1 // Auto-generated file. Do not edit!
2 // Template: src/f32-raddexpminusmax/avx2-p5.c.in
3 // Generator: tools/xngen
4 //
5 // Copyright 2019 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 <immintrin.h>
13
14 #include <xnnpack/raddexpminusmax.h>
15
16
17 static const int32_t mask_table[14] = {-1, -1, -1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 0, 0};
18
xnn_f32_raddexpminusmax_ukernel__avx2_p5_x96(size_t elements,const float * input,float * sum,float max)19 void xnn_f32_raddexpminusmax_ukernel__avx2_p5_x96(
20 size_t elements,
21 const float* input,
22 float* sum,
23 float max)
24 {
25 assert(elements % sizeof(float) == 0);
26
27 const __m256 vmagic_bias = _mm256_set1_ps(0x1.8000FEp23f);
28 // The smallest x for which expf(x) is normalized.
29 const __m256 vdenorm_cutoff = _mm256_set1_ps(-0x1.5D589Ep6f);
30 const __m256 vlog2e = _mm256_set1_ps(0x1.715476p+0f);
31 const __m256 vminus_ln2_hi = _mm256_set1_ps(-0x1.62E43p-1f);
32 const __m256 vminus_ln2_lo = _mm256_set1_ps(0x1.05C61p-29f);
33
34 const __m256 vc1 = _mm256_set1_ps(0x1.FFFFF6p-1f);
35 const __m256 vc2 = _mm256_set1_ps(0x1.FFFDC6p-2f);
36 const __m256 vc3 = _mm256_set1_ps(0x1.555A80p-3f);
37 const __m256 vc4 = _mm256_set1_ps(0x1.573A1Ap-5f);
38 const __m256 vc5 = _mm256_set1_ps(0x1.0F9F9Cp-7f);
39
40 const __m256 vi_max = _mm256_set1_ps(max);
41
42 __m256 vacc0 = _mm256_setzero_ps();
43 for (; elements >= 96 * sizeof(float); elements -= 96 * sizeof(float)) {
44 // Load 96 (12x8) inputs at a time.
45 const __m256 vi0 = _mm256_loadu_ps(input);
46 const __m256 vi1 = _mm256_loadu_ps(input + 8);
47 const __m256 vi2 = _mm256_loadu_ps(input + 16);
48 const __m256 vi3 = _mm256_loadu_ps(input + 24);
49 const __m256 vi4 = _mm256_loadu_ps(input + 32);
50 const __m256 vi5 = _mm256_loadu_ps(input + 40);
51 const __m256 vi6 = _mm256_loadu_ps(input + 48);
52 const __m256 vi7 = _mm256_loadu_ps(input + 56);
53 const __m256 vi8 = _mm256_loadu_ps(input + 64);
54 const __m256 vi9 = _mm256_loadu_ps(input + 72);
55 const __m256 vi10 = _mm256_loadu_ps(input + 80);
56 const __m256 vi11 = _mm256_loadu_ps(input + 88);
57 input += 96;
58
59 // Subtract maximum input x := i - i_max. This implies x <= 0.
60 const __m256 vx0 = _mm256_sub_ps(vi0, vi_max);
61 const __m256 vx1 = _mm256_sub_ps(vi1, vi_max);
62 const __m256 vx2 = _mm256_sub_ps(vi2, vi_max);
63 const __m256 vx3 = _mm256_sub_ps(vi3, vi_max);
64 const __m256 vx4 = _mm256_sub_ps(vi4, vi_max);
65 const __m256 vx5 = _mm256_sub_ps(vi5, vi_max);
66 const __m256 vx6 = _mm256_sub_ps(vi6, vi_max);
67 const __m256 vx7 = _mm256_sub_ps(vi7, vi_max);
68 const __m256 vx8 = _mm256_sub_ps(vi8, vi_max);
69 const __m256 vx9 = _mm256_sub_ps(vi9, vi_max);
70 const __m256 vx10 = _mm256_sub_ps(vi10, vi_max);
71 const __m256 vx11 = _mm256_sub_ps(vi11, vi_max);
72
73 // Compute reduced argument elements := round(x / log(2)).
74 __m256 vn0 = _mm256_fmadd_ps(vx0, vlog2e, vmagic_bias);
75 __m256 vn1 = _mm256_fmadd_ps(vx1, vlog2e, vmagic_bias);
76 __m256 vn2 = _mm256_fmadd_ps(vx2, vlog2e, vmagic_bias);
77 __m256 vn3 = _mm256_fmadd_ps(vx3, vlog2e, vmagic_bias);
78 __m256 vn4 = _mm256_fmadd_ps(vx4, vlog2e, vmagic_bias);
79 __m256 vn5 = _mm256_fmadd_ps(vx5, vlog2e, vmagic_bias);
80 __m256 vn6 = _mm256_fmadd_ps(vx6, vlog2e, vmagic_bias);
81 __m256 vn7 = _mm256_fmadd_ps(vx7, vlog2e, vmagic_bias);
82 __m256 vn8 = _mm256_fmadd_ps(vx8, vlog2e, vmagic_bias);
83 __m256 vn9 = _mm256_fmadd_ps(vx9, vlog2e, vmagic_bias);
84 __m256 vn10 = _mm256_fmadd_ps(vx10, vlog2e, vmagic_bias);
85 __m256 vn11 = _mm256_fmadd_ps(vx11, vlog2e, vmagic_bias);
86
87 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
88 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
89 const __m256 vs0 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn0), 23));
90 const __m256 vs1 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn1), 23));
91 const __m256 vs2 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn2), 23));
92 const __m256 vs3 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn3), 23));
93 const __m256 vs4 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn4), 23));
94 const __m256 vs5 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn5), 23));
95 const __m256 vs6 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn6), 23));
96 const __m256 vs7 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn7), 23));
97 const __m256 vs8 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn8), 23));
98 const __m256 vs9 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn9), 23));
99 const __m256 vs10 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn10), 23));
100 const __m256 vs11 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn11), 23));
101
102 // Subtract the large number back to get final elements := round(x / log(2)).
103 vn0 = _mm256_sub_ps(vn0, vmagic_bias);
104 vn1 = _mm256_sub_ps(vn1, vmagic_bias);
105 vn2 = _mm256_sub_ps(vn2, vmagic_bias);
106 vn3 = _mm256_sub_ps(vn3, vmagic_bias);
107 vn4 = _mm256_sub_ps(vn4, vmagic_bias);
108 vn5 = _mm256_sub_ps(vn5, vmagic_bias);
109 vn6 = _mm256_sub_ps(vn6, vmagic_bias);
110 vn7 = _mm256_sub_ps(vn7, vmagic_bias);
111 vn8 = _mm256_sub_ps(vn8, vmagic_bias);
112 vn9 = _mm256_sub_ps(vn9, vmagic_bias);
113 vn10 = _mm256_sub_ps(vn10, vmagic_bias);
114 vn11 = _mm256_sub_ps(vn11, vmagic_bias);
115
116 // Compute reduced argument t := x - elements * log(2).
117 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
118 __m256 vt0 = _mm256_fmadd_ps(vn0, vminus_ln2_hi, vx0);
119 __m256 vt1 = _mm256_fmadd_ps(vn1, vminus_ln2_hi, vx1);
120 __m256 vt2 = _mm256_fmadd_ps(vn2, vminus_ln2_hi, vx2);
121 __m256 vt3 = _mm256_fmadd_ps(vn3, vminus_ln2_hi, vx3);
122 __m256 vt4 = _mm256_fmadd_ps(vn4, vminus_ln2_hi, vx4);
123 __m256 vt5 = _mm256_fmadd_ps(vn5, vminus_ln2_hi, vx5);
124 __m256 vt6 = _mm256_fmadd_ps(vn6, vminus_ln2_hi, vx6);
125 __m256 vt7 = _mm256_fmadd_ps(vn7, vminus_ln2_hi, vx7);
126 __m256 vt8 = _mm256_fmadd_ps(vn8, vminus_ln2_hi, vx8);
127 __m256 vt9 = _mm256_fmadd_ps(vn9, vminus_ln2_hi, vx9);
128 __m256 vt10 = _mm256_fmadd_ps(vn10, vminus_ln2_hi, vx10);
129 __m256 vt11 = _mm256_fmadd_ps(vn11, vminus_ln2_hi, vx11);
130
131 vt0 = _mm256_fmadd_ps(vn0, vminus_ln2_lo, vt0);
132 vt1 = _mm256_fmadd_ps(vn1, vminus_ln2_lo, vt1);
133 vt2 = _mm256_fmadd_ps(vn2, vminus_ln2_lo, vt2);
134 vt3 = _mm256_fmadd_ps(vn3, vminus_ln2_lo, vt3);
135 vt4 = _mm256_fmadd_ps(vn4, vminus_ln2_lo, vt4);
136 vt5 = _mm256_fmadd_ps(vn5, vminus_ln2_lo, vt5);
137 vt6 = _mm256_fmadd_ps(vn6, vminus_ln2_lo, vt6);
138 vt7 = _mm256_fmadd_ps(vn7, vminus_ln2_lo, vt7);
139 vt8 = _mm256_fmadd_ps(vn8, vminus_ln2_lo, vt8);
140 vt9 = _mm256_fmadd_ps(vn9, vminus_ln2_lo, vt9);
141 vt10 = _mm256_fmadd_ps(vn10, vminus_ln2_lo, vt10);
142 vt11 = _mm256_fmadd_ps(vn11, vminus_ln2_lo, vt11);
143
144 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
145 __m256 vp0 = _mm256_fmadd_ps(vc5, vt0, vc4);
146 __m256 vp1 = _mm256_fmadd_ps(vc5, vt1, vc4);
147 __m256 vp2 = _mm256_fmadd_ps(vc5, vt2, vc4);
148 __m256 vp3 = _mm256_fmadd_ps(vc5, vt3, vc4);
149 __m256 vp4 = _mm256_fmadd_ps(vc5, vt4, vc4);
150 __m256 vp5 = _mm256_fmadd_ps(vc5, vt5, vc4);
151 __m256 vp6 = _mm256_fmadd_ps(vc5, vt6, vc4);
152 __m256 vp7 = _mm256_fmadd_ps(vc5, vt7, vc4);
153 __m256 vp8 = _mm256_fmadd_ps(vc5, vt8, vc4);
154 __m256 vp9 = _mm256_fmadd_ps(vc5, vt9, vc4);
155 __m256 vp10 = _mm256_fmadd_ps(vc5, vt10, vc4);
156 __m256 vp11 = _mm256_fmadd_ps(vc5, vt11, vc4);
157
158 vp0 = _mm256_fmadd_ps(vp0, vt0, vc3);
159 vp1 = _mm256_fmadd_ps(vp1, vt1, vc3);
160 vp2 = _mm256_fmadd_ps(vp2, vt2, vc3);
161 vp3 = _mm256_fmadd_ps(vp3, vt3, vc3);
162 vp4 = _mm256_fmadd_ps(vp4, vt4, vc3);
163 vp5 = _mm256_fmadd_ps(vp5, vt5, vc3);
164 vp6 = _mm256_fmadd_ps(vp6, vt6, vc3);
165 vp7 = _mm256_fmadd_ps(vp7, vt7, vc3);
166 vp8 = _mm256_fmadd_ps(vp8, vt8, vc3);
167 vp9 = _mm256_fmadd_ps(vp9, vt9, vc3);
168 vp10 = _mm256_fmadd_ps(vp10, vt10, vc3);
169 vp11 = _mm256_fmadd_ps(vp11, vt11, vc3);
170
171 vp0 = _mm256_fmadd_ps(vp0, vt0, vc2);
172 vp1 = _mm256_fmadd_ps(vp1, vt1, vc2);
173 vp2 = _mm256_fmadd_ps(vp2, vt2, vc2);
174 vp3 = _mm256_fmadd_ps(vp3, vt3, vc2);
175 vp4 = _mm256_fmadd_ps(vp4, vt4, vc2);
176 vp5 = _mm256_fmadd_ps(vp5, vt5, vc2);
177 vp6 = _mm256_fmadd_ps(vp6, vt6, vc2);
178 vp7 = _mm256_fmadd_ps(vp7, vt7, vc2);
179 vp8 = _mm256_fmadd_ps(vp8, vt8, vc2);
180 vp9 = _mm256_fmadd_ps(vp9, vt9, vc2);
181 vp10 = _mm256_fmadd_ps(vp10, vt10, vc2);
182 vp11 = _mm256_fmadd_ps(vp11, vt11, vc2);
183
184 vp0 = _mm256_fmadd_ps(vp0, vt0, vc1);
185 vp1 = _mm256_fmadd_ps(vp1, vt1, vc1);
186 vp2 = _mm256_fmadd_ps(vp2, vt2, vc1);
187 vp3 = _mm256_fmadd_ps(vp3, vt3, vc1);
188 vp4 = _mm256_fmadd_ps(vp4, vt4, vc1);
189 vp5 = _mm256_fmadd_ps(vp5, vt5, vc1);
190 vp6 = _mm256_fmadd_ps(vp6, vt6, vc1);
191 vp7 = _mm256_fmadd_ps(vp7, vt7, vc1);
192 vp8 = _mm256_fmadd_ps(vp8, vt8, vc1);
193 vp9 = _mm256_fmadd_ps(vp9, vt9, vc1);
194 vp10 = _mm256_fmadd_ps(vp10, vt10, vc1);
195 vp11 = _mm256_fmadd_ps(vp11, vt11, vc1);
196
197 // Reconstruct the final f value:
198 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
199 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
200 // = s + (t * s) * p
201 vt0 = _mm256_mul_ps(vt0, vs0);
202 vt1 = _mm256_mul_ps(vt1, vs1);
203 vt2 = _mm256_mul_ps(vt2, vs2);
204 vt3 = _mm256_mul_ps(vt3, vs3);
205 vt4 = _mm256_mul_ps(vt4, vs4);
206 vt5 = _mm256_mul_ps(vt5, vs5);
207 vt6 = _mm256_mul_ps(vt6, vs6);
208 vt7 = _mm256_mul_ps(vt7, vs7);
209 vt8 = _mm256_mul_ps(vt8, vs8);
210 vt9 = _mm256_mul_ps(vt9, vs9);
211 vt10 = _mm256_mul_ps(vt10, vs10);
212 vt11 = _mm256_mul_ps(vt11, vs11);
213
214 __m256 vf0 = _mm256_fmadd_ps(vt0, vp0, vs0);
215 __m256 vf1 = _mm256_fmadd_ps(vt1, vp1, vs1);
216 __m256 vf2 = _mm256_fmadd_ps(vt2, vp2, vs2);
217 __m256 vf3 = _mm256_fmadd_ps(vt3, vp3, vs3);
218 __m256 vf4 = _mm256_fmadd_ps(vt4, vp4, vs4);
219 __m256 vf5 = _mm256_fmadd_ps(vt5, vp5, vs5);
220 __m256 vf6 = _mm256_fmadd_ps(vt6, vp6, vs6);
221 __m256 vf7 = _mm256_fmadd_ps(vt7, vp7, vs7);
222 __m256 vf8 = _mm256_fmadd_ps(vt8, vp8, vs8);
223 __m256 vf9 = _mm256_fmadd_ps(vt9, vp9, vs9);
224 __m256 vf10 = _mm256_fmadd_ps(vt10, vp10, vs10);
225 __m256 vf11 = _mm256_fmadd_ps(vt11, vp11, vs11);
226
227 // For inputs below zero cutoff, replace output with +0.0f.
228 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
229 vf0 = _mm256_andnot_ps(_mm256_cmp_ps(vx0, vdenorm_cutoff, _CMP_LT_OS), vf0);
230 vf1 = _mm256_andnot_ps(_mm256_cmp_ps(vx1, vdenorm_cutoff, _CMP_LT_OS), vf1);
231 vf2 = _mm256_andnot_ps(_mm256_cmp_ps(vx2, vdenorm_cutoff, _CMP_LT_OS), vf2);
232 vf3 = _mm256_andnot_ps(_mm256_cmp_ps(vx3, vdenorm_cutoff, _CMP_LT_OS), vf3);
233 vf4 = _mm256_andnot_ps(_mm256_cmp_ps(vx4, vdenorm_cutoff, _CMP_LT_OS), vf4);
234 vf5 = _mm256_andnot_ps(_mm256_cmp_ps(vx5, vdenorm_cutoff, _CMP_LT_OS), vf5);
235 vf6 = _mm256_andnot_ps(_mm256_cmp_ps(vx6, vdenorm_cutoff, _CMP_LT_OS), vf6);
236 vf7 = _mm256_andnot_ps(_mm256_cmp_ps(vx7, vdenorm_cutoff, _CMP_LT_OS), vf7);
237 vf8 = _mm256_andnot_ps(_mm256_cmp_ps(vx8, vdenorm_cutoff, _CMP_LT_OS), vf8);
238 vf9 = _mm256_andnot_ps(_mm256_cmp_ps(vx9, vdenorm_cutoff, _CMP_LT_OS), vf9);
239 vf10 = _mm256_andnot_ps(_mm256_cmp_ps(vx10, vdenorm_cutoff, _CMP_LT_OS), vf10);
240 vf11 = _mm256_andnot_ps(_mm256_cmp_ps(vx11, vdenorm_cutoff, _CMP_LT_OS), vf11);
241
242 // Accumulate computed exponents.
243 vacc0 = _mm256_add_ps(vacc0, vf0);
244 vacc0 = _mm256_add_ps(vacc0, vf1);
245 vacc0 = _mm256_add_ps(vacc0, vf2);
246 vacc0 = _mm256_add_ps(vacc0, vf3);
247 vacc0 = _mm256_add_ps(vacc0, vf4);
248 vacc0 = _mm256_add_ps(vacc0, vf5);
249 vacc0 = _mm256_add_ps(vacc0, vf6);
250 vacc0 = _mm256_add_ps(vacc0, vf7);
251 vacc0 = _mm256_add_ps(vacc0, vf8);
252 vacc0 = _mm256_add_ps(vacc0, vf9);
253 vacc0 = _mm256_add_ps(vacc0, vf10);
254 vacc0 = _mm256_add_ps(vacc0, vf11);
255 }
256
257 __m256 vacc = vacc0;
258 for (; elements >= 8 * sizeof(float); elements -= 8 * sizeof(float)) {
259 // Load 8 inputs at a time.
260 const __m256 vi = _mm256_loadu_ps(input);
261 input += 8;
262
263 // Subtract maximum input x := i - i_max. This implies x <= 0.
264 const __m256 vx = _mm256_sub_ps(vi, vi_max);
265
266 // Compute reduced argument elements := round(x / log(2)).
267 __m256 vn = _mm256_fmadd_ps(vx, vlog2e, vmagic_bias);
268
269 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
270 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
271 const __m256 vs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn), 23));
272
273 // Subtract the large number back to get final elements := round(x / log(2)).
274 vn = _mm256_sub_ps(vn, vmagic_bias);
275
276 // Compute reduced argument t := x - elements * log(2).
277 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
278 __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2_hi, vx);
279 vt = _mm256_fmadd_ps(vn, vminus_ln2_lo, vt);
280
281 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
282 __m256 vp = _mm256_fmadd_ps(vc5, vt, vc4);
283 vp = _mm256_fmadd_ps(vp, vt, vc3);
284 vp = _mm256_fmadd_ps(vp, vt, vc2);
285 vp = _mm256_fmadd_ps(vp, vt, vc1);
286
287 // Reconstruct the final f value:
288 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
289 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
290 // = s + (t * s) * p
291 vt = _mm256_mul_ps(vt, vs);
292 __m256 vf = _mm256_fmadd_ps(vt, vp, vs);
293
294 // For inputs below zero cutoff, replace output with +0.0f.
295 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
296 vf = _mm256_andnot_ps(_mm256_cmp_ps(vx, vdenorm_cutoff, _CMP_LT_OS), vf);
297
298 // Accumulate computed exponents.
299 vacc = _mm256_add_ps(vacc, vf);
300 }
301 if (elements != 0) {
302 assert(elements >= 1 * sizeof(float));
303 assert(elements <= 7 * sizeof(float));
304 const __m256i vmask = _mm256_loadu_si256((const __m256i*) ((uintptr_t) &mask_table[7] - elements));
305
306 // Load up to 7 inputs at a time.
307 const __m256 vi = _mm256_maskload_ps(input, vmask);
308
309 // Subtract maximum input x := i - i_max. This implies x <= 0.
310 const __m256 vx = _mm256_sub_ps(vi, vi_max);
311
312 // Compute reduced argument elements := round(x / log(2)).
313 __m256 vn = _mm256_fmadd_ps(vx, vlog2e, vmagic_bias);
314
315 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
316 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
317 const __m256 vs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn), 23));
318
319 // Subtract the large number back to get final elements := round(x / log(2)).
320 vn = _mm256_sub_ps(vn, vmagic_bias);
321
322 // Compute reduced argument t := x - elements * log(2).
323 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
324 __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2_hi, vx);
325 vt = _mm256_fmadd_ps(vn, vminus_ln2_lo, vt);
326
327 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
328 __m256 vp = _mm256_fmadd_ps(vc5, vt, vc4);
329 vp = _mm256_fmadd_ps(vp, vt, vc3);
330 vp = _mm256_fmadd_ps(vp, vt, vc2);
331 vp = _mm256_fmadd_ps(vp, vt, vc1);
332
333 // Reconstruct the final f value:
334 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
335 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
336 // = s + (t * s) * p
337 vt = _mm256_mul_ps(vt, vs);
338 __m256 vf = _mm256_fmadd_ps(vt, vp, vs);
339
340 // For inputs below zero cutoff, replace output with +0.0f.
341 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
342 vf = _mm256_andnot_ps(_mm256_cmp_ps(vx, vdenorm_cutoff, _CMP_LT_OS), vf);
343
344 // Accumulate computed exponents. And addend with mask to leave unmasked 32-bit lanes unchanged.
345 vacc = _mm256_add_ps(vacc, _mm256_and_ps(vf, _mm256_castsi256_ps(vmask)));
346 }
347 // Reduce 8 elements in the SIMD register
348 __m128 vacc_lo = _mm_add_ps(_mm256_castps256_ps128(vacc), _mm256_extractf128_ps(vacc, 1));
349 vacc_lo = _mm_add_ps(vacc_lo, _mm_movehl_ps(vacc_lo, vacc_lo));
350 vacc_lo = _mm_add_ss(vacc_lo, _mm_movehdup_ps(vacc_lo));
351 _mm_store_ss(sum, vacc_lo);
352 _mm256_zeroupper();
353 }
354