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1 // Auto-generated file. Do not edit!
2 //   Template: src/f32-raddstoreexpminusmax/neon-lut64-p2.c.in
3 //   Generator: tools/xngen
4 //
5 // Copyright 2020 Google LLC
6 //
7 // This source code is licensed under the BSD-style license found in the
8 // LICENSE file in the root directory of this source tree.
9 
10 #include <assert.h>
11 
12 #include <arm_neon.h>
13 
14 #include <xnnpack/common.h>
15 #include <xnnpack/raddstoreexpminusmax.h>
16 
17 
18 extern XNN_INTERNAL const float xnn_table_exp2_k_over_64[64];
19 
xnn_f32_raddstoreexpminusmax_ukernel__neon_lut64_p2_x12_acc3(size_t elements,const float * input,float * output,float * sum,float max)20 void xnn_f32_raddstoreexpminusmax_ukernel__neon_lut64_p2_x12_acc3(
21     size_t elements,
22     const float* input,
23     float* output,
24     float* sum,
25     float max)
26 {
27   assert(elements % sizeof(float) == 0);
28 
29   const float32x4_t vmagic_bias = vmovq_n_f32(0x1.800000p23f);
30   // The smallest x for which expf(x) is normalized.
31   const float32x4_t vdenorm_cutoff = vmovq_n_f32(-0x1.5D589Ep6f);
32   const float32x4_t vlog2e_x64  = vmovq_n_f32(0x1.715476p6f);
33   // Last 13 bits are zeroes
34   const float32x4_t vminus_ln2_o64_hi = vmovq_n_f32(-0x1.630000p-7f);
35   const float32x4_t vminus_ln2_o64_lo = vmovq_n_f32(0x1.BD0106p-19f);
36 
37   const float32x4_t vc2 = vmovq_n_f32(0x1.FFFF0Ap-2f);
38 
39   const int32x4_t vindex_mask = vmovq_n_s32(INT32_C(0x3F));
40 
41   const float32x4_t vi_max = vdupq_n_f32(max);
42 
43   float32x4_t vacc0 = vmovq_n_f32(0.0f);
44   float32x4_t vacc1 = vmovq_n_f32(0.0f);
45   float32x4_t vacc2 = vmovq_n_f32(0.0f);
46   for (; elements >= 12 * sizeof(float); elements -= 12 * sizeof(float)) {
47     // Load 12 (3x4) inputs at a time.
48     const float32x4_t vi0123 = vld1q_f32(input); input += 4;
49     const float32x4_t vi4567 = vld1q_f32(input); input += 4;
50     const float32x4_t vi89AB = vld1q_f32(input); input += 4;
51 
52     // Subtract maximum input x := i - i_max. This implies x <= 0.
53     const float32x4_t vx0123 = vsubq_f32(vi0123, vi_max);
54     const float32x4_t vx4567 = vsubq_f32(vi4567, vi_max);
55     const float32x4_t vx89AB = vsubq_f32(vi89AB, vi_max);
56 
57     // Compute reduced argument n := round(x * 64 / log(2)).
58     // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing
59     // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
60     // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e.
61     // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0]
62     // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the
63     // algorithm.
64     float32x4_t vn0123 = vmlaq_f32(vmagic_bias, vx0123, vlog2e_x64);
65     float32x4_t vn4567 = vmlaq_f32(vmagic_bias, vx4567, vlog2e_x64);
66     float32x4_t vn89AB = vmlaq_f32(vmagic_bias, vx89AB, vlog2e_x64);
67 
68     // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized,
69     // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where
70     // e := int(n / 64). We create s in two steps:
71     // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) from the table using the 6 low bits of n, as integer. Note that the
72     //    fetched values are in the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
73     // 2. Adjust fecthed value by addition of e to its floating-point exponent. The result is always a normalized
74     //    number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0,
75     //    and thus the adjusted exponent is not lower than -126.
76     //
77     // Extract e from bits 6:14 of n and shift it into bits 23:31 (position of floating-point exponent).
78     const int32x4_t ve0123 = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn0123), vmovq_n_s32(INT32_C(0x3F))), 17);
79     const int32x4_t ve4567 = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn4567), vmovq_n_s32(INT32_C(0x3F))), 17);
80     const int32x4_t ve89AB = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn89AB), vmovq_n_s32(INT32_C(0x3F))), 17);
81 
82     // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64).
83     const uint64x2_t vidx0123 = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn0123), vindex_mask));
84     const uint64_t vidx01 = vgetq_lane_u64(vidx0123, 0);
85     const uint64_t vidx23 = vgetq_lane_u64(vidx0123, 1);
86     const uint64x2_t vidx4567 = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn4567), vindex_mask));
87     const uint64_t vidx45 = vgetq_lane_u64(vidx4567, 0);
88     const uint64_t vidx67 = vgetq_lane_u64(vidx4567, 1);
89     const uint64x2_t vidx89AB = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn89AB), vindex_mask));
90     const uint64_t vidx89 = vgetq_lane_u64(vidx89AB, 0);
91     const uint64_t vidxAB = vgetq_lane_u64(vidx89AB, 1);
92 
93     float32x2_t vl01 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx01]);
94     float32x2_t vl23 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx23]);
95     float32x2_t vl45 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx45]);
96     float32x2_t vl67 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx67]);
97     float32x2_t vl89 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx89]);
98     float32x2_t vlAB = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidxAB]);
99 
100     vl01 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx01 >> 32)], vl01, 1);
101     vl23 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx23 >> 32)], vl23, 1);
102     const float32x4_t vl0123 = vcombine_f32(vl01, vl23);
103     vl45 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx45 >> 32)], vl45, 1);
104     vl67 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx67 >> 32)], vl67, 1);
105     const float32x4_t vl4567 = vcombine_f32(vl45, vl67);
106     vl89 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx89 >> 32)], vl89, 1);
107     vlAB = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidxAB >> 32)], vlAB, 1);
108     const float32x4_t vl89AB = vcombine_f32(vl89, vlAB);
109 
110     // Adjust exponent of the value l fetched from the table to get the final s value.
111     const float32x4_t vs0123 = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl0123), ve0123));
112     const float32x4_t vs4567 = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl4567), ve4567));
113     const float32x4_t vs89AB = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl89AB), ve89AB));
114 
115     // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number.
116     vn0123 = vsubq_f32(vn0123, vmagic_bias);
117     vn4567 = vsubq_f32(vn4567, vmagic_bias);
118     vn89AB = vsubq_f32(vn89AB, vmagic_bias);
119 
120     // Compute reduced argument t := x - n * log(2) / 64.
121     // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy.
122     float32x4_t vt0123 = vmlaq_f32(vx0123, vn0123, vminus_ln2_o64_hi);
123     float32x4_t vt4567 = vmlaq_f32(vx4567, vn4567, vminus_ln2_o64_hi);
124     float32x4_t vt89AB = vmlaq_f32(vx89AB, vn89AB, vminus_ln2_o64_hi);
125 
126     vt0123 = vmlaq_f32(vt0123, vn0123, vminus_ln2_o64_lo);
127     vt4567 = vmlaq_f32(vt4567, vn4567, vminus_ln2_o64_lo);
128     vt89AB = vmlaq_f32(vt89AB, vn89AB, vminus_ln2_o64_lo);
129 
130     // Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128].
131     float32x4_t vp0123 = vmulq_f32(vt0123, vc2);
132     float32x4_t vp4567 = vmulq_f32(vt4567, vc2);
133     float32x4_t vp89AB = vmulq_f32(vt89AB, vc2);
134 
135     vp0123 = vmlaq_f32(vt0123, vt0123, vp0123);
136     vp4567 = vmlaq_f32(vt4567, vt4567, vp4567);
137     vp89AB = vmlaq_f32(vt89AB, vt89AB, vp89AB);
138 
139     // Reconstruct the final f value:
140     //   f = s * (1 + t * (1 + t * c2))
141     //     = s * (1 + t + t * (t * c2))
142     //     = s + s * (t + t * (t * c2))
143     //     = s + s * p
144     float32x4_t vf0123 = vmlaq_f32(vs0123, vs0123, vp0123);
145     float32x4_t vf4567 = vmlaq_f32(vs4567, vs4567, vp4567);
146     float32x4_t vf89AB = vmlaq_f32(vs89AB, vs89AB, vp89AB);
147 
148     // For inputs below denormal cutoff, replace output with +0.0f.
149     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
150     vf0123 = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf0123), vcltq_f32(vx0123, vdenorm_cutoff)));
151     vf4567 = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf4567), vcltq_f32(vx4567, vdenorm_cutoff)));
152     vf89AB = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf89AB), vcltq_f32(vx89AB, vdenorm_cutoff)));
153 
154     // Store 12 (3x4) outputs at a time.
155     vst1q_f32(output, vf0123); output += 4;
156     vst1q_f32(output, vf4567); output += 4;
157     vst1q_f32(output, vf89AB); output += 4;
158 
159     // Accumulate computed exponents.
160     vacc0 = vaddq_f32(vacc0, vf0123);
161     vacc1 = vaddq_f32(vacc1, vf4567);
162     vacc2 = vaddq_f32(vacc2, vf89AB);
163   }
164   // Add up all accumulators to vacc0
165   vacc0 = vaddq_f32(vacc0, vacc1);
166   vacc0 = vaddq_f32(vacc0, vacc2);
167 
168   float32x4_t vacc = vacc0;
169   for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
170     // Load 4 inputs at a time.
171     const float32x4_t vi = vld1q_f32(input); input += 4;
172 
173     // Subtract maximum input x := i - i_max. This implies x <= 0.
174     const float32x4_t vx = vsubq_f32(vi, vi_max);
175 
176     // Compute reduced argument n := round(x * 64 / log(2)).
177     // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing
178     // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
179     // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e.
180     // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0]
181     // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the
182     // algorithm.
183     float32x4_t vn = vmlaq_f32(vmagic_bias, vx, vlog2e_x64);
184 
185     // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized,
186     // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where
187     // e := int(n / 64). We create s in two steps:
188     // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) from the table using the 6 low bits of n, as integer. Note that the
189     //    fetched values are in the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
190     // 2. Adjust fecthed value by addition of e to its floating-point exponent. The result is always a normalized
191     //    number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0,
192     //    and thus the adjusted exponent is not lower than -126.
193     //
194     // Extract e from bits 6:14 of n and shift it into bits 23:31 (position of floating-point exponent).
195     const int32x4_t ve = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn), vmovq_n_s32(INT32_C(0x3F))), 17);
196 
197     // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64).
198     const uint64x2_t vidx = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn), vindex_mask));
199     const uint64_t vidx_lo = vgetq_lane_u64(vidx, 0);
200     const uint64_t vidx_hi = vgetq_lane_u64(vidx, 1);
201     float32x2_t vl_lo = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_lo]);
202     float32x2_t vl_hi = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_hi]);
203     vl_lo = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_lo >> 32)], vl_lo, 1);
204     vl_hi = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_hi >> 32)], vl_hi, 1);
205     const float32x4_t vl = vcombine_f32(vl_lo, vl_hi);
206     // Adjust exponent of the value l fetched from the table to get the final s value.
207     const float32x4_t vs = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl), ve));
208 
209     // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number.
210     vn = vsubq_f32(vn, vmagic_bias);
211 
212     // Compute reduced argument t := x - n * log(2) / 64.
213     // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy.
214     float32x4_t vt = vmlaq_f32(vx, vn, vminus_ln2_o64_hi);
215     vt = vmlaq_f32(vt, vn, vminus_ln2_o64_lo);
216 
217     // Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128].
218     float32x4_t vp = vmulq_f32(vt, vc2);
219     vp = vmlaq_f32(vt, vt, vp);
220 
221     // Reconstruct the final f value:
222     //   f = s * (1 + t * (1 + t * c2))
223     //     = s * (1 + t + t * (t * c2))
224     //     = s + s * (t + t * (t * c2))
225     //     = s + s * p
226     float32x4_t vf = vmlaq_f32(vs, vs, vp);
227 
228     // For inputs below denormal cutoff, replace output with +0.0f.
229     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
230     vf = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcltq_f32(vx, vdenorm_cutoff)));
231 
232     // Store 4 outputs at a time.
233     vst1q_f32(output, vf); output += 4;
234 
235     // Accumulate computed exponents.
236     vacc = vaddq_f32(vacc, vf);
237   }
238 #if XNN_ARCH_ARM64
239   float vacc_lo = vaddvq_f32(vacc);
240 #else
241   float32x2_t vacc_lo = vadd_f32(vget_high_f32(vacc), vget_low_f32(vacc));
242 #endif
243   if (elements != 0) {
244     assert(elements >= 1 * sizeof(float));
245     assert(elements <= 3 * sizeof(float));
246     // Load 4 inputs at a time.
247     const float32x4_t vi = vld1q_f32(input); input += 4;
248 
249     // Subtract maximum input x := i - i_max. This implies x <= 0.
250     const float32x4_t vx = vsubq_f32(vi, vi_max);
251 
252     // Compute reduced argument n := round(x * 64 / log(2)).
253     // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing
254     // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
255     // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e.
256     // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0]
257     // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the
258     // algorithm.
259     float32x4_t vn = vmlaq_f32(vmagic_bias, vx, vlog2e_x64);
260 
261     // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized,
262     // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where
263     // e := int(n / 64). We create s in two steps:
264     // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) from the table using the 6 low bits of n, as integer. Note that the
265     //    fetched values are in the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
266     // 2. Adjust fecthed value by addition of e to its floating-point exponent. The result is always a normalized
267     //    number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0,
268     //    and thus the adjusted exponent is not lower than -126.
269     //
270     // Extract e from bits 6:14 of n and shift it into bits 23:31 (position of floating-point exponent).
271     const int32x4_t ve = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn), vmovq_n_s32(INT32_C(0x3F))), 17);
272 
273     // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64).
274     const uint64x2_t vidx = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn), vindex_mask));
275     const uint64_t vidx_lo = vgetq_lane_u64(vidx, 0);
276     const uint64_t vidx_hi = vgetq_lane_u64(vidx, 1);
277     float32x2_t vl_lo = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_lo]);
278     float32x2_t vl_hi = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_hi]);
279     vl_lo = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_lo >> 32)], vl_lo, 1);
280     vl_hi = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_hi >> 32)], vl_hi, 1);
281     const float32x4_t vl = vcombine_f32(vl_lo, vl_hi);
282     // Adjust exponent of the value l fetched from the table to get the final s value.
283     const float32x4_t vs = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl), ve));
284 
285     // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number.
286     vn = vsubq_f32(vn, vmagic_bias);
287 
288     // Compute reduced argument t := x - n * log(2) / 64.
289     // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy.
290     float32x4_t vt = vmlaq_f32(vx, vn, vminus_ln2_o64_hi);
291     vt = vmlaq_f32(vt, vn, vminus_ln2_o64_lo);
292 
293     // Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128].
294     float32x4_t vp = vmulq_f32(vt, vc2);
295     vp = vmlaq_f32(vt, vt, vp);
296 
297     // Reconstruct the final f value:
298     //   f = s * (1 + t * (1 + t * c2))
299     //     = s * (1 + t + t * (t * c2))
300     //     = s + s * (t + t * (t * c2))
301     //     = s + s * p
302     float32x4_t vf = vmlaq_f32(vs, vs, vp);
303 
304     // For inputs below denormal cutoff, replace output with +0.0f.
305     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
306     vf = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcltq_f32(vx, vdenorm_cutoff)));
307 
308     float32x2_t vf_lo = vget_low_f32(vf);
309     if (elements & (2 * sizeof(float))) {
310       // Store 2 outputs at a time.
311       vst1_f32(output, vf_lo); output += 2;
312 
313       // Accumulate 2 computed exponents.
314       #if XNN_ARCH_ARM64
315         vacc_lo += vaddv_f32(vf_lo);
316       #else
317         vacc_lo = vadd_f32(vacc_lo, vf_lo);
318       #endif
319 
320       vf_lo = vget_high_f32(vf);
321     }
322     if (elements & (1 * sizeof(float))) {
323       // Store 1 output at a time.
324       vst1_lane_f32(output, vf_lo, 0);
325 
326       // Accumulate 1 computed exponent.
327       #if XNN_ARCH_ARM64
328         vacc_lo += vget_lane_f32(vf_lo, 0);
329       #else
330         vacc_lo = vadd_f32(vacc_lo, vreinterpret_f32_u64(vshl_n_u64(vreinterpret_u64_f32(vf_lo), 32)));
331       #endif
332     }
333   }
334   // Reduce 4 elements in the SIMD register
335 #if XNN_ARCH_ARM64
336   *sum = vacc_lo;
337 #else
338   vst1_lane_f32(sum, vpadd_f32(vacc_lo, vacc_lo), 0);
339 #endif
340 }
341