xref: /aosp_15_r20/external/XNNPACK/src/f32-raddextexp/gen/avx2-p5-x80.c (revision 4bdc94577ba0e567308109d787f7fec7b531ce36)
1 // Auto-generated file. Do not edit!
2 //   Template: src/f32-raddextexp/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 #include <math.h>
12 
13 #include <immintrin.h>
14 
15 #include <xnnpack/raddextexp.h>
16 
17 
18 static const int32_t mask_table[14] = {-1, -1, -1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 0, 0};
19 
xnn_f32_raddextexp_ukernel__avx2_p5_x80(size_t elements,const float * x,float * sum)20 void xnn_f32_raddextexp_ukernel__avx2_p5_x80(
21     size_t elements,
22     const float* x,
23     float* sum)
24 {
25   assert(elements % sizeof(float) == 0);
26 
27   const __m256 vlog2e = _mm256_set1_ps(0x1.715476p+0f);
28   const __m256 vminus_ln2_hi = _mm256_set1_ps(-0x1.62E43p-1f);
29   const __m256 vminus_ln2_lo = _mm256_set1_ps(0x1.05C61p-29f);
30 
31   // The smallest elements such that 2**elements is considered non-negligible.
32   // For smaller elements, 2**elements is replaced with zero.
33   const __m256 vmin_exponent = _mm256_set1_ps(-127.0f);
34   const __m256 vmagic_bias = _mm256_set1_ps(0x1.8000FEp23f);
35   const __m256 vminus_inf = _mm256_set1_ps(-INFINITY);
36 
37   const __m256 vc0 = _mm256_set1_ps(1.0f);
38   const __m256 vc1 = _mm256_set1_ps(0x1.FFFFF6p-1f);
39   const __m256 vc2 = _mm256_set1_ps(0x1.FFFDC6p-2f);
40   const __m256 vc3 = _mm256_set1_ps(0x1.555A80p-3f);
41   const __m256 vc4 = _mm256_set1_ps(0x1.573A1Ap-5f);
42   const __m256 vc5 = _mm256_set1_ps(0x1.0F9F9Cp-7f);
43 
44   __m256 vaccv0 = _mm256_setzero_ps();
45   __m256 vacce0 = vminus_inf;
46   for (; elements >= 80 * sizeof(float); elements -= 80 * sizeof(float)) {
47     // Load 80 (10x8) inputs at a time.
48     const __m256 vx0 = _mm256_loadu_ps(x);
49     const __m256 vx1 = _mm256_loadu_ps(x + 8);
50     const __m256 vx2 = _mm256_loadu_ps(x + 16);
51     const __m256 vx3 = _mm256_loadu_ps(x + 24);
52     const __m256 vx4 = _mm256_loadu_ps(x + 32);
53     const __m256 vx5 = _mm256_loadu_ps(x + 40);
54     const __m256 vx6 = _mm256_loadu_ps(x + 48);
55     const __m256 vx7 = _mm256_loadu_ps(x + 56);
56     const __m256 vx8 = _mm256_loadu_ps(x + 64);
57     const __m256 vx9 = _mm256_loadu_ps(x + 72);
58     x += 80;
59 
60     // Compute reduced argument elements := round(x / log(2)).
61     const __m256 vn0 = _mm256_round_ps(_mm256_mul_ps(vx0, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
62     const __m256 vn1 = _mm256_round_ps(_mm256_mul_ps(vx1, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
63     const __m256 vn2 = _mm256_round_ps(_mm256_mul_ps(vx2, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
64     const __m256 vn3 = _mm256_round_ps(_mm256_mul_ps(vx3, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
65     const __m256 vn4 = _mm256_round_ps(_mm256_mul_ps(vx4, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
66     const __m256 vn5 = _mm256_round_ps(_mm256_mul_ps(vx5, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
67     const __m256 vn6 = _mm256_round_ps(_mm256_mul_ps(vx6, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
68     const __m256 vn7 = _mm256_round_ps(_mm256_mul_ps(vx7, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
69     const __m256 vn8 = _mm256_round_ps(_mm256_mul_ps(vx8, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
70     const __m256 vn9 = _mm256_round_ps(_mm256_mul_ps(vx9, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
71 
72     // Compute reduced argument t := x - elements * log(2).
73     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
74     __m256 vt0 = _mm256_fmadd_ps(vn0, vminus_ln2_hi, vx0);
75     __m256 vt1 = _mm256_fmadd_ps(vn1, vminus_ln2_hi, vx1);
76     __m256 vt2 = _mm256_fmadd_ps(vn2, vminus_ln2_hi, vx2);
77     __m256 vt3 = _mm256_fmadd_ps(vn3, vminus_ln2_hi, vx3);
78     __m256 vt4 = _mm256_fmadd_ps(vn4, vminus_ln2_hi, vx4);
79     __m256 vt5 = _mm256_fmadd_ps(vn5, vminus_ln2_hi, vx5);
80     __m256 vt6 = _mm256_fmadd_ps(vn6, vminus_ln2_hi, vx6);
81     __m256 vt7 = _mm256_fmadd_ps(vn7, vminus_ln2_hi, vx7);
82     __m256 vt8 = _mm256_fmadd_ps(vn8, vminus_ln2_hi, vx8);
83     __m256 vt9 = _mm256_fmadd_ps(vn9, vminus_ln2_hi, vx9);
84 
85     vt0 = _mm256_fmadd_ps(vn0, vminus_ln2_lo, vt0);
86     vt1 = _mm256_fmadd_ps(vn1, vminus_ln2_lo, vt1);
87     vt2 = _mm256_fmadd_ps(vn2, vminus_ln2_lo, vt2);
88     vt3 = _mm256_fmadd_ps(vn3, vminus_ln2_lo, vt3);
89     vt4 = _mm256_fmadd_ps(vn4, vminus_ln2_lo, vt4);
90     vt5 = _mm256_fmadd_ps(vn5, vminus_ln2_lo, vt5);
91     vt6 = _mm256_fmadd_ps(vn6, vminus_ln2_lo, vt6);
92     vt7 = _mm256_fmadd_ps(vn7, vminus_ln2_lo, vt7);
93     vt8 = _mm256_fmadd_ps(vn8, vminus_ln2_lo, vt8);
94     vt9 = _mm256_fmadd_ps(vn9, vminus_ln2_lo, vt9);
95 
96     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
97     __m256 vp0 = _mm256_fmadd_ps(vc5, vt0, vc4);
98     __m256 vp1 = _mm256_fmadd_ps(vc5, vt1, vc4);
99     __m256 vp2 = _mm256_fmadd_ps(vc5, vt2, vc4);
100     __m256 vp3 = _mm256_fmadd_ps(vc5, vt3, vc4);
101     __m256 vp4 = _mm256_fmadd_ps(vc5, vt4, vc4);
102     __m256 vp5 = _mm256_fmadd_ps(vc5, vt5, vc4);
103     __m256 vp6 = _mm256_fmadd_ps(vc5, vt6, vc4);
104     __m256 vp7 = _mm256_fmadd_ps(vc5, vt7, vc4);
105     __m256 vp8 = _mm256_fmadd_ps(vc5, vt8, vc4);
106     __m256 vp9 = _mm256_fmadd_ps(vc5, vt9, vc4);
107 
108     vp0 = _mm256_fmadd_ps(vp0, vt0, vc3);
109     vp1 = _mm256_fmadd_ps(vp1, vt1, vc3);
110     vp2 = _mm256_fmadd_ps(vp2, vt2, vc3);
111     vp3 = _mm256_fmadd_ps(vp3, vt3, vc3);
112     vp4 = _mm256_fmadd_ps(vp4, vt4, vc3);
113     vp5 = _mm256_fmadd_ps(vp5, vt5, vc3);
114     vp6 = _mm256_fmadd_ps(vp6, vt6, vc3);
115     vp7 = _mm256_fmadd_ps(vp7, vt7, vc3);
116     vp8 = _mm256_fmadd_ps(vp8, vt8, vc3);
117     vp9 = _mm256_fmadd_ps(vp9, vt9, vc3);
118 
119     vp0 = _mm256_fmadd_ps(vp0, vt0, vc2);
120     vp1 = _mm256_fmadd_ps(vp1, vt1, vc2);
121     vp2 = _mm256_fmadd_ps(vp2, vt2, vc2);
122     vp3 = _mm256_fmadd_ps(vp3, vt3, vc2);
123     vp4 = _mm256_fmadd_ps(vp4, vt4, vc2);
124     vp5 = _mm256_fmadd_ps(vp5, vt5, vc2);
125     vp6 = _mm256_fmadd_ps(vp6, vt6, vc2);
126     vp7 = _mm256_fmadd_ps(vp7, vt7, vc2);
127     vp8 = _mm256_fmadd_ps(vp8, vt8, vc2);
128     vp9 = _mm256_fmadd_ps(vp9, vt9, vc2);
129 
130     vp0 = _mm256_fmadd_ps(vp0, vt0, vc1);
131     vp1 = _mm256_fmadd_ps(vp1, vt1, vc1);
132     vp2 = _mm256_fmadd_ps(vp2, vt2, vc1);
133     vp3 = _mm256_fmadd_ps(vp3, vt3, vc1);
134     vp4 = _mm256_fmadd_ps(vp4, vt4, vc1);
135     vp5 = _mm256_fmadd_ps(vp5, vt5, vc1);
136     vp6 = _mm256_fmadd_ps(vp6, vt6, vc1);
137     vp7 = _mm256_fmadd_ps(vp7, vt7, vc1);
138     vp8 = _mm256_fmadd_ps(vp8, vt8, vc1);
139     vp9 = _mm256_fmadd_ps(vp9, vt9, vc1);
140 
141     vp0 = _mm256_fmadd_ps(vp0, vt0, vc0);
142     vp1 = _mm256_fmadd_ps(vp1, vt1, vc0);
143     vp2 = _mm256_fmadd_ps(vp2, vt2, vc0);
144     vp3 = _mm256_fmadd_ps(vp3, vt3, vc0);
145     vp4 = _mm256_fmadd_ps(vp4, vt4, vc0);
146     vp5 = _mm256_fmadd_ps(vp5, vt5, vc0);
147     vp6 = _mm256_fmadd_ps(vp6, vt6, vc0);
148     vp7 = _mm256_fmadd_ps(vp7, vt7, vc0);
149     vp8 = _mm256_fmadd_ps(vp8, vt8, vc0);
150     vp9 = _mm256_fmadd_ps(vp9, vt9, vc0);
151 
152     // Accumulate "extended" floating-point numbers in ("mantissa", "exponent") representation where
153     //  - vnX is "exponent"
154     //  - vpX is "mantissa"
155     //
156     // exp2(ae) * av + exp2(be) * bv =
157     //   = exp2(max(ae, be)) * exp2(ae - max(ae, be)) * av + exp2(max(ae, be)) * exp2(be - max(ae, be)) * bv
158     //   = exp2(max_e) * (exp2(ae - max_e) * av + exp2(be - max_e) * bv)
159     //   = exp2(max_e) * (exp2(delta_ae) * av + exp2(delta_be) * bv)
160     //
161     // For computational efficiency we may add several "extended" floating-point numbers at a time.
162     __m256 vmax_e0 = _mm256_max_ps(vacce0, vn0);
163     vmax_e0 = _mm256_max_ps(vmax_e0, vn1);
164     vmax_e0 = _mm256_max_ps(vmax_e0, vn2);
165     vmax_e0 = _mm256_max_ps(vmax_e0, vn3);
166     vmax_e0 = _mm256_max_ps(vmax_e0, vn4);
167     vmax_e0 = _mm256_max_ps(vmax_e0, vn5);
168     vmax_e0 = _mm256_max_ps(vmax_e0, vn6);
169     vmax_e0 = _mm256_max_ps(vmax_e0, vn7);
170     vmax_e0 = _mm256_max_ps(vmax_e0, vn8);
171     vmax_e0 = _mm256_max_ps(vmax_e0, vn9);
172 
173     // For computational efficiency, replace exp2(delta_e) with 0.0f when delta_e <= -127.0.
174     // This replacement is done in two steps:
175     // 1. Clamp minimum delta_e at -127.0.
176     // 2. Map delta_e to scale factor 0.0 when delta_e == -127.0
177     const __m256 vdelta_acce0 = _mm256_max_ps(_mm256_sub_ps(vacce0, vmax_e0), vmin_exponent);
178     const __m256 vdelta_e0 = _mm256_max_ps(_mm256_sub_ps(vn0, vmax_e0), vmin_exponent);
179     const __m256 vdelta_e1 = _mm256_max_ps(_mm256_sub_ps(vn1, vmax_e0), vmin_exponent);
180     const __m256 vdelta_e2 = _mm256_max_ps(_mm256_sub_ps(vn2, vmax_e0), vmin_exponent);
181     const __m256 vdelta_e3 = _mm256_max_ps(_mm256_sub_ps(vn3, vmax_e0), vmin_exponent);
182     const __m256 vdelta_e4 = _mm256_max_ps(_mm256_sub_ps(vn4, vmax_e0), vmin_exponent);
183     const __m256 vdelta_e5 = _mm256_max_ps(_mm256_sub_ps(vn5, vmax_e0), vmin_exponent);
184     const __m256 vdelta_e6 = _mm256_max_ps(_mm256_sub_ps(vn6, vmax_e0), vmin_exponent);
185     const __m256 vdelta_e7 = _mm256_max_ps(_mm256_sub_ps(vn7, vmax_e0), vmin_exponent);
186     const __m256 vdelta_e8 = _mm256_max_ps(_mm256_sub_ps(vn8, vmax_e0), vmin_exponent);
187     const __m256 vdelta_e9 = _mm256_max_ps(_mm256_sub_ps(vn9, vmax_e0), vmin_exponent);
188 
189     // Convert delta-exponents into scale factors:
190     // - s = exp2(delta_e) when delta_e > -127.0
191     // - s = 0.0 when delta_e <= -127.0
192     //
193     // Note: delta-exponents can not exceed 0.0, thus scale factors can not exceed 1.0.
194     const __m256 vaccs0 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_acce0, vmagic_bias)), 23));
195     const __m256 vs0 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e0, vmagic_bias)), 23));
196     const __m256 vs1 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e1, vmagic_bias)), 23));
197     const __m256 vs2 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e2, vmagic_bias)), 23));
198     const __m256 vs3 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e3, vmagic_bias)), 23));
199     const __m256 vs4 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e4, vmagic_bias)), 23));
200     const __m256 vs5 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e5, vmagic_bias)), 23));
201     const __m256 vs6 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e6, vmagic_bias)), 23));
202     const __m256 vs7 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e7, vmagic_bias)), 23));
203     const __m256 vs8 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e8, vmagic_bias)), 23));
204     const __m256 vs9 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e9, vmagic_bias)), 23));
205 
206     // Update accumulated "mantissa" and "exponent" values
207     vaccv0 = _mm256_mul_ps(vaccv0, vaccs0);
208     vaccv0 = _mm256_fmadd_ps(vp0, vs0, vaccv0);
209     vaccv0 = _mm256_fmadd_ps(vp1, vs1, vaccv0);
210     vaccv0 = _mm256_fmadd_ps(vp2, vs2, vaccv0);
211     vaccv0 = _mm256_fmadd_ps(vp3, vs3, vaccv0);
212     vaccv0 = _mm256_fmadd_ps(vp4, vs4, vaccv0);
213     vaccv0 = _mm256_fmadd_ps(vp5, vs5, vaccv0);
214     vaccv0 = _mm256_fmadd_ps(vp6, vs6, vaccv0);
215     vaccv0 = _mm256_fmadd_ps(vp7, vs7, vaccv0);
216     vaccv0 = _mm256_fmadd_ps(vp8, vs8, vaccv0);
217     vaccv0 = _mm256_fmadd_ps(vp9, vs9, vaccv0);
218 
219     vacce0 = vmax_e0;
220   }
221 
222   // Reduce partial sums of "extended" floating-point numbers into a single "extended" SIMD vector of sums.
223   __m256 vaccv = vaccv0;
224   __m256 vacce = vacce0;
225 
226   for (; elements >= 8 * sizeof(float); elements -= 8 * sizeof(float)) {
227     // Load 8 inputs at a time.
228     const __m256 vx = _mm256_loadu_ps(x);
229     x += 8;
230 
231     // Compute reduced argument elements := round(x / log(2)).
232     const __m256 vn = _mm256_round_ps(_mm256_mul_ps(vx, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
233 
234     // Compute reduced argument t := x - elements * log(2).
235     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
236     __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2_hi, vx);
237     vt = _mm256_fmadd_ps(vn, vminus_ln2_lo, vt);
238 
239     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
240     __m256 vp = _mm256_fmadd_ps(vc5, vt, vc4);
241     vp = _mm256_fmadd_ps(vp, vt, vc3);
242     vp = _mm256_fmadd_ps(vp, vt, vc2);
243     vp = _mm256_fmadd_ps(vp, vt, vc1);
244     vp = _mm256_fmadd_ps(vp, vt, vc0);
245 
246     // Accumulate "extended" floating-point numbers in ("mantissa", "exponent") representation.
247     const __m256 vmax_e = _mm256_max_ps(vacce, vn);
248 
249     // For computational efficiency, clamp minimum exp2(delta_e) at -127.0. It will be mapped to 0.0 scale factor later.
250     const __m256 vdelta_acce = _mm256_max_ps(_mm256_sub_ps(vacce, vmax_e), vmin_exponent);
251     const __m256 vdelta_e = _mm256_max_ps(_mm256_sub_ps(vn, vmax_e), vmin_exponent);
252 
253     // Convert exponents into scale factors.
254     const __m256 vaccs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_acce, vmagic_bias)), 23));
255     const __m256 vs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e, vmagic_bias)), 23));
256 
257     // Update accumulated "mantissa" and "exponent" values.
258     vaccv = _mm256_mul_ps(vaccv, vaccs);
259     vaccv = _mm256_fmadd_ps(vp, vs, vaccv);
260 
261     vacce = vmax_e;
262   }
263   if XNN_UNLIKELY(elements != 0) {
264     assert(elements >= 1 * sizeof(float));
265     assert(elements <= 7 * sizeof(float));
266     const __m256i vmask = _mm256_loadu_si256((const __m256i*) ((uintptr_t) &mask_table[7] - elements));
267 
268     // Load up to 7 inputs at a time.
269     const __m256 vx = _mm256_maskload_ps(x, vmask);
270 
271     // Compute reduced argument elements := round(x / log(2)).
272     __m256 vn = _mm256_round_ps(_mm256_mul_ps(vx, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
273 
274     // Compute reduced argument t := x - elements * log(2).
275     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
276     __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2_hi, vx);
277     vt = _mm256_fmadd_ps(vn, vminus_ln2_lo, vt);
278 
279     // Correct reduced argument elements for masked out elements.
280     vn = _mm256_blendv_ps(vacce, vn, _mm256_castsi256_ps(vmask));
281 
282     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
283     __m256 vp = _mm256_fmadd_ps(vc5, vt, vc4);
284     vp = _mm256_fmadd_ps(vp, vt, vc3);
285     vp = _mm256_fmadd_ps(vp, vt, vc2);
286     vp = _mm256_fmadd_ps(vp, vt, vc1);
287     vp = _mm256_fmadd_ps(vp, vt, vc0);
288     vp = _mm256_and_ps(vp, _mm256_castsi256_ps(vmask));
289 
290     // Accumulate "extended" floating-point numbers in ("mantissa", "exponent") representation.
291     const __m256 vmax_e = _mm256_max_ps(vacce, vn);
292 
293     // For computational efficiency, clamp minimum exp2(delta_e) at -127.0. It will be mapped to 0.0 scale factor later.
294     const __m256 vdelta_e = _mm256_max_ps(_mm256_sub_ps(vn, vmax_e), vmin_exponent);
295     const __m256 vdelta_acce = _mm256_max_ps(_mm256_sub_ps(vacce, vmax_e), vmin_exponent);
296 
297     // Convert exponents into scale factors.
298     const __m256 vs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_e, vmagic_bias)), 23));
299     const __m256 vaccs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_acce, vmagic_bias)), 23));
300 
301     // Update accumulated "mantissa" and "exponent" values.
302     vaccv = _mm256_mul_ps(vaccv, vaccs);
303     vaccv = _mm256_fmadd_ps(vp, vs, vaccv);
304 
305     vacce = vmax_e;
306   }
307 
308   // Reduce partial sums of "extended" floating-point numbers into a single "extended" floating-point sum.
309   __m256 vmax_acce = _mm256_max_ps(vacce, _mm256_permute2f128_ps(vacce, vacce, 1));
310   vmax_acce = _mm256_max_ps(vmax_acce, _mm256_shuffle_ps(vmax_acce, vmax_acce, _MM_SHUFFLE(1, 0, 3, 2)));
311   vmax_acce = _mm256_max_ps(vmax_acce, _mm256_shuffle_ps(vmax_acce, vmax_acce, _MM_SHUFFLE(2, 3, 0, 1)));
312   const __m256 vdelta_acce = _mm256_max_ps(_mm256_sub_ps(vacce, vmax_acce), vmin_exponent);
313   const __m256 vaccs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(_mm256_add_ps(vdelta_acce, vmagic_bias)), 23));
314 
315   vaccv = _mm256_mul_ps(vaccv, vaccs);
316   __m128 vaccv_sum = _mm_add_ps(_mm256_castps256_ps128(vaccv), _mm256_extractf128_ps(vaccv, 1));
317   vaccv_sum = _mm_add_ps(vaccv_sum, _mm_movehl_ps(vaccv_sum, vaccv_sum));
318   vaccv_sum = _mm_add_ss(vaccv_sum, _mm_movehdup_ps(vaccv_sum));
319 
320   _mm_store_ss(&sum[0], vaccv_sum);
321   _mm_store_ss(&sum[1], _mm256_castps256_ps128(vmax_acce));
322 
323   _mm256_zeroupper();
324 }
325