to a list of
6617 // reduction operations.
6618 // Stack[Stack.size() - 2] always points to the parent operation.
6619 markExtraArg(Stack[Stack.size() - 2], TreeN);
6620 ExtraArgs.erase(TreeN);
6621 } else
6622 ReductionData.addReductionOps(TreeN, ReductionOps);
6623 }
6624 // Retract.
6625 Stack.pop_back();
6626 continue;
6627 }
6628
6629 // Visit left or right.
6630 Value *NextV = TreeN->getOperand(EdgeToVist);
6631 if (NextV != Phi) {
6632 auto *I = dyn_cast<Instruction>(NextV);
6633 OpData = getOperationData(I);
6634 // Continue analysis if the next operand is a reduction operation or
6635 // (possibly) a reduced value. If the reduced value opcode is not set,
6636 // the first met operation != reduction operation is considered as the
6637 // reduced value class.
6638 if (I && (!ReducedValueData || OpData == ReducedValueData ||
6639 OpData == ReductionData)) {
6640 const bool IsReductionOperation = OpData == ReductionData;
6641 // Only handle trees in the current basic block.
6642 if (!ReductionData.hasSameParent(I, B->getParent(),
6643 IsReductionOperation)) {
6644 // I is an extra argument for TreeN (its parent operation).
6645 markExtraArg(Stack.back(), I);
6646 continue;
6647 }
6648
6649 // Each tree node needs to have minimal number of users except for the
6650 // ultimate reduction.
6651 if (!ReductionData.hasRequiredNumberOfUses(I,
6652 OpData == ReductionData) &&
6653 I != B) {
6654 // I is an extra argument for TreeN (its parent operation).
6655 markExtraArg(Stack.back(), I);
6656 continue;
6657 }
6658
6659 if (IsReductionOperation) {
6660 // We need to be able to reassociate the reduction operations.
6661 if (!OpData.isAssociative(I)) {
6662 // I is an extra argument for TreeN (its parent operation).
6663 markExtraArg(Stack.back(), I);
6664 continue;
6665 }
6666 } else if (ReducedValueData &&
6667 ReducedValueData != OpData) {
6668 // Make sure that the opcodes of the operations that we are going to
6669 // reduce match.
6670 // I is an extra argument for TreeN (its parent operation).
6671 markExtraArg(Stack.back(), I);
6672 continue;
6673 } else if (!ReducedValueData)
6674 ReducedValueData = OpData;
6675
6676 Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex()));
6677 continue;
6678 }
6679 }
6680 // NextV is an extra argument for TreeN (its parent operation).
6681 markExtraArg(Stack.back(), NextV);
6682 }
6683 return true;
6684 }
6685
6686 /// Attempt to vectorize the tree found by
6687 /// matchAssociativeReduction.
tryToReduce(BoUpSLP & V,TargetTransformInfo * TTI)6688 bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) {
6689 if (ReducedVals.empty())
6690 return false;
6691
6692 // If there is a sufficient number of reduction values, reduce
6693 // to a nearby power-of-2. Can safely generate oversized
6694 // vectors and rely on the backend to split them to legal sizes.
6695 unsigned NumReducedVals = ReducedVals.size();
6696 if (NumReducedVals < 4)
6697 return false;
6698
6699 unsigned ReduxWidth = PowerOf2Floor(NumReducedVals);
6700
6701 Value *VectorizedTree = nullptr;
6702
6703 // FIXME: Fast-math-flags should be set based on the instructions in the
6704 // reduction (not all of 'fast' are required).
6705 IRBuilder<> Builder(cast<Instruction>(ReductionRoot));
6706 FastMathFlags Unsafe;
6707 Unsafe.setFast();
6708 Builder.setFastMathFlags(Unsafe);
6709 unsigned i = 0;
6710
6711 BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues;
6712 // The same extra argument may be used several time, so log each attempt
6713 // to use it.
6714 for (auto &Pair : ExtraArgs) {
6715 assert(Pair.first && "DebugLoc must be set.");
6716 ExternallyUsedValues[Pair.second].push_back(Pair.first);
6717 }
6718
6719 // The compare instruction of a min/max is the insertion point for new
6720 // instructions and may be replaced with a new compare instruction.
6721 auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) {
6722 assert(isa<SelectInst>(RdxRootInst) &&
6723 "Expected min/max reduction to have select root instruction");
6724 Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition();
6725 assert(isa<Instruction>(ScalarCond) &&
6726 "Expected min/max reduction to have compare condition");
6727 return cast<Instruction>(ScalarCond);
6728 };
6729
6730 // The reduction root is used as the insertion point for new instructions,
6731 // so set it as externally used to prevent it from being deleted.
6732 ExternallyUsedValues[ReductionRoot];
6733 SmallVector<Value *, 16> IgnoreList;
6734 for (auto &V : ReductionOps)
6735 IgnoreList.append(V.begin(), V.end());
6736 while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) {
6737 auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth);
6738 V.buildTree(VL, ExternallyUsedValues, IgnoreList);
6739 Optional<ArrayRef<unsigned>> Order = V.bestOrder();
6740 // TODO: Handle orders of size less than number of elements in the vector.
6741 if (Order && Order->size() == VL.size()) {
6742 // TODO: reorder tree nodes without tree rebuilding.
6743 SmallVector<Value *, 4> ReorderedOps(VL.size());
6744 llvm::transform(*Order, ReorderedOps.begin(),
6745 [VL](const unsigned Idx) { return VL[Idx]; });
6746 V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList);
6747 }
6748 if (V.isTreeTinyAndNotFullyVectorizable())
6749 break;
6750 if (V.isLoadCombineReductionCandidate(ReductionData.getOpcode()))
6751 break;
6752
6753 V.computeMinimumValueSizes();
6754
6755 // Estimate cost.
6756 int TreeCost = V.getTreeCost();
6757 int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth);
6758 int Cost = TreeCost + ReductionCost;
6759 if (Cost >= -SLPCostThreshold) {
6760 V.getORE()->emit([&]() {
6761 return OptimizationRemarkMissed(
6762 SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0]))
6763 << "Vectorizing horizontal reduction is possible"
6764 << "but not beneficial with cost "
6765 << ore::NV("Cost", Cost) << " and threshold "
6766 << ore::NV("Threshold", -SLPCostThreshold);
6767 });
6768 break;
6769 }
6770
6771 LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:"
6772 << Cost << ". (HorRdx)\n");
6773 V.getORE()->emit([&]() {
6774 return OptimizationRemark(
6775 SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0]))
6776 << "Vectorized horizontal reduction with cost "
6777 << ore::NV("Cost", Cost) << " and with tree size "
6778 << ore::NV("TreeSize", V.getTreeSize());
6779 });
6780
6781 // Vectorize a tree.
6782 DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc();
6783 Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues);
6784
6785 // Emit a reduction. For min/max, the root is a select, but the insertion
6786 // point is the compare condition of that select.
6787 Instruction *RdxRootInst = cast<Instruction>(ReductionRoot);
6788 if (ReductionData.isMinMax())
6789 Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst));
6790 else
6791 Builder.SetInsertPoint(RdxRootInst);
6792
6793 Value *ReducedSubTree =
6794 emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI);
6795 if (VectorizedTree) {
6796 Builder.SetCurrentDebugLocation(Loc);
6797 OperationData VectReductionData(ReductionData.getOpcode(),
6798 VectorizedTree, ReducedSubTree,
6799 ReductionData.getKind());
6800 VectorizedTree =
6801 VectReductionData.createOp(Builder, "op.rdx", ReductionOps);
6802 } else
6803 VectorizedTree = ReducedSubTree;
6804 i += ReduxWidth;
6805 ReduxWidth = PowerOf2Floor(NumReducedVals - i);
6806 }
6807
6808 if (VectorizedTree) {
6809 // Finish the reduction.
6810 for (; i < NumReducedVals; ++i) {
6811 auto *I = cast<Instruction>(ReducedVals[i]);
6812 Builder.SetCurrentDebugLocation(I->getDebugLoc());
6813 OperationData VectReductionData(ReductionData.getOpcode(),
6814 VectorizedTree, I,
6815 ReductionData.getKind());
6816 VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps);
6817 }
6818 for (auto &Pair : ExternallyUsedValues) {
6819 // Add each externally used value to the final reduction.
6820 for (auto *I : Pair.second) {
6821 Builder.SetCurrentDebugLocation(I->getDebugLoc());
6822 OperationData VectReductionData(ReductionData.getOpcode(),
6823 VectorizedTree, Pair.first,
6824 ReductionData.getKind());
6825 VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I);
6826 }
6827 }
6828
6829 // Update users. For a min/max reduction that ends with a compare and
6830 // select, we also have to RAUW for the compare instruction feeding the
6831 // reduction root. That's because the original compare may have extra uses
6832 // besides the final select of the reduction.
6833 if (ReductionData.isMinMax()) {
6834 if (auto *VecSelect = dyn_cast<SelectInst>(VectorizedTree)) {
6835 Instruction *ScalarCmp =
6836 getCmpForMinMaxReduction(cast<Instruction>(ReductionRoot));
6837 ScalarCmp->replaceAllUsesWith(VecSelect->getCondition());
6838 }
6839 }
6840 ReductionRoot->replaceAllUsesWith(VectorizedTree);
6841
6842 // Mark all scalar reduction ops for deletion, they are replaced by the
6843 // vector reductions.
6844 V.eraseInstructions(IgnoreList);
6845 }
6846 return VectorizedTree != nullptr;
6847 }
6848
numReductionValues() const6849 unsigned numReductionValues() const {
6850 return ReducedVals.size();
6851 }
6852
6853 private:
6854 /// Calculate the cost of a reduction.
getReductionCost(TargetTransformInfo * TTI,Value * FirstReducedVal,unsigned ReduxWidth)6855 int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal,
6856 unsigned ReduxWidth) {
6857 Type *ScalarTy = FirstReducedVal->getType();
6858 Type *VecTy = VectorType::get(ScalarTy, ReduxWidth);
6859
6860 int PairwiseRdxCost;
6861 int SplittingRdxCost;
6862 switch (ReductionData.getKind()) {
6863 case RK_Arithmetic:
6864 PairwiseRdxCost =
6865 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy,
6866 /*IsPairwiseForm=*/true);
6867 SplittingRdxCost =
6868 TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy,
6869 /*IsPairwiseForm=*/false);
6870 break;
6871 case RK_Min:
6872 case RK_Max:
6873 case RK_UMin:
6874 case RK_UMax: {
6875 Type *VecCondTy = CmpInst::makeCmpResultType(VecTy);
6876 bool IsUnsigned = ReductionData.getKind() == RK_UMin ||
6877 ReductionData.getKind() == RK_UMax;
6878 PairwiseRdxCost =
6879 TTI->getMinMaxReductionCost(VecTy, VecCondTy,
6880 /*IsPairwiseForm=*/true, IsUnsigned);
6881 SplittingRdxCost =
6882 TTI->getMinMaxReductionCost(VecTy, VecCondTy,
6883 /*IsPairwiseForm=*/false, IsUnsigned);
6884 break;
6885 }
6886 case RK_None:
6887 llvm_unreachable("Expected arithmetic or min/max reduction operation");
6888 }
6889
6890 IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost;
6891 int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost;
6892
6893 int ScalarReduxCost = 0;
6894 switch (ReductionData.getKind()) {
6895 case RK_Arithmetic:
6896 ScalarReduxCost =
6897 TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy);
6898 break;
6899 case RK_Min:
6900 case RK_Max:
6901 case RK_UMin:
6902 case RK_UMax:
6903 ScalarReduxCost =
6904 TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) +
6905 TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy,
6906 CmpInst::makeCmpResultType(ScalarTy));
6907 break;
6908 case RK_None:
6909 llvm_unreachable("Expected arithmetic or min/max reduction operation");
6910 }
6911 ScalarReduxCost *= (ReduxWidth - 1);
6912
6913 LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost
6914 << " for reduction that starts with " << *FirstReducedVal
6915 << " (It is a "
6916 << (IsPairwiseReduction ? "pairwise" : "splitting")
6917 << " reduction)\n");
6918
6919 return VecReduxCost - ScalarReduxCost;
6920 }
6921
6922 /// Emit a horizontal reduction of the vectorized value.
emitReduction(Value * VectorizedValue,IRBuilder<> & Builder,unsigned ReduxWidth,const TargetTransformInfo * TTI)6923 Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder,
6924 unsigned ReduxWidth, const TargetTransformInfo *TTI) {
6925 assert(VectorizedValue && "Need to have a vectorized tree node");
6926 assert(isPowerOf2_32(ReduxWidth) &&
6927 "We only handle power-of-two reductions for now");
6928
6929 if (!IsPairwiseReduction) {
6930 // FIXME: The builder should use an FMF guard. It should not be hard-coded
6931 // to 'fast'.
6932 assert(Builder.getFastMathFlags().isFast() && "Expected 'fast' FMF");
6933 return createSimpleTargetReduction(
6934 Builder, TTI, ReductionData.getOpcode(), VectorizedValue,
6935 ReductionData.getFlags(), ReductionOps.back());
6936 }
6937
6938 Value *TmpVec = VectorizedValue;
6939 for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) {
6940 Value *LeftMask =
6941 createRdxShuffleMask(ReduxWidth, i, true, true, Builder);
6942 Value *RightMask =
6943 createRdxShuffleMask(ReduxWidth, i, true, false, Builder);
6944
6945 Value *LeftShuf = Builder.CreateShuffleVector(
6946 TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l");
6947 Value *RightShuf = Builder.CreateShuffleVector(
6948 TmpVec, UndefValue::get(TmpVec->getType()), (RightMask),
6949 "rdx.shuf.r");
6950 OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf,
6951 RightShuf, ReductionData.getKind());
6952 TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps);
6953 }
6954
6955 // The result is in the first element of the vector.
6956 return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0));
6957 }
6958 };
6959
6960 } // end anonymous namespace
6961
6962 /// Recognize construction of vectors like
6963 /// %ra = insertelement <4 x float> undef, float %s0, i32 0
6964 /// %rb = insertelement <4 x float> %ra, float %s1, i32 1
6965 /// %rc = insertelement <4 x float> %rb, float %s2, i32 2
6966 /// %rd = insertelement <4 x float> %rc, float %s3, i32 3
6967 /// starting from the last insertelement or insertvalue instruction.
6968 ///
6969 /// Also recognize aggregates like {<2 x float>, <2 x float>},
6970 /// {{float, float}, {float, float}}, [2 x {float, float}] and so on.
6971 /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples.
6972 ///
6973 /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type.
6974 ///
6975 /// \return true if it matches.
findBuildAggregate(Value * LastInsertInst,TargetTransformInfo * TTI,SmallVectorImpl<Value * > & BuildVectorOpds,int & UserCost)6976 static bool findBuildAggregate(Value *LastInsertInst, TargetTransformInfo *TTI,
6977 SmallVectorImpl<Value *> &BuildVectorOpds,
6978 int &UserCost) {
6979 assert((isa<InsertElementInst>(LastInsertInst) ||
6980 isa<InsertValueInst>(LastInsertInst)) &&
6981 "Expected insertelement or insertvalue instruction!");
6982 UserCost = 0;
6983 do {
6984 Value *InsertedOperand;
6985 if (auto *IE = dyn_cast<InsertElementInst>(LastInsertInst)) {
6986 InsertedOperand = IE->getOperand(1);
6987 LastInsertInst = IE->getOperand(0);
6988 if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) {
6989 UserCost += TTI->getVectorInstrCost(Instruction::InsertElement,
6990 IE->getType(), CI->getZExtValue());
6991 }
6992 } else {
6993 auto *IV = cast<InsertValueInst>(LastInsertInst);
6994 InsertedOperand = IV->getInsertedValueOperand();
6995 LastInsertInst = IV->getAggregateOperand();
6996 }
6997 if (isa<InsertElementInst>(InsertedOperand) ||
6998 isa<InsertValueInst>(InsertedOperand)) {
6999 int TmpUserCost;
7000 SmallVector<Value *, 8> TmpBuildVectorOpds;
7001 if (!findBuildAggregate(InsertedOperand, TTI, TmpBuildVectorOpds,
7002 TmpUserCost))
7003 return false;
7004 BuildVectorOpds.append(TmpBuildVectorOpds.rbegin(),
7005 TmpBuildVectorOpds.rend());
7006 UserCost += TmpUserCost;
7007 } else {
7008 BuildVectorOpds.push_back(InsertedOperand);
7009 }
7010 if (isa<UndefValue>(LastInsertInst))
7011 break;
7012 if ((!isa<InsertValueInst>(LastInsertInst) &&
7013 !isa<InsertElementInst>(LastInsertInst)) ||
7014 !LastInsertInst->hasOneUse())
7015 return false;
7016 } while (true);
7017 std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end());
7018 return true;
7019 }
7020
PhiTypeSorterFunc(Value * V,Value * V2)7021 static bool PhiTypeSorterFunc(Value *V, Value *V2) {
7022 return V->getType() < V2->getType();
7023 }
7024
7025 /// Try and get a reduction value from a phi node.
7026 ///
7027 /// Given a phi node \p P in a block \p ParentBB, consider possible reductions
7028 /// if they come from either \p ParentBB or a containing loop latch.
7029 ///
7030 /// \returns A candidate reduction value if possible, or \code nullptr \endcode
7031 /// if not possible.
getReductionValue(const DominatorTree * DT,PHINode * P,BasicBlock * ParentBB,LoopInfo * LI)7032 static Value *getReductionValue(const DominatorTree *DT, PHINode *P,
7033 BasicBlock *ParentBB, LoopInfo *LI) {
7034 // There are situations where the reduction value is not dominated by the
7035 // reduction phi. Vectorizing such cases has been reported to cause
7036 // miscompiles. See PR25787.
7037 auto DominatedReduxValue = [&](Value *R) {
7038 return isa<Instruction>(R) &&
7039 DT->dominates(P->getParent(), cast<Instruction>(R)->getParent());
7040 };
7041
7042 Value *Rdx = nullptr;
7043
7044 // Return the incoming value if it comes from the same BB as the phi node.
7045 if (P->getIncomingBlock(0) == ParentBB) {
7046 Rdx = P->getIncomingValue(0);
7047 } else if (P->getIncomingBlock(1) == ParentBB) {
7048 Rdx = P->getIncomingValue(1);
7049 }
7050
7051 if (Rdx && DominatedReduxValue(Rdx))
7052 return Rdx;
7053
7054 // Otherwise, check whether we have a loop latch to look at.
7055 Loop *BBL = LI->getLoopFor(ParentBB);
7056 if (!BBL)
7057 return nullptr;
7058 BasicBlock *BBLatch = BBL->getLoopLatch();
7059 if (!BBLatch)
7060 return nullptr;
7061
7062 // There is a loop latch, return the incoming value if it comes from
7063 // that. This reduction pattern occasionally turns up.
7064 if (P->getIncomingBlock(0) == BBLatch) {
7065 Rdx = P->getIncomingValue(0);
7066 } else if (P->getIncomingBlock(1) == BBLatch) {
7067 Rdx = P->getIncomingValue(1);
7068 }
7069
7070 if (Rdx && DominatedReduxValue(Rdx))
7071 return Rdx;
7072
7073 return nullptr;
7074 }
7075
7076 /// Attempt to reduce a horizontal reduction.
7077 /// If it is legal to match a horizontal reduction feeding the phi node \a P
7078 /// with reduction operators \a Root (or one of its operands) in a basic block
7079 /// \a BB, then check if it can be done. If horizontal reduction is not found
7080 /// and root instruction is a binary operation, vectorization of the operands is
7081 /// attempted.
7082 /// \returns true if a horizontal reduction was matched and reduced or operands
7083 /// of one of the binary instruction were vectorized.
7084 /// \returns false if a horizontal reduction was not matched (or not possible)
7085 /// or no vectorization of any binary operation feeding \a Root instruction was
7086 /// performed.
tryToVectorizeHorReductionOrInstOperands(PHINode * P,Instruction * Root,BasicBlock * BB,BoUpSLP & R,TargetTransformInfo * TTI,const function_ref<bool (Instruction *,BoUpSLP &)> Vectorize)7087 static bool tryToVectorizeHorReductionOrInstOperands(
7088 PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R,
7089 TargetTransformInfo *TTI,
7090 const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) {
7091 if (!ShouldVectorizeHor)
7092 return false;
7093
7094 if (!Root)
7095 return false;
7096
7097 if (Root->getParent() != BB || isa<PHINode>(Root))
7098 return false;
7099 // Start analysis starting from Root instruction. If horizontal reduction is
7100 // found, try to vectorize it. If it is not a horizontal reduction or
7101 // vectorization is not possible or not effective, and currently analyzed
7102 // instruction is a binary operation, try to vectorize the operands, using
7103 // pre-order DFS traversal order. If the operands were not vectorized, repeat
7104 // the same procedure considering each operand as a possible root of the
7105 // horizontal reduction.
7106 // Interrupt the process if the Root instruction itself was vectorized or all
7107 // sub-trees not higher that RecursionMaxDepth were analyzed/vectorized.
7108 SmallVector<std::pair<Instruction *, unsigned>, 8> Stack(1, {Root, 0});
7109 SmallPtrSet<Value *, 8> VisitedInstrs;
7110 bool Res = false;
7111 while (!Stack.empty()) {
7112 Instruction *Inst;
7113 unsigned Level;
7114 std::tie(Inst, Level) = Stack.pop_back_val();
7115 auto *BI = dyn_cast<BinaryOperator>(Inst);
7116 auto *SI = dyn_cast<SelectInst>(Inst);
7117 if (BI || SI) {
7118 HorizontalReduction HorRdx;
7119 if (HorRdx.matchAssociativeReduction(P, Inst)) {
7120 if (HorRdx.tryToReduce(R, TTI)) {
7121 Res = true;
7122 // Set P to nullptr to avoid re-analysis of phi node in
7123 // matchAssociativeReduction function unless this is the root node.
7124 P = nullptr;
7125 continue;
7126 }
7127 }
7128 if (P && BI) {
7129 Inst = dyn_cast<Instruction>(BI->getOperand(0));
7130 if (Inst == P)
7131 Inst = dyn_cast<Instruction>(BI->getOperand(1));
7132 if (!Inst) {
7133 // Set P to nullptr to avoid re-analysis of phi node in
7134 // matchAssociativeReduction function unless this is the root node.
7135 P = nullptr;
7136 continue;
7137 }
7138 }
7139 }
7140 // Set P to nullptr to avoid re-analysis of phi node in
7141 // matchAssociativeReduction function unless this is the root node.
7142 P = nullptr;
7143 if (Vectorize(Inst, R)) {
7144 Res = true;
7145 continue;
7146 }
7147
7148 // Try to vectorize operands.
7149 // Continue analysis for the instruction from the same basic block only to
7150 // save compile time.
7151 if (++Level < RecursionMaxDepth)
7152 for (auto *Op : Inst->operand_values())
7153 if (VisitedInstrs.insert(Op).second)
7154 if (auto *I = dyn_cast<Instruction>(Op))
7155 if (!isa<PHINode>(I) && !R.isDeleted(I) && I->getParent() == BB)
7156 Stack.emplace_back(I, Level);
7157 }
7158 return Res;
7159 }
7160
vectorizeRootInstruction(PHINode * P,Value * V,BasicBlock * BB,BoUpSLP & R,TargetTransformInfo * TTI)7161 bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V,
7162 BasicBlock *BB, BoUpSLP &R,
7163 TargetTransformInfo *TTI) {
7164 if (!V)
7165 return false;
7166 auto *I = dyn_cast<Instruction>(V);
7167 if (!I)
7168 return false;
7169
7170 if (!isa<BinaryOperator>(I))
7171 P = nullptr;
7172 // Try to match and vectorize a horizontal reduction.
7173 auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool {
7174 return tryToVectorize(I, R);
7175 };
7176 return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI,
7177 ExtraVectorization);
7178 }
7179
vectorizeInsertValueInst(InsertValueInst * IVI,BasicBlock * BB,BoUpSLP & R)7180 bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI,
7181 BasicBlock *BB, BoUpSLP &R) {
7182 int UserCost = 0;
7183 const DataLayout &DL = BB->getModule()->getDataLayout();
7184 if (!R.canMapToVector(IVI->getType(), DL))
7185 return false;
7186
7187 SmallVector<Value *, 16> BuildVectorOpds;
7188 if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, UserCost))
7189 return false;
7190
7191 LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n");
7192 // Aggregate value is unlikely to be processed in vector register, we need to
7193 // extract scalars into scalar registers, so NeedExtraction is set true.
7194 return tryToVectorizeList(BuildVectorOpds, R, UserCost);
7195 }
7196
vectorizeInsertElementInst(InsertElementInst * IEI,BasicBlock * BB,BoUpSLP & R)7197 bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI,
7198 BasicBlock *BB, BoUpSLP &R) {
7199 int UserCost;
7200 SmallVector<Value *, 16> BuildVectorOpds;
7201 if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, UserCost) ||
7202 (llvm::all_of(BuildVectorOpds,
7203 [](Value *V) { return isa<ExtractElementInst>(V); }) &&
7204 isShuffle(BuildVectorOpds)))
7205 return false;
7206
7207 // Vectorize starting with the build vector operands ignoring the BuildVector
7208 // instructions for the purpose of scheduling and user extraction.
7209 return tryToVectorizeList(BuildVectorOpds, R, UserCost);
7210 }
7211
vectorizeCmpInst(CmpInst * CI,BasicBlock * BB,BoUpSLP & R)7212 bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB,
7213 BoUpSLP &R) {
7214 if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R))
7215 return true;
7216
7217 bool OpsChanged = false;
7218 for (int Idx = 0; Idx < 2; ++Idx) {
7219 OpsChanged |=
7220 vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI);
7221 }
7222 return OpsChanged;
7223 }
7224
vectorizeSimpleInstructions(SmallVectorImpl<Instruction * > & Instructions,BasicBlock * BB,BoUpSLP & R)7225 bool SLPVectorizerPass::vectorizeSimpleInstructions(
7226 SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R) {
7227 bool OpsChanged = false;
7228 for (auto *I : reverse(Instructions)) {
7229 if (R.isDeleted(I))
7230 continue;
7231 if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I))
7232 OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R);
7233 else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I))
7234 OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R);
7235 else if (auto *CI = dyn_cast<CmpInst>(I))
7236 OpsChanged |= vectorizeCmpInst(CI, BB, R);
7237 }
7238 Instructions.clear();
7239 return OpsChanged;
7240 }
7241
vectorizeChainsInBlock(BasicBlock * BB,BoUpSLP & R)7242 bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) {
7243 bool Changed = false;
7244 SmallVector<Value *, 4> Incoming;
7245 SmallPtrSet<Value *, 16> VisitedInstrs;
7246
7247 bool HaveVectorizedPhiNodes = true;
7248 while (HaveVectorizedPhiNodes) {
7249 HaveVectorizedPhiNodes = false;
7250
7251 // Collect the incoming values from the PHIs.
7252 Incoming.clear();
7253 for (Instruction &I : *BB) {
7254 PHINode *P = dyn_cast<PHINode>(&I);
7255 if (!P)
7256 break;
7257
7258 if (!VisitedInstrs.count(P) && !R.isDeleted(P))
7259 Incoming.push_back(P);
7260 }
7261
7262 // Sort by type.
7263 llvm::stable_sort(Incoming, PhiTypeSorterFunc);
7264
7265 // Try to vectorize elements base on their type.
7266 for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(),
7267 E = Incoming.end();
7268 IncIt != E;) {
7269
7270 // Look for the next elements with the same type.
7271 SmallVector<Value *, 4>::iterator SameTypeIt = IncIt;
7272 while (SameTypeIt != E &&
7273 (*SameTypeIt)->getType() == (*IncIt)->getType()) {
7274 VisitedInstrs.insert(*SameTypeIt);
7275 ++SameTypeIt;
7276 }
7277
7278 // Try to vectorize them.
7279 unsigned NumElts = (SameTypeIt - IncIt);
7280 LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs ("
7281 << NumElts << ")\n");
7282 // The order in which the phi nodes appear in the program does not matter.
7283 // So allow tryToVectorizeList to reorder them if it is beneficial. This
7284 // is done when there are exactly two elements since tryToVectorizeList
7285 // asserts that there are only two values when AllowReorder is true.
7286 bool AllowReorder = NumElts == 2;
7287 if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R,
7288 /*UserCost=*/0, AllowReorder)) {
7289 // Success start over because instructions might have been changed.
7290 HaveVectorizedPhiNodes = true;
7291 Changed = true;
7292 break;
7293 }
7294
7295 // Start over at the next instruction of a different type (or the end).
7296 IncIt = SameTypeIt;
7297 }
7298 }
7299
7300 VisitedInstrs.clear();
7301
7302 SmallVector<Instruction *, 8> PostProcessInstructions;
7303 SmallDenseSet<Instruction *, 4> KeyNodes;
7304 for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
7305 // Skip instructions marked for the deletion.
7306 if (R.isDeleted(&*it))
7307 continue;
7308 // We may go through BB multiple times so skip the one we have checked.
7309 if (!VisitedInstrs.insert(&*it).second) {
7310 if (it->use_empty() && KeyNodes.count(&*it) > 0 &&
7311 vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) {
7312 // We would like to start over since some instructions are deleted
7313 // and the iterator may become invalid value.
7314 Changed = true;
7315 it = BB->begin();
7316 e = BB->end();
7317 }
7318 continue;
7319 }
7320
7321 if (isa<DbgInfoIntrinsic>(it))
7322 continue;
7323
7324 // Try to vectorize reductions that use PHINodes.
7325 if (PHINode *P = dyn_cast<PHINode>(it)) {
7326 // Check that the PHI is a reduction PHI.
7327 if (P->getNumIncomingValues() != 2)
7328 return Changed;
7329
7330 // Try to match and vectorize a horizontal reduction.
7331 if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R,
7332 TTI)) {
7333 Changed = true;
7334 it = BB->begin();
7335 e = BB->end();
7336 continue;
7337 }
7338 continue;
7339 }
7340
7341 // Ran into an instruction without users, like terminator, or function call
7342 // with ignored return value, store. Ignore unused instructions (basing on
7343 // instruction type, except for CallInst and InvokeInst).
7344 if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) ||
7345 isa<InvokeInst>(it))) {
7346 KeyNodes.insert(&*it);
7347 bool OpsChanged = false;
7348 if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) {
7349 for (auto *V : it->operand_values()) {
7350 // Try to match and vectorize a horizontal reduction.
7351 OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI);
7352 }
7353 }
7354 // Start vectorization of post-process list of instructions from the
7355 // top-tree instructions to try to vectorize as many instructions as
7356 // possible.
7357 OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R);
7358 if (OpsChanged) {
7359 // We would like to start over since some instructions are deleted
7360 // and the iterator may become invalid value.
7361 Changed = true;
7362 it = BB->begin();
7363 e = BB->end();
7364 continue;
7365 }
7366 }
7367
7368 if (isa<InsertElementInst>(it) || isa<CmpInst>(it) ||
7369 isa<InsertValueInst>(it))
7370 PostProcessInstructions.push_back(&*it);
7371 }
7372
7373 return Changed;
7374 }
7375
vectorizeGEPIndices(BasicBlock * BB,BoUpSLP & R)7376 bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) {
7377 auto Changed = false;
7378 for (auto &Entry : GEPs) {
7379 // If the getelementptr list has fewer than two elements, there's nothing
7380 // to do.
7381 if (Entry.second.size() < 2)
7382 continue;
7383
7384 LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length "
7385 << Entry.second.size() << ".\n");
7386
7387 // Process the GEP list in chunks suitable for the target's supported
7388 // vector size. If a vector register can't hold 1 element, we are done.
7389 unsigned MaxVecRegSize = R.getMaxVecRegSize();
7390 unsigned EltSize = R.getVectorElementSize(Entry.second[0]);
7391 if (MaxVecRegSize < EltSize)
7392 continue;
7393
7394 unsigned MaxElts = MaxVecRegSize / EltSize;
7395 for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) {
7396 auto Len = std::min<unsigned>(BE - BI, MaxElts);
7397 auto GEPList = makeArrayRef(&Entry.second[BI], Len);
7398
7399 // Initialize a set a candidate getelementptrs. Note that we use a
7400 // SetVector here to preserve program order. If the index computations
7401 // are vectorizable and begin with loads, we want to minimize the chance
7402 // of having to reorder them later.
7403 SetVector<Value *> Candidates(GEPList.begin(), GEPList.end());
7404
7405 // Some of the candidates may have already been vectorized after we
7406 // initially collected them. If so, they are marked as deleted, so remove
7407 // them from the set of candidates.
7408 Candidates.remove_if(
7409 [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); });
7410
7411 // Remove from the set of candidates all pairs of getelementptrs with
7412 // constant differences. Such getelementptrs are likely not good
7413 // candidates for vectorization in a bottom-up phase since one can be
7414 // computed from the other. We also ensure all candidate getelementptr
7415 // indices are unique.
7416 for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) {
7417 auto *GEPI = GEPList[I];
7418 if (!Candidates.count(GEPI))
7419 continue;
7420 auto *SCEVI = SE->getSCEV(GEPList[I]);
7421 for (int J = I + 1; J < E && Candidates.size() > 1; ++J) {
7422 auto *GEPJ = GEPList[J];
7423 auto *SCEVJ = SE->getSCEV(GEPList[J]);
7424 if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) {
7425 Candidates.remove(GEPI);
7426 Candidates.remove(GEPJ);
7427 } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) {
7428 Candidates.remove(GEPJ);
7429 }
7430 }
7431 }
7432
7433 // We break out of the above computation as soon as we know there are
7434 // fewer than two candidates remaining.
7435 if (Candidates.size() < 2)
7436 continue;
7437
7438 // Add the single, non-constant index of each candidate to the bundle. We
7439 // ensured the indices met these constraints when we originally collected
7440 // the getelementptrs.
7441 SmallVector<Value *, 16> Bundle(Candidates.size());
7442 auto BundleIndex = 0u;
7443 for (auto *V : Candidates) {
7444 auto *GEP = cast<GetElementPtrInst>(V);
7445 auto *GEPIdx = GEP->idx_begin()->get();
7446 assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx));
7447 Bundle[BundleIndex++] = GEPIdx;
7448 }
7449
7450 // Try and vectorize the indices. We are currently only interested in
7451 // gather-like cases of the form:
7452 //
7453 // ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ...
7454 //
7455 // where the loads of "a", the loads of "b", and the subtractions can be
7456 // performed in parallel. It's likely that detecting this pattern in a
7457 // bottom-up phase will be simpler and less costly than building a
7458 // full-blown top-down phase beginning at the consecutive loads.
7459 Changed |= tryToVectorizeList(Bundle, R);
7460 }
7461 }
7462 return Changed;
7463 }
7464
vectorizeStoreChains(BoUpSLP & R)7465 bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) {
7466 bool Changed = false;
7467 // Attempt to sort and vectorize each of the store-groups.
7468 for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e;
7469 ++it) {
7470 if (it->second.size() < 2)
7471 continue;
7472
7473 LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length "
7474 << it->second.size() << ".\n");
7475
7476 Changed |= vectorizeStores(it->second, R);
7477 }
7478 return Changed;
7479 }
7480
7481 char SLPVectorizer::ID = 0;
7482
7483 static const char lv_name[] = "SLP Vectorizer";
7484
INITIALIZE_PASS_BEGIN(SLPVectorizer,SV_NAME,lv_name,false,false)7485 INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false)
7486 INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass)
7487 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
7488 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
7489 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass)
7490 INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
7491 INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass)
7492 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass)
7493 INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false)
7494
7495 Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); }
7496