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1 //===- SampleProfile.cpp - Incorporate sample profiles into the IR --------===//
2 //
3 //                      The LLVM Compiler Infrastructure
4 //
5 // This file is distributed under the University of Illinois Open Source
6 // License. See LICENSE.TXT for details.
7 //
8 //===----------------------------------------------------------------------===//
9 //
10 // This file implements the SampleProfileLoader transformation. This pass
11 // reads a profile file generated by a sampling profiler (e.g. Linux Perf -
12 // http://perf.wiki.kernel.org/) and generates IR metadata to reflect the
13 // profile information in the given profile.
14 //
15 // This pass generates branch weight annotations on the IR:
16 //
17 // - prof: Represents branch weights. This annotation is added to branches
18 //      to indicate the weights of each edge coming out of the branch.
19 //      The weight of each edge is the weight of the target block for
20 //      that edge. The weight of a block B is computed as the maximum
21 //      number of samples found in B.
22 //
23 //===----------------------------------------------------------------------===//
24 
25 #include "llvm/Transforms/SampleProfile.h"
26 #include "llvm/ADT/DenseMap.h"
27 #include "llvm/ADT/SmallPtrSet.h"
28 #include "llvm/ADT/SmallSet.h"
29 #include "llvm/ADT/StringRef.h"
30 #include "llvm/Analysis/AssumptionCache.h"
31 #include "llvm/Analysis/LoopInfo.h"
32 #include "llvm/Analysis/PostDominators.h"
33 #include "llvm/IR/Constants.h"
34 #include "llvm/IR/DebugInfo.h"
35 #include "llvm/IR/DiagnosticInfo.h"
36 #include "llvm/IR/Dominators.h"
37 #include "llvm/IR/Function.h"
38 #include "llvm/IR/InstIterator.h"
39 #include "llvm/IR/Instructions.h"
40 #include "llvm/IR/IntrinsicInst.h"
41 #include "llvm/IR/LLVMContext.h"
42 #include "llvm/IR/MDBuilder.h"
43 #include "llvm/IR/Metadata.h"
44 #include "llvm/IR/Module.h"
45 #include "llvm/Pass.h"
46 #include "llvm/ProfileData/SampleProfReader.h"
47 #include "llvm/Support/CommandLine.h"
48 #include "llvm/Support/Debug.h"
49 #include "llvm/Support/ErrorOr.h"
50 #include "llvm/Support/Format.h"
51 #include "llvm/Support/raw_ostream.h"
52 #include "llvm/Transforms/IPO.h"
53 #include "llvm/Transforms/Utils/Cloning.h"
54 #include <cctype>
55 
56 using namespace llvm;
57 using namespace sampleprof;
58 
59 #define DEBUG_TYPE "sample-profile"
60 
61 // Command line option to specify the file to read samples from. This is
62 // mainly used for debugging.
63 static cl::opt<std::string> SampleProfileFile(
64     "sample-profile-file", cl::init(""), cl::value_desc("filename"),
65     cl::desc("Profile file loaded by -sample-profile"), cl::Hidden);
66 static cl::opt<unsigned> SampleProfileMaxPropagateIterations(
67     "sample-profile-max-propagate-iterations", cl::init(100),
68     cl::desc("Maximum number of iterations to go through when propagating "
69              "sample block/edge weights through the CFG."));
70 static cl::opt<unsigned> SampleProfileRecordCoverage(
71     "sample-profile-check-record-coverage", cl::init(0), cl::value_desc("N"),
72     cl::desc("Emit a warning if less than N% of records in the input profile "
73              "are matched to the IR."));
74 static cl::opt<unsigned> SampleProfileSampleCoverage(
75     "sample-profile-check-sample-coverage", cl::init(0), cl::value_desc("N"),
76     cl::desc("Emit a warning if less than N% of samples in the input profile "
77              "are matched to the IR."));
78 static cl::opt<double> SampleProfileHotThreshold(
79     "sample-profile-inline-hot-threshold", cl::init(0.1), cl::value_desc("N"),
80     cl::desc("Inlined functions that account for more than N% of all samples "
81              "collected in the parent function, will be inlined again."));
82 
83 namespace {
84 typedef DenseMap<const BasicBlock *, uint64_t> BlockWeightMap;
85 typedef DenseMap<const BasicBlock *, const BasicBlock *> EquivalenceClassMap;
86 typedef std::pair<const BasicBlock *, const BasicBlock *> Edge;
87 typedef DenseMap<Edge, uint64_t> EdgeWeightMap;
88 typedef DenseMap<const BasicBlock *, SmallVector<const BasicBlock *, 8>>
89     BlockEdgeMap;
90 
91 /// \brief Sample profile pass.
92 ///
93 /// This pass reads profile data from the file specified by
94 /// -sample-profile-file and annotates every affected function with the
95 /// profile information found in that file.
96 class SampleProfileLoader {
97 public:
SampleProfileLoader(StringRef Name=SampleProfileFile)98   SampleProfileLoader(StringRef Name = SampleProfileFile)
99       : DT(nullptr), PDT(nullptr), LI(nullptr), ACT(nullptr), Reader(),
100         Samples(nullptr), Filename(Name), ProfileIsValid(false),
101         TotalCollectedSamples(0) {}
102 
103   bool doInitialization(Module &M);
104   bool runOnModule(Module &M);
setACT(AssumptionCacheTracker * A)105   void setACT(AssumptionCacheTracker *A) { ACT = A; }
106 
dump()107   void dump() { Reader->dump(); }
108 
109 protected:
110   bool runOnFunction(Function &F);
111   unsigned getFunctionLoc(Function &F);
112   bool emitAnnotations(Function &F);
113   ErrorOr<uint64_t> getInstWeight(const Instruction &I) const;
114   ErrorOr<uint64_t> getBlockWeight(const BasicBlock *BB) const;
115   const FunctionSamples *findCalleeFunctionSamples(const CallInst &I) const;
116   const FunctionSamples *findFunctionSamples(const Instruction &I) const;
117   bool inlineHotFunctions(Function &F);
118   void printEdgeWeight(raw_ostream &OS, Edge E);
119   void printBlockWeight(raw_ostream &OS, const BasicBlock *BB) const;
120   void printBlockEquivalence(raw_ostream &OS, const BasicBlock *BB);
121   bool computeBlockWeights(Function &F);
122   void findEquivalenceClasses(Function &F);
123   void findEquivalencesFor(BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
124                            DominatorTreeBase<BasicBlock> *DomTree);
125   void propagateWeights(Function &F);
126   uint64_t visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge);
127   void buildEdges(Function &F);
128   bool propagateThroughEdges(Function &F);
129   void computeDominanceAndLoopInfo(Function &F);
130   unsigned getOffset(unsigned L, unsigned H) const;
131   void clearFunctionData();
132 
133   /// \brief Map basic blocks to their computed weights.
134   ///
135   /// The weight of a basic block is defined to be the maximum
136   /// of all the instruction weights in that block.
137   BlockWeightMap BlockWeights;
138 
139   /// \brief Map edges to their computed weights.
140   ///
141   /// Edge weights are computed by propagating basic block weights in
142   /// SampleProfile::propagateWeights.
143   EdgeWeightMap EdgeWeights;
144 
145   /// \brief Set of visited blocks during propagation.
146   SmallPtrSet<const BasicBlock *, 32> VisitedBlocks;
147 
148   /// \brief Set of visited edges during propagation.
149   SmallSet<Edge, 32> VisitedEdges;
150 
151   /// \brief Equivalence classes for block weights.
152   ///
153   /// Two blocks BB1 and BB2 are in the same equivalence class if they
154   /// dominate and post-dominate each other, and they are in the same loop
155   /// nest. When this happens, the two blocks are guaranteed to execute
156   /// the same number of times.
157   EquivalenceClassMap EquivalenceClass;
158 
159   /// \brief Dominance, post-dominance and loop information.
160   std::unique_ptr<DominatorTree> DT;
161   std::unique_ptr<DominatorTreeBase<BasicBlock>> PDT;
162   std::unique_ptr<LoopInfo> LI;
163 
164   AssumptionCacheTracker *ACT;
165 
166   /// \brief Predecessors for each basic block in the CFG.
167   BlockEdgeMap Predecessors;
168 
169   /// \brief Successors for each basic block in the CFG.
170   BlockEdgeMap Successors;
171 
172   /// \brief Profile reader object.
173   std::unique_ptr<SampleProfileReader> Reader;
174 
175   /// \brief Samples collected for the body of this function.
176   FunctionSamples *Samples;
177 
178   /// \brief Name of the profile file to load.
179   StringRef Filename;
180 
181   /// \brief Flag indicating whether the profile input loaded successfully.
182   bool ProfileIsValid;
183 
184   /// \brief Total number of samples collected in this profile.
185   ///
186   /// This is the sum of all the samples collected in all the functions executed
187   /// at runtime.
188   uint64_t TotalCollectedSamples;
189 };
190 
191 class SampleProfileLoaderLegacyPass : public ModulePass {
192 public:
193   // Class identification, replacement for typeinfo
194   static char ID;
195 
SampleProfileLoaderLegacyPass(StringRef Name=SampleProfileFile)196   SampleProfileLoaderLegacyPass(StringRef Name = SampleProfileFile)
197       : ModulePass(ID), SampleLoader(Name) {
198     initializeSampleProfileLoaderLegacyPassPass(
199         *PassRegistry::getPassRegistry());
200   }
201 
dump()202   void dump() { SampleLoader.dump(); }
203 
doInitialization(Module & M)204   bool doInitialization(Module &M) override {
205     return SampleLoader.doInitialization(M);
206   }
getPassName() const207   const char *getPassName() const override { return "Sample profile pass"; }
208   bool runOnModule(Module &M) override;
209 
getAnalysisUsage(AnalysisUsage & AU) const210   void getAnalysisUsage(AnalysisUsage &AU) const override {
211     AU.addRequired<AssumptionCacheTracker>();
212   }
213 private:
214   SampleProfileLoader SampleLoader;
215 };
216 
217 class SampleCoverageTracker {
218 public:
SampleCoverageTracker()219   SampleCoverageTracker() : SampleCoverage(), TotalUsedSamples(0) {}
220 
221   bool markSamplesUsed(const FunctionSamples *FS, uint32_t LineOffset,
222                        uint32_t Discriminator, uint64_t Samples);
223   unsigned computeCoverage(unsigned Used, unsigned Total) const;
224   unsigned countUsedRecords(const FunctionSamples *FS) const;
225   unsigned countBodyRecords(const FunctionSamples *FS) const;
getTotalUsedSamples() const226   uint64_t getTotalUsedSamples() const { return TotalUsedSamples; }
227   uint64_t countBodySamples(const FunctionSamples *FS) const;
clear()228   void clear() {
229     SampleCoverage.clear();
230     TotalUsedSamples = 0;
231   }
232 
233 private:
234   typedef std::map<LineLocation, unsigned> BodySampleCoverageMap;
235   typedef DenseMap<const FunctionSamples *, BodySampleCoverageMap>
236       FunctionSamplesCoverageMap;
237 
238   /// Coverage map for sampling records.
239   ///
240   /// This map keeps a record of sampling records that have been matched to
241   /// an IR instruction. This is used to detect some form of staleness in
242   /// profiles (see flag -sample-profile-check-coverage).
243   ///
244   /// Each entry in the map corresponds to a FunctionSamples instance.  This is
245   /// another map that counts how many times the sample record at the
246   /// given location has been used.
247   FunctionSamplesCoverageMap SampleCoverage;
248 
249   /// Number of samples used from the profile.
250   ///
251   /// When a sampling record is used for the first time, the samples from
252   /// that record are added to this accumulator.  Coverage is later computed
253   /// based on the total number of samples available in this function and
254   /// its callsites.
255   ///
256   /// Note that this accumulator tracks samples used from a single function
257   /// and all the inlined callsites. Strictly, we should have a map of counters
258   /// keyed by FunctionSamples pointers, but these stats are cleared after
259   /// every function, so we just need to keep a single counter.
260   uint64_t TotalUsedSamples;
261 };
262 
263 SampleCoverageTracker CoverageTracker;
264 
265 /// Return true if the given callsite is hot wrt to its caller.
266 ///
267 /// Functions that were inlined in the original binary will be represented
268 /// in the inline stack in the sample profile. If the profile shows that
269 /// the original inline decision was "good" (i.e., the callsite is executed
270 /// frequently), then we will recreate the inline decision and apply the
271 /// profile from the inlined callsite.
272 ///
273 /// To decide whether an inlined callsite is hot, we compute the fraction
274 /// of samples used by the callsite with respect to the total number of samples
275 /// collected in the caller.
276 ///
277 /// If that fraction is larger than the default given by
278 /// SampleProfileHotThreshold, the callsite will be inlined again.
callsiteIsHot(const FunctionSamples * CallerFS,const FunctionSamples * CallsiteFS)279 bool callsiteIsHot(const FunctionSamples *CallerFS,
280                    const FunctionSamples *CallsiteFS) {
281   if (!CallsiteFS)
282     return false; // The callsite was not inlined in the original binary.
283 
284   uint64_t ParentTotalSamples = CallerFS->getTotalSamples();
285   if (ParentTotalSamples == 0)
286     return false; // Avoid division by zero.
287 
288   uint64_t CallsiteTotalSamples = CallsiteFS->getTotalSamples();
289   if (CallsiteTotalSamples == 0)
290     return false; // Callsite is trivially cold.
291 
292   double PercentSamples =
293       (double)CallsiteTotalSamples / (double)ParentTotalSamples * 100.0;
294   return PercentSamples >= SampleProfileHotThreshold;
295 }
296 }
297 
298 /// Mark as used the sample record for the given function samples at
299 /// (LineOffset, Discriminator).
300 ///
301 /// \returns true if this is the first time we mark the given record.
markSamplesUsed(const FunctionSamples * FS,uint32_t LineOffset,uint32_t Discriminator,uint64_t Samples)302 bool SampleCoverageTracker::markSamplesUsed(const FunctionSamples *FS,
303                                             uint32_t LineOffset,
304                                             uint32_t Discriminator,
305                                             uint64_t Samples) {
306   LineLocation Loc(LineOffset, Discriminator);
307   unsigned &Count = SampleCoverage[FS][Loc];
308   bool FirstTime = (++Count == 1);
309   if (FirstTime)
310     TotalUsedSamples += Samples;
311   return FirstTime;
312 }
313 
314 /// Return the number of sample records that were applied from this profile.
315 ///
316 /// This count does not include records from cold inlined callsites.
317 unsigned
countUsedRecords(const FunctionSamples * FS) const318 SampleCoverageTracker::countUsedRecords(const FunctionSamples *FS) const {
319   auto I = SampleCoverage.find(FS);
320 
321   // The size of the coverage map for FS represents the number of records
322   // that were marked used at least once.
323   unsigned Count = (I != SampleCoverage.end()) ? I->second.size() : 0;
324 
325   // If there are inlined callsites in this function, count the samples found
326   // in the respective bodies. However, do not bother counting callees with 0
327   // total samples, these are callees that were never invoked at runtime.
328   for (const auto &I : FS->getCallsiteSamples()) {
329     const FunctionSamples *CalleeSamples = &I.second;
330     if (callsiteIsHot(FS, CalleeSamples))
331       Count += countUsedRecords(CalleeSamples);
332   }
333 
334   return Count;
335 }
336 
337 /// Return the number of sample records in the body of this profile.
338 ///
339 /// This count does not include records from cold inlined callsites.
340 unsigned
countBodyRecords(const FunctionSamples * FS) const341 SampleCoverageTracker::countBodyRecords(const FunctionSamples *FS) const {
342   unsigned Count = FS->getBodySamples().size();
343 
344   // Only count records in hot callsites.
345   for (const auto &I : FS->getCallsiteSamples()) {
346     const FunctionSamples *CalleeSamples = &I.second;
347     if (callsiteIsHot(FS, CalleeSamples))
348       Count += countBodyRecords(CalleeSamples);
349   }
350 
351   return Count;
352 }
353 
354 /// Return the number of samples collected in the body of this profile.
355 ///
356 /// This count does not include samples from cold inlined callsites.
357 uint64_t
countBodySamples(const FunctionSamples * FS) const358 SampleCoverageTracker::countBodySamples(const FunctionSamples *FS) const {
359   uint64_t Total = 0;
360   for (const auto &I : FS->getBodySamples())
361     Total += I.second.getSamples();
362 
363   // Only count samples in hot callsites.
364   for (const auto &I : FS->getCallsiteSamples()) {
365     const FunctionSamples *CalleeSamples = &I.second;
366     if (callsiteIsHot(FS, CalleeSamples))
367       Total += countBodySamples(CalleeSamples);
368   }
369 
370   return Total;
371 }
372 
373 /// Return the fraction of sample records used in this profile.
374 ///
375 /// The returned value is an unsigned integer in the range 0-100 indicating
376 /// the percentage of sample records that were used while applying this
377 /// profile to the associated function.
computeCoverage(unsigned Used,unsigned Total) const378 unsigned SampleCoverageTracker::computeCoverage(unsigned Used,
379                                                 unsigned Total) const {
380   assert(Used <= Total &&
381          "number of used records cannot exceed the total number of records");
382   return Total > 0 ? Used * 100 / Total : 100;
383 }
384 
385 /// Clear all the per-function data used to load samples and propagate weights.
clearFunctionData()386 void SampleProfileLoader::clearFunctionData() {
387   BlockWeights.clear();
388   EdgeWeights.clear();
389   VisitedBlocks.clear();
390   VisitedEdges.clear();
391   EquivalenceClass.clear();
392   DT = nullptr;
393   PDT = nullptr;
394   LI = nullptr;
395   Predecessors.clear();
396   Successors.clear();
397   CoverageTracker.clear();
398 }
399 
400 /// \brief Returns the offset of lineno \p L to head_lineno \p H
401 ///
402 /// \param L  Lineno
403 /// \param H  Header lineno of the function
404 ///
405 /// \returns offset to the header lineno. 16 bits are used to represent offset.
406 /// We assume that a single function will not exceed 65535 LOC.
getOffset(unsigned L,unsigned H) const407 unsigned SampleProfileLoader::getOffset(unsigned L, unsigned H) const {
408   return (L - H) & 0xffff;
409 }
410 
411 /// \brief Print the weight of edge \p E on stream \p OS.
412 ///
413 /// \param OS  Stream to emit the output to.
414 /// \param E  Edge to print.
printEdgeWeight(raw_ostream & OS,Edge E)415 void SampleProfileLoader::printEdgeWeight(raw_ostream &OS, Edge E) {
416   OS << "weight[" << E.first->getName() << "->" << E.second->getName()
417      << "]: " << EdgeWeights[E] << "\n";
418 }
419 
420 /// \brief Print the equivalence class of block \p BB on stream \p OS.
421 ///
422 /// \param OS  Stream to emit the output to.
423 /// \param BB  Block to print.
printBlockEquivalence(raw_ostream & OS,const BasicBlock * BB)424 void SampleProfileLoader::printBlockEquivalence(raw_ostream &OS,
425                                                 const BasicBlock *BB) {
426   const BasicBlock *Equiv = EquivalenceClass[BB];
427   OS << "equivalence[" << BB->getName()
428      << "]: " << ((Equiv) ? EquivalenceClass[BB]->getName() : "NONE") << "\n";
429 }
430 
431 /// \brief Print the weight of block \p BB on stream \p OS.
432 ///
433 /// \param OS  Stream to emit the output to.
434 /// \param BB  Block to print.
printBlockWeight(raw_ostream & OS,const BasicBlock * BB) const435 void SampleProfileLoader::printBlockWeight(raw_ostream &OS,
436                                            const BasicBlock *BB) const {
437   const auto &I = BlockWeights.find(BB);
438   uint64_t W = (I == BlockWeights.end() ? 0 : I->second);
439   OS << "weight[" << BB->getName() << "]: " << W << "\n";
440 }
441 
442 /// \brief Get the weight for an instruction.
443 ///
444 /// The "weight" of an instruction \p Inst is the number of samples
445 /// collected on that instruction at runtime. To retrieve it, we
446 /// need to compute the line number of \p Inst relative to the start of its
447 /// function. We use HeaderLineno to compute the offset. We then
448 /// look up the samples collected for \p Inst using BodySamples.
449 ///
450 /// \param Inst Instruction to query.
451 ///
452 /// \returns the weight of \p Inst.
453 ErrorOr<uint64_t>
getInstWeight(const Instruction & Inst) const454 SampleProfileLoader::getInstWeight(const Instruction &Inst) const {
455   const DebugLoc &DLoc = Inst.getDebugLoc();
456   if (!DLoc)
457     return std::error_code();
458 
459   const FunctionSamples *FS = findFunctionSamples(Inst);
460   if (!FS)
461     return std::error_code();
462 
463   // Ignore all dbg_value intrinsics.
464   const IntrinsicInst *II = dyn_cast<IntrinsicInst>(&Inst);
465   if (II && II->getIntrinsicID() == Intrinsic::dbg_value)
466     return std::error_code();
467 
468   const DILocation *DIL = DLoc;
469   unsigned Lineno = DLoc.getLine();
470   unsigned HeaderLineno = DIL->getScope()->getSubprogram()->getLine();
471 
472   uint32_t LineOffset = getOffset(Lineno, HeaderLineno);
473   uint32_t Discriminator = DIL->getDiscriminator();
474   ErrorOr<uint64_t> R = FS->findSamplesAt(LineOffset, Discriminator);
475   if (R) {
476     bool FirstMark =
477         CoverageTracker.markSamplesUsed(FS, LineOffset, Discriminator, R.get());
478     if (FirstMark) {
479       const Function *F = Inst.getParent()->getParent();
480       LLVMContext &Ctx = F->getContext();
481       emitOptimizationRemark(
482           Ctx, DEBUG_TYPE, *F, DLoc,
483           Twine("Applied ") + Twine(*R) + " samples from profile (offset: " +
484               Twine(LineOffset) +
485               ((Discriminator) ? Twine(".") + Twine(Discriminator) : "") + ")");
486     }
487     DEBUG(dbgs() << "    " << Lineno << "." << DIL->getDiscriminator() << ":"
488                  << Inst << " (line offset: " << Lineno - HeaderLineno << "."
489                  << DIL->getDiscriminator() << " - weight: " << R.get()
490                  << ")\n");
491   } else {
492     // If a call instruction is inlined in profile, but not inlined here,
493     // it means that the inlined callsite has no sample, thus the call
494     // instruction should have 0 count.
495     const CallInst *CI = dyn_cast<CallInst>(&Inst);
496     if (CI && findCalleeFunctionSamples(*CI))
497       R = 0;
498   }
499   return R;
500 }
501 
502 /// \brief Compute the weight of a basic block.
503 ///
504 /// The weight of basic block \p BB is the maximum weight of all the
505 /// instructions in BB.
506 ///
507 /// \param BB The basic block to query.
508 ///
509 /// \returns the weight for \p BB.
510 ErrorOr<uint64_t>
getBlockWeight(const BasicBlock * BB) const511 SampleProfileLoader::getBlockWeight(const BasicBlock *BB) const {
512   DenseMap<uint64_t, uint64_t> CM;
513   for (auto &I : BB->getInstList()) {
514     const ErrorOr<uint64_t> &R = getInstWeight(I);
515     if (R) CM[R.get()]++;
516   }
517   if (CM.size() == 0) return std::error_code();
518   uint64_t W = 0, C = 0;
519   for (const auto &C_W : CM) {
520     if (C_W.second == W) {
521       C = std::max(C, C_W.first);
522     } else if (C_W.second > W) {
523       C = C_W.first;
524       W = C_W.second;
525     }
526   }
527   return C;
528 }
529 
530 /// \brief Compute and store the weights of every basic block.
531 ///
532 /// This populates the BlockWeights map by computing
533 /// the weights of every basic block in the CFG.
534 ///
535 /// \param F The function to query.
computeBlockWeights(Function & F)536 bool SampleProfileLoader::computeBlockWeights(Function &F) {
537   bool Changed = false;
538   DEBUG(dbgs() << "Block weights\n");
539   for (const auto &BB : F) {
540     ErrorOr<uint64_t> Weight = getBlockWeight(&BB);
541     if (Weight) {
542       BlockWeights[&BB] = Weight.get();
543       VisitedBlocks.insert(&BB);
544       Changed = true;
545     }
546     DEBUG(printBlockWeight(dbgs(), &BB));
547   }
548 
549   return Changed;
550 }
551 
552 /// \brief Get the FunctionSamples for a call instruction.
553 ///
554 /// The FunctionSamples of a call instruction \p Inst is the inlined
555 /// instance in which that call instruction is calling to. It contains
556 /// all samples that resides in the inlined instance. We first find the
557 /// inlined instance in which the call instruction is from, then we
558 /// traverse its children to find the callsite with the matching
559 /// location and callee function name.
560 ///
561 /// \param Inst Call instruction to query.
562 ///
563 /// \returns The FunctionSamples pointer to the inlined instance.
564 const FunctionSamples *
findCalleeFunctionSamples(const CallInst & Inst) const565 SampleProfileLoader::findCalleeFunctionSamples(const CallInst &Inst) const {
566   const DILocation *DIL = Inst.getDebugLoc();
567   if (!DIL) {
568     return nullptr;
569   }
570   DISubprogram *SP = DIL->getScope()->getSubprogram();
571   if (!SP)
572     return nullptr;
573 
574   const FunctionSamples *FS = findFunctionSamples(Inst);
575   if (FS == nullptr)
576     return nullptr;
577 
578   return FS->findFunctionSamplesAt(LineLocation(
579       getOffset(DIL->getLine(), SP->getLine()), DIL->getDiscriminator()));
580 }
581 
582 /// \brief Get the FunctionSamples for an instruction.
583 ///
584 /// The FunctionSamples of an instruction \p Inst is the inlined instance
585 /// in which that instruction is coming from. We traverse the inline stack
586 /// of that instruction, and match it with the tree nodes in the profile.
587 ///
588 /// \param Inst Instruction to query.
589 ///
590 /// \returns the FunctionSamples pointer to the inlined instance.
591 const FunctionSamples *
findFunctionSamples(const Instruction & Inst) const592 SampleProfileLoader::findFunctionSamples(const Instruction &Inst) const {
593   SmallVector<LineLocation, 10> S;
594   const DILocation *DIL = Inst.getDebugLoc();
595   if (!DIL) {
596     return Samples;
597   }
598   for (DIL = DIL->getInlinedAt(); DIL; DIL = DIL->getInlinedAt()) {
599     DISubprogram *SP = DIL->getScope()->getSubprogram();
600     if (!SP)
601       return nullptr;
602     S.push_back(LineLocation(getOffset(DIL->getLine(), SP->getLine()),
603                              DIL->getDiscriminator()));
604   }
605   if (S.size() == 0)
606     return Samples;
607   const FunctionSamples *FS = Samples;
608   for (int i = S.size() - 1; i >= 0 && FS != nullptr; i--) {
609     FS = FS->findFunctionSamplesAt(S[i]);
610   }
611   return FS;
612 }
613 
614 
615 /// \brief Iteratively inline hot callsites of a function.
616 ///
617 /// Iteratively traverse all callsites of the function \p F, and find if
618 /// the corresponding inlined instance exists and is hot in profile. If
619 /// it is hot enough, inline the callsites and adds new callsites of the
620 /// callee into the caller.
621 ///
622 /// TODO: investigate the possibility of not invoking InlineFunction directly.
623 ///
624 /// \param F function to perform iterative inlining.
625 ///
626 /// \returns True if there is any inline happened.
inlineHotFunctions(Function & F)627 bool SampleProfileLoader::inlineHotFunctions(Function &F) {
628   bool Changed = false;
629   LLVMContext &Ctx = F.getContext();
630   while (true) {
631     bool LocalChanged = false;
632     SmallVector<CallInst *, 10> CIS;
633     for (auto &BB : F) {
634       for (auto &I : BB.getInstList()) {
635         CallInst *CI = dyn_cast<CallInst>(&I);
636         if (CI && callsiteIsHot(Samples, findCalleeFunctionSamples(*CI)))
637           CIS.push_back(CI);
638       }
639     }
640     for (auto CI : CIS) {
641       InlineFunctionInfo IFI(nullptr, ACT);
642       Function *CalledFunction = CI->getCalledFunction();
643       DebugLoc DLoc = CI->getDebugLoc();
644       uint64_t NumSamples = findCalleeFunctionSamples(*CI)->getTotalSamples();
645       if (InlineFunction(CI, IFI)) {
646         LocalChanged = true;
647         emitOptimizationRemark(Ctx, DEBUG_TYPE, F, DLoc,
648                                Twine("inlined hot callee '") +
649                                    CalledFunction->getName() + "' with " +
650                                    Twine(NumSamples) + " samples into '" +
651                                    F.getName() + "'");
652       }
653     }
654     if (LocalChanged) {
655       Changed = true;
656     } else {
657       break;
658     }
659   }
660   return Changed;
661 }
662 
663 /// \brief Find equivalence classes for the given block.
664 ///
665 /// This finds all the blocks that are guaranteed to execute the same
666 /// number of times as \p BB1. To do this, it traverses all the
667 /// descendants of \p BB1 in the dominator or post-dominator tree.
668 ///
669 /// A block BB2 will be in the same equivalence class as \p BB1 if
670 /// the following holds:
671 ///
672 /// 1- \p BB1 is a descendant of BB2 in the opposite tree. So, if BB2
673 ///    is a descendant of \p BB1 in the dominator tree, then BB2 should
674 ///    dominate BB1 in the post-dominator tree.
675 ///
676 /// 2- Both BB2 and \p BB1 must be in the same loop.
677 ///
678 /// For every block BB2 that meets those two requirements, we set BB2's
679 /// equivalence class to \p BB1.
680 ///
681 /// \param BB1  Block to check.
682 /// \param Descendants  Descendants of \p BB1 in either the dom or pdom tree.
683 /// \param DomTree  Opposite dominator tree. If \p Descendants is filled
684 ///                 with blocks from \p BB1's dominator tree, then
685 ///                 this is the post-dominator tree, and vice versa.
findEquivalencesFor(BasicBlock * BB1,ArrayRef<BasicBlock * > Descendants,DominatorTreeBase<BasicBlock> * DomTree)686 void SampleProfileLoader::findEquivalencesFor(
687     BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
688     DominatorTreeBase<BasicBlock> *DomTree) {
689   const BasicBlock *EC = EquivalenceClass[BB1];
690   uint64_t Weight = BlockWeights[EC];
691   for (const auto *BB2 : Descendants) {
692     bool IsDomParent = DomTree->dominates(BB2, BB1);
693     bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2);
694     if (BB1 != BB2 && IsDomParent && IsInSameLoop) {
695       EquivalenceClass[BB2] = EC;
696 
697       // If BB2 is heavier than BB1, make BB2 have the same weight
698       // as BB1.
699       //
700       // Note that we don't worry about the opposite situation here
701       // (when BB2 is lighter than BB1). We will deal with this
702       // during the propagation phase. Right now, we just want to
703       // make sure that BB1 has the largest weight of all the
704       // members of its equivalence set.
705       Weight = std::max(Weight, BlockWeights[BB2]);
706     }
707   }
708   BlockWeights[EC] = Weight;
709 }
710 
711 /// \brief Find equivalence classes.
712 ///
713 /// Since samples may be missing from blocks, we can fill in the gaps by setting
714 /// the weights of all the blocks in the same equivalence class to the same
715 /// weight. To compute the concept of equivalence, we use dominance and loop
716 /// information. Two blocks B1 and B2 are in the same equivalence class if B1
717 /// dominates B2, B2 post-dominates B1 and both are in the same loop.
718 ///
719 /// \param F The function to query.
findEquivalenceClasses(Function & F)720 void SampleProfileLoader::findEquivalenceClasses(Function &F) {
721   SmallVector<BasicBlock *, 8> DominatedBBs;
722   DEBUG(dbgs() << "\nBlock equivalence classes\n");
723   // Find equivalence sets based on dominance and post-dominance information.
724   for (auto &BB : F) {
725     BasicBlock *BB1 = &BB;
726 
727     // Compute BB1's equivalence class once.
728     if (EquivalenceClass.count(BB1)) {
729       DEBUG(printBlockEquivalence(dbgs(), BB1));
730       continue;
731     }
732 
733     // By default, blocks are in their own equivalence class.
734     EquivalenceClass[BB1] = BB1;
735 
736     // Traverse all the blocks dominated by BB1. We are looking for
737     // every basic block BB2 such that:
738     //
739     // 1- BB1 dominates BB2.
740     // 2- BB2 post-dominates BB1.
741     // 3- BB1 and BB2 are in the same loop nest.
742     //
743     // If all those conditions hold, it means that BB2 is executed
744     // as many times as BB1, so they are placed in the same equivalence
745     // class by making BB2's equivalence class be BB1.
746     DominatedBBs.clear();
747     DT->getDescendants(BB1, DominatedBBs);
748     findEquivalencesFor(BB1, DominatedBBs, PDT.get());
749 
750     DEBUG(printBlockEquivalence(dbgs(), BB1));
751   }
752 
753   // Assign weights to equivalence classes.
754   //
755   // All the basic blocks in the same equivalence class will execute
756   // the same number of times. Since we know that the head block in
757   // each equivalence class has the largest weight, assign that weight
758   // to all the blocks in that equivalence class.
759   DEBUG(dbgs() << "\nAssign the same weight to all blocks in the same class\n");
760   for (auto &BI : F) {
761     const BasicBlock *BB = &BI;
762     const BasicBlock *EquivBB = EquivalenceClass[BB];
763     if (BB != EquivBB)
764       BlockWeights[BB] = BlockWeights[EquivBB];
765     DEBUG(printBlockWeight(dbgs(), BB));
766   }
767 }
768 
769 /// \brief Visit the given edge to decide if it has a valid weight.
770 ///
771 /// If \p E has not been visited before, we copy to \p UnknownEdge
772 /// and increment the count of unknown edges.
773 ///
774 /// \param E  Edge to visit.
775 /// \param NumUnknownEdges  Current number of unknown edges.
776 /// \param UnknownEdge  Set if E has not been visited before.
777 ///
778 /// \returns E's weight, if known. Otherwise, return 0.
visitEdge(Edge E,unsigned * NumUnknownEdges,Edge * UnknownEdge)779 uint64_t SampleProfileLoader::visitEdge(Edge E, unsigned *NumUnknownEdges,
780                                         Edge *UnknownEdge) {
781   if (!VisitedEdges.count(E)) {
782     (*NumUnknownEdges)++;
783     *UnknownEdge = E;
784     return 0;
785   }
786 
787   return EdgeWeights[E];
788 }
789 
790 /// \brief Propagate weights through incoming/outgoing edges.
791 ///
792 /// If the weight of a basic block is known, and there is only one edge
793 /// with an unknown weight, we can calculate the weight of that edge.
794 ///
795 /// Similarly, if all the edges have a known count, we can calculate the
796 /// count of the basic block, if needed.
797 ///
798 /// \param F  Function to process.
799 ///
800 /// \returns  True if new weights were assigned to edges or blocks.
propagateThroughEdges(Function & F)801 bool SampleProfileLoader::propagateThroughEdges(Function &F) {
802   bool Changed = false;
803   DEBUG(dbgs() << "\nPropagation through edges\n");
804   for (const auto &BI : F) {
805     const BasicBlock *BB = &BI;
806     const BasicBlock *EC = EquivalenceClass[BB];
807 
808     // Visit all the predecessor and successor edges to determine
809     // which ones have a weight assigned already. Note that it doesn't
810     // matter that we only keep track of a single unknown edge. The
811     // only case we are interested in handling is when only a single
812     // edge is unknown (see setEdgeOrBlockWeight).
813     for (unsigned i = 0; i < 2; i++) {
814       uint64_t TotalWeight = 0;
815       unsigned NumUnknownEdges = 0, NumTotalEdges = 0;
816       Edge UnknownEdge, SelfReferentialEdge, SingleEdge;
817 
818       if (i == 0) {
819         // First, visit all predecessor edges.
820         NumTotalEdges = Predecessors[BB].size();
821         for (auto *Pred : Predecessors[BB]) {
822           Edge E = std::make_pair(Pred, BB);
823           TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
824           if (E.first == E.second)
825             SelfReferentialEdge = E;
826         }
827         if (NumTotalEdges == 1) {
828           SingleEdge = std::make_pair(Predecessors[BB][0], BB);
829         }
830       } else {
831         // On the second round, visit all successor edges.
832         NumTotalEdges = Successors[BB].size();
833         for (auto *Succ : Successors[BB]) {
834           Edge E = std::make_pair(BB, Succ);
835           TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
836         }
837         if (NumTotalEdges == 1) {
838           SingleEdge = std::make_pair(BB, Successors[BB][0]);
839         }
840       }
841 
842       // After visiting all the edges, there are three cases that we
843       // can handle immediately:
844       //
845       // - All the edge weights are known (i.e., NumUnknownEdges == 0).
846       //   In this case, we simply check that the sum of all the edges
847       //   is the same as BB's weight. If not, we change BB's weight
848       //   to match. Additionally, if BB had not been visited before,
849       //   we mark it visited.
850       //
851       // - Only one edge is unknown and BB has already been visited.
852       //   In this case, we can compute the weight of the edge by
853       //   subtracting the total block weight from all the known
854       //   edge weights. If the edges weight more than BB, then the
855       //   edge of the last remaining edge is set to zero.
856       //
857       // - There exists a self-referential edge and the weight of BB is
858       //   known. In this case, this edge can be based on BB's weight.
859       //   We add up all the other known edges and set the weight on
860       //   the self-referential edge as we did in the previous case.
861       //
862       // In any other case, we must continue iterating. Eventually,
863       // all edges will get a weight, or iteration will stop when
864       // it reaches SampleProfileMaxPropagateIterations.
865       if (NumUnknownEdges <= 1) {
866         uint64_t &BBWeight = BlockWeights[EC];
867         if (NumUnknownEdges == 0) {
868           if (!VisitedBlocks.count(EC)) {
869             // If we already know the weight of all edges, the weight of the
870             // basic block can be computed. It should be no larger than the sum
871             // of all edge weights.
872             if (TotalWeight > BBWeight) {
873               BBWeight = TotalWeight;
874               Changed = true;
875               DEBUG(dbgs() << "All edge weights for " << BB->getName()
876                            << " known. Set weight for block: ";
877                     printBlockWeight(dbgs(), BB););
878             }
879           } else if (NumTotalEdges == 1 &&
880                      EdgeWeights[SingleEdge] < BlockWeights[EC]) {
881             // If there is only one edge for the visited basic block, use the
882             // block weight to adjust edge weight if edge weight is smaller.
883             EdgeWeights[SingleEdge] = BlockWeights[EC];
884             Changed = true;
885           }
886         } else if (NumUnknownEdges == 1 && VisitedBlocks.count(EC)) {
887           // If there is a single unknown edge and the block has been
888           // visited, then we can compute E's weight.
889           if (BBWeight >= TotalWeight)
890             EdgeWeights[UnknownEdge] = BBWeight - TotalWeight;
891           else
892             EdgeWeights[UnknownEdge] = 0;
893           VisitedEdges.insert(UnknownEdge);
894           Changed = true;
895           DEBUG(dbgs() << "Set weight for edge: ";
896                 printEdgeWeight(dbgs(), UnknownEdge));
897         }
898       } else if (SelfReferentialEdge.first && VisitedBlocks.count(EC)) {
899         uint64_t &BBWeight = BlockWeights[BB];
900         // We have a self-referential edge and the weight of BB is known.
901         if (BBWeight >= TotalWeight)
902           EdgeWeights[SelfReferentialEdge] = BBWeight - TotalWeight;
903         else
904           EdgeWeights[SelfReferentialEdge] = 0;
905         VisitedEdges.insert(SelfReferentialEdge);
906         Changed = true;
907         DEBUG(dbgs() << "Set self-referential edge weight to: ";
908               printEdgeWeight(dbgs(), SelfReferentialEdge));
909       }
910     }
911   }
912 
913   return Changed;
914 }
915 
916 /// \brief Build in/out edge lists for each basic block in the CFG.
917 ///
918 /// We are interested in unique edges. If a block B1 has multiple
919 /// edges to another block B2, we only add a single B1->B2 edge.
buildEdges(Function & F)920 void SampleProfileLoader::buildEdges(Function &F) {
921   for (auto &BI : F) {
922     BasicBlock *B1 = &BI;
923 
924     // Add predecessors for B1.
925     SmallPtrSet<BasicBlock *, 16> Visited;
926     if (!Predecessors[B1].empty())
927       llvm_unreachable("Found a stale predecessors list in a basic block.");
928     for (pred_iterator PI = pred_begin(B1), PE = pred_end(B1); PI != PE; ++PI) {
929       BasicBlock *B2 = *PI;
930       if (Visited.insert(B2).second)
931         Predecessors[B1].push_back(B2);
932     }
933 
934     // Add successors for B1.
935     Visited.clear();
936     if (!Successors[B1].empty())
937       llvm_unreachable("Found a stale successors list in a basic block.");
938     for (succ_iterator SI = succ_begin(B1), SE = succ_end(B1); SI != SE; ++SI) {
939       BasicBlock *B2 = *SI;
940       if (Visited.insert(B2).second)
941         Successors[B1].push_back(B2);
942     }
943   }
944 }
945 
946 /// \brief Propagate weights into edges
947 ///
948 /// The following rules are applied to every block BB in the CFG:
949 ///
950 /// - If BB has a single predecessor/successor, then the weight
951 ///   of that edge is the weight of the block.
952 ///
953 /// - If all incoming or outgoing edges are known except one, and the
954 ///   weight of the block is already known, the weight of the unknown
955 ///   edge will be the weight of the block minus the sum of all the known
956 ///   edges. If the sum of all the known edges is larger than BB's weight,
957 ///   we set the unknown edge weight to zero.
958 ///
959 /// - If there is a self-referential edge, and the weight of the block is
960 ///   known, the weight for that edge is set to the weight of the block
961 ///   minus the weight of the other incoming edges to that block (if
962 ///   known).
propagateWeights(Function & F)963 void SampleProfileLoader::propagateWeights(Function &F) {
964   bool Changed = true;
965   unsigned I = 0;
966 
967   // Add an entry count to the function using the samples gathered
968   // at the function entry.
969   F.setEntryCount(Samples->getHeadSamples());
970 
971   // Before propagation starts, build, for each block, a list of
972   // unique predecessors and successors. This is necessary to handle
973   // identical edges in multiway branches. Since we visit all blocks and all
974   // edges of the CFG, it is cleaner to build these lists once at the start
975   // of the pass.
976   buildEdges(F);
977 
978   // Propagate until we converge or we go past the iteration limit.
979   while (Changed && I++ < SampleProfileMaxPropagateIterations) {
980     Changed = propagateThroughEdges(F);
981   }
982 
983   // Generate MD_prof metadata for every branch instruction using the
984   // edge weights computed during propagation.
985   DEBUG(dbgs() << "\nPropagation complete. Setting branch weights\n");
986   LLVMContext &Ctx = F.getContext();
987   MDBuilder MDB(Ctx);
988   for (auto &BI : F) {
989     BasicBlock *BB = &BI;
990 
991     if (BlockWeights[BB]) {
992       for (auto &I : BB->getInstList()) {
993         if (CallInst *CI = dyn_cast<CallInst>(&I)) {
994           if (!dyn_cast<IntrinsicInst>(&I)) {
995             SmallVector<uint32_t, 1> Weights;
996             Weights.push_back(BlockWeights[BB]);
997             CI->setMetadata(LLVMContext::MD_prof,
998                             MDB.createBranchWeights(Weights));
999           }
1000         }
1001       }
1002     }
1003     TerminatorInst *TI = BB->getTerminator();
1004     if (TI->getNumSuccessors() == 1)
1005       continue;
1006     if (!isa<BranchInst>(TI) && !isa<SwitchInst>(TI))
1007       continue;
1008 
1009     DEBUG(dbgs() << "\nGetting weights for branch at line "
1010                  << TI->getDebugLoc().getLine() << ".\n");
1011     SmallVector<uint32_t, 4> Weights;
1012     uint32_t MaxWeight = 0;
1013     DebugLoc MaxDestLoc;
1014     for (unsigned I = 0; I < TI->getNumSuccessors(); ++I) {
1015       BasicBlock *Succ = TI->getSuccessor(I);
1016       Edge E = std::make_pair(BB, Succ);
1017       uint64_t Weight = EdgeWeights[E];
1018       DEBUG(dbgs() << "\t"; printEdgeWeight(dbgs(), E));
1019       // Use uint32_t saturated arithmetic to adjust the incoming weights,
1020       // if needed. Sample counts in profiles are 64-bit unsigned values,
1021       // but internally branch weights are expressed as 32-bit values.
1022       if (Weight > std::numeric_limits<uint32_t>::max()) {
1023         DEBUG(dbgs() << " (saturated due to uint32_t overflow)");
1024         Weight = std::numeric_limits<uint32_t>::max();
1025       }
1026       Weights.push_back(static_cast<uint32_t>(Weight));
1027       if (Weight != 0) {
1028         if (Weight > MaxWeight) {
1029           MaxWeight = Weight;
1030           MaxDestLoc = Succ->getFirstNonPHIOrDbgOrLifetime()->getDebugLoc();
1031         }
1032       }
1033     }
1034 
1035     // Only set weights if there is at least one non-zero weight.
1036     // In any other case, let the analyzer set weights.
1037     if (MaxWeight > 0) {
1038       DEBUG(dbgs() << "SUCCESS. Found non-zero weights.\n");
1039       TI->setMetadata(llvm::LLVMContext::MD_prof,
1040                       MDB.createBranchWeights(Weights));
1041       DebugLoc BranchLoc = TI->getDebugLoc();
1042       emitOptimizationRemark(
1043           Ctx, DEBUG_TYPE, F, MaxDestLoc,
1044           Twine("most popular destination for conditional branches at ") +
1045               ((BranchLoc) ? Twine(BranchLoc->getFilename() + ":" +
1046                                    Twine(BranchLoc.getLine()) + ":" +
1047                                    Twine(BranchLoc.getCol()))
1048                            : Twine("<UNKNOWN LOCATION>")));
1049     } else {
1050       DEBUG(dbgs() << "SKIPPED. All branch weights are zero.\n");
1051     }
1052   }
1053 }
1054 
1055 /// \brief Get the line number for the function header.
1056 ///
1057 /// This looks up function \p F in the current compilation unit and
1058 /// retrieves the line number where the function is defined. This is
1059 /// line 0 for all the samples read from the profile file. Every line
1060 /// number is relative to this line.
1061 ///
1062 /// \param F  Function object to query.
1063 ///
1064 /// \returns the line number where \p F is defined. If it returns 0,
1065 ///          it means that there is no debug information available for \p F.
getFunctionLoc(Function & F)1066 unsigned SampleProfileLoader::getFunctionLoc(Function &F) {
1067   if (DISubprogram *S = F.getSubprogram())
1068     return S->getLine();
1069 
1070   // If the start of \p F is missing, emit a diagnostic to inform the user
1071   // about the missed opportunity.
1072   F.getContext().diagnose(DiagnosticInfoSampleProfile(
1073       "No debug information found in function " + F.getName() +
1074           ": Function profile not used",
1075       DS_Warning));
1076   return 0;
1077 }
1078 
computeDominanceAndLoopInfo(Function & F)1079 void SampleProfileLoader::computeDominanceAndLoopInfo(Function &F) {
1080   DT.reset(new DominatorTree);
1081   DT->recalculate(F);
1082 
1083   PDT.reset(new DominatorTreeBase<BasicBlock>(true));
1084   PDT->recalculate(F);
1085 
1086   LI.reset(new LoopInfo);
1087   LI->analyze(*DT);
1088 }
1089 
1090 /// \brief Generate branch weight metadata for all branches in \p F.
1091 ///
1092 /// Branch weights are computed out of instruction samples using a
1093 /// propagation heuristic. Propagation proceeds in 3 phases:
1094 ///
1095 /// 1- Assignment of block weights. All the basic blocks in the function
1096 ///    are initial assigned the same weight as their most frequently
1097 ///    executed instruction.
1098 ///
1099 /// 2- Creation of equivalence classes. Since samples may be missing from
1100 ///    blocks, we can fill in the gaps by setting the weights of all the
1101 ///    blocks in the same equivalence class to the same weight. To compute
1102 ///    the concept of equivalence, we use dominance and loop information.
1103 ///    Two blocks B1 and B2 are in the same equivalence class if B1
1104 ///    dominates B2, B2 post-dominates B1 and both are in the same loop.
1105 ///
1106 /// 3- Propagation of block weights into edges. This uses a simple
1107 ///    propagation heuristic. The following rules are applied to every
1108 ///    block BB in the CFG:
1109 ///
1110 ///    - If BB has a single predecessor/successor, then the weight
1111 ///      of that edge is the weight of the block.
1112 ///
1113 ///    - If all the edges are known except one, and the weight of the
1114 ///      block is already known, the weight of the unknown edge will
1115 ///      be the weight of the block minus the sum of all the known
1116 ///      edges. If the sum of all the known edges is larger than BB's weight,
1117 ///      we set the unknown edge weight to zero.
1118 ///
1119 ///    - If there is a self-referential edge, and the weight of the block is
1120 ///      known, the weight for that edge is set to the weight of the block
1121 ///      minus the weight of the other incoming edges to that block (if
1122 ///      known).
1123 ///
1124 /// Since this propagation is not guaranteed to finalize for every CFG, we
1125 /// only allow it to proceed for a limited number of iterations (controlled
1126 /// by -sample-profile-max-propagate-iterations).
1127 ///
1128 /// FIXME: Try to replace this propagation heuristic with a scheme
1129 /// that is guaranteed to finalize. A work-list approach similar to
1130 /// the standard value propagation algorithm used by SSA-CCP might
1131 /// work here.
1132 ///
1133 /// Once all the branch weights are computed, we emit the MD_prof
1134 /// metadata on BB using the computed values for each of its branches.
1135 ///
1136 /// \param F The function to query.
1137 ///
1138 /// \returns true if \p F was modified. Returns false, otherwise.
emitAnnotations(Function & F)1139 bool SampleProfileLoader::emitAnnotations(Function &F) {
1140   bool Changed = false;
1141 
1142   if (getFunctionLoc(F) == 0)
1143     return false;
1144 
1145   DEBUG(dbgs() << "Line number for the first instruction in " << F.getName()
1146                << ": " << getFunctionLoc(F) << "\n");
1147 
1148   Changed |= inlineHotFunctions(F);
1149 
1150   // Compute basic block weights.
1151   Changed |= computeBlockWeights(F);
1152 
1153   if (Changed) {
1154     // Compute dominance and loop info needed for propagation.
1155     computeDominanceAndLoopInfo(F);
1156 
1157     // Find equivalence classes.
1158     findEquivalenceClasses(F);
1159 
1160     // Propagate weights to all edges.
1161     propagateWeights(F);
1162   }
1163 
1164   // If coverage checking was requested, compute it now.
1165   if (SampleProfileRecordCoverage) {
1166     unsigned Used = CoverageTracker.countUsedRecords(Samples);
1167     unsigned Total = CoverageTracker.countBodyRecords(Samples);
1168     unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
1169     if (Coverage < SampleProfileRecordCoverage) {
1170       F.getContext().diagnose(DiagnosticInfoSampleProfile(
1171           F.getSubprogram()->getFilename(), getFunctionLoc(F),
1172           Twine(Used) + " of " + Twine(Total) + " available profile records (" +
1173               Twine(Coverage) + "%) were applied",
1174           DS_Warning));
1175     }
1176   }
1177 
1178   if (SampleProfileSampleCoverage) {
1179     uint64_t Used = CoverageTracker.getTotalUsedSamples();
1180     uint64_t Total = CoverageTracker.countBodySamples(Samples);
1181     unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
1182     if (Coverage < SampleProfileSampleCoverage) {
1183       F.getContext().diagnose(DiagnosticInfoSampleProfile(
1184           F.getSubprogram()->getFilename(), getFunctionLoc(F),
1185           Twine(Used) + " of " + Twine(Total) + " available profile samples (" +
1186               Twine(Coverage) + "%) were applied",
1187           DS_Warning));
1188     }
1189   }
1190   return Changed;
1191 }
1192 
1193 char SampleProfileLoaderLegacyPass::ID = 0;
1194 INITIALIZE_PASS_BEGIN(SampleProfileLoaderLegacyPass, "sample-profile",
1195                 "Sample Profile loader", false, false)
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)1196 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
1197 INITIALIZE_PASS_END(SampleProfileLoaderLegacyPass, "sample-profile",
1198                 "Sample Profile loader", false, false)
1199 
1200 bool SampleProfileLoader::doInitialization(Module &M) {
1201   auto &Ctx = M.getContext();
1202   auto ReaderOrErr = SampleProfileReader::create(Filename, Ctx);
1203   if (std::error_code EC = ReaderOrErr.getError()) {
1204     std::string Msg = "Could not open profile: " + EC.message();
1205     Ctx.diagnose(DiagnosticInfoSampleProfile(Filename, Msg));
1206     return false;
1207   }
1208   Reader = std::move(ReaderOrErr.get());
1209   ProfileIsValid = (Reader->read() == sampleprof_error::success);
1210   return true;
1211 }
1212 
createSampleProfileLoaderPass()1213 ModulePass *llvm::createSampleProfileLoaderPass() {
1214   return new SampleProfileLoaderLegacyPass(SampleProfileFile);
1215 }
1216 
createSampleProfileLoaderPass(StringRef Name)1217 ModulePass *llvm::createSampleProfileLoaderPass(StringRef Name) {
1218   return new SampleProfileLoaderLegacyPass(Name);
1219 }
1220 
runOnModule(Module & M)1221 bool SampleProfileLoader::runOnModule(Module &M) {
1222   if (!ProfileIsValid)
1223     return false;
1224 
1225   // Compute the total number of samples collected in this profile.
1226   for (const auto &I : Reader->getProfiles())
1227     TotalCollectedSamples += I.second.getTotalSamples();
1228 
1229   bool retval = false;
1230   for (auto &F : M)
1231     if (!F.isDeclaration()) {
1232       clearFunctionData();
1233       retval |= runOnFunction(F);
1234     }
1235   M.setProfileSummary(Reader->getSummary().getMD(M.getContext()));
1236   return retval;
1237 }
1238 
runOnModule(Module & M)1239 bool SampleProfileLoaderLegacyPass::runOnModule(Module &M) {
1240   // FIXME: pass in AssumptionCache correctly for the new pass manager.
1241   SampleLoader.setACT(&getAnalysis<AssumptionCacheTracker>());
1242   return SampleLoader.runOnModule(M);
1243 }
1244 
runOnFunction(Function & F)1245 bool SampleProfileLoader::runOnFunction(Function &F) {
1246   F.setEntryCount(0);
1247   Samples = Reader->getSamplesFor(F);
1248   if (!Samples->empty())
1249     return emitAnnotations(F);
1250   return false;
1251 }
1252 
run(Module & M,AnalysisManager<Module> & AM)1253 PreservedAnalyses SampleProfileLoaderPass::run(Module &M,
1254                                                AnalysisManager<Module> &AM) {
1255 
1256   SampleProfileLoader SampleLoader(SampleProfileFile);
1257 
1258   SampleLoader.doInitialization(M);
1259 
1260   if (!SampleLoader.runOnModule(M))
1261     return PreservedAnalyses::all();
1262 
1263   return PreservedAnalyses::none();
1264 }
1265