xref: /aosp_15_r20/external/XNNPACK/src/f32-raddextexp/gen/avx512f-p5-scalef-x160-acc2.c (revision 4bdc94577ba0e567308109d787f7fec7b531ce36)
1 // Auto-generated file. Do not edit!
2 //   Template: src/f32-raddextexp/avx512f-p5-scalef.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/common.h>
16 #include <xnnpack/intrinsics-polyfill.h>
17 #include <xnnpack/raddextexp.h>
18 
19 
xnn_f32_raddextexp_ukernel__avx512f_p5_scalef_x160_acc2(size_t elements,const float * x,float * sum)20 void xnn_f32_raddextexp_ukernel__avx512f_p5_scalef_x160_acc2(
21     size_t elements,
22     const float* x,
23     float* sum)
24 {
25   assert(elements % sizeof(float) == 0);
26 
27   const __m512 vlog2e = _mm512_set1_ps(0x1.715476p+0f);
28   const __m512 vminus_ln2_hi = _mm512_set1_ps(-0x1.62E43p-1f);
29   const __m512 vminus_ln2_lo = _mm512_set1_ps(0x1.05C61p-29f);
30 
31   const __m512 vc0 = _mm512_set1_ps(1.0f);
32   const __m512 vc1 = _mm512_set1_ps(0x1.FFFFF6p-1f);
33   const __m512 vc2 = _mm512_set1_ps(0x1.FFFDC6p-2f);
34   const __m512 vc3 = _mm512_set1_ps(0x1.555A80p-3f);
35   const __m512 vc4 = _mm512_set1_ps(0x1.573A1Ap-5f);
36   const __m512 vc5 = _mm512_set1_ps(0x1.0F9F9Cp-7f);
37 
38   const __m512 vminus_inf = _mm512_set1_ps(-INFINITY);
39 
40   __m512 vaccv0 = _mm512_setzero_ps();
41   __m512 vaccv1 = _mm512_setzero_ps();
42   __m512 vacce0 = vminus_inf;
43   __m512 vacce1 = vminus_inf;
44   for (; elements >= 160 * sizeof(float); elements -= 160 * sizeof(float)) {
45     // Load 160 (10x16) inputs at a time.
46     const __m512 vx0 = _mm512_loadu_ps(x);
47     const __m512 vx1 = _mm512_loadu_ps(x + 16);
48     const __m512 vx2 = _mm512_loadu_ps(x + 32);
49     const __m512 vx3 = _mm512_loadu_ps(x + 48);
50     const __m512 vx4 = _mm512_loadu_ps(x + 64);
51     const __m512 vx5 = _mm512_loadu_ps(x + 80);
52     const __m512 vx6 = _mm512_loadu_ps(x + 96);
53     const __m512 vx7 = _mm512_loadu_ps(x + 112);
54     const __m512 vx8 = _mm512_loadu_ps(x + 128);
55     const __m512 vx9 = _mm512_loadu_ps(x + 144);
56     x += 160;
57 
58     // Compute reduced argument elements := round(x / log(2)).
59     const __m512 vn0 = _mm512_roundscale_ps(_mm512_mul_ps(vx0, vlog2e), 0);
60     const __m512 vn1 = _mm512_roundscale_ps(_mm512_mul_ps(vx1, vlog2e), 0);
61     const __m512 vn2 = _mm512_roundscale_ps(_mm512_mul_ps(vx2, vlog2e), 0);
62     const __m512 vn3 = _mm512_roundscale_ps(_mm512_mul_ps(vx3, vlog2e), 0);
63     const __m512 vn4 = _mm512_roundscale_ps(_mm512_mul_ps(vx4, vlog2e), 0);
64     const __m512 vn5 = _mm512_roundscale_ps(_mm512_mul_ps(vx5, vlog2e), 0);
65     const __m512 vn6 = _mm512_roundscale_ps(_mm512_mul_ps(vx6, vlog2e), 0);
66     const __m512 vn7 = _mm512_roundscale_ps(_mm512_mul_ps(vx7, vlog2e), 0);
67     const __m512 vn8 = _mm512_roundscale_ps(_mm512_mul_ps(vx8, vlog2e), 0);
68     const __m512 vn9 = _mm512_roundscale_ps(_mm512_mul_ps(vx9, vlog2e), 0);
69 
70     // Compute reduced argument t := x - elements * log(2).
71     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
72     __m512 vt0 = _mm512_fmadd_ps(vn0, vminus_ln2_hi, vx0);
73     __m512 vt1 = _mm512_fmadd_ps(vn1, vminus_ln2_hi, vx1);
74     __m512 vt2 = _mm512_fmadd_ps(vn2, vminus_ln2_hi, vx2);
75     __m512 vt3 = _mm512_fmadd_ps(vn3, vminus_ln2_hi, vx3);
76     __m512 vt4 = _mm512_fmadd_ps(vn4, vminus_ln2_hi, vx4);
77     __m512 vt5 = _mm512_fmadd_ps(vn5, vminus_ln2_hi, vx5);
78     __m512 vt6 = _mm512_fmadd_ps(vn6, vminus_ln2_hi, vx6);
79     __m512 vt7 = _mm512_fmadd_ps(vn7, vminus_ln2_hi, vx7);
80     __m512 vt8 = _mm512_fmadd_ps(vn8, vminus_ln2_hi, vx8);
81     __m512 vt9 = _mm512_fmadd_ps(vn9, vminus_ln2_hi, vx9);
82 
83     vt0 = _mm512_fmadd_ps(vn0, vminus_ln2_lo, vt0);
84     vt1 = _mm512_fmadd_ps(vn1, vminus_ln2_lo, vt1);
85     vt2 = _mm512_fmadd_ps(vn2, vminus_ln2_lo, vt2);
86     vt3 = _mm512_fmadd_ps(vn3, vminus_ln2_lo, vt3);
87     vt4 = _mm512_fmadd_ps(vn4, vminus_ln2_lo, vt4);
88     vt5 = _mm512_fmadd_ps(vn5, vminus_ln2_lo, vt5);
89     vt6 = _mm512_fmadd_ps(vn6, vminus_ln2_lo, vt6);
90     vt7 = _mm512_fmadd_ps(vn7, vminus_ln2_lo, vt7);
91     vt8 = _mm512_fmadd_ps(vn8, vminus_ln2_lo, vt8);
92     vt9 = _mm512_fmadd_ps(vn9, vminus_ln2_lo, vt9);
93 
94     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
95     __m512 vp0 = _mm512_fmadd_ps(vc5, vt0, vc4);
96     __m512 vp1 = _mm512_fmadd_ps(vc5, vt1, vc4);
97     __m512 vp2 = _mm512_fmadd_ps(vc5, vt2, vc4);
98     __m512 vp3 = _mm512_fmadd_ps(vc5, vt3, vc4);
99     __m512 vp4 = _mm512_fmadd_ps(vc5, vt4, vc4);
100     __m512 vp5 = _mm512_fmadd_ps(vc5, vt5, vc4);
101     __m512 vp6 = _mm512_fmadd_ps(vc5, vt6, vc4);
102     __m512 vp7 = _mm512_fmadd_ps(vc5, vt7, vc4);
103     __m512 vp8 = _mm512_fmadd_ps(vc5, vt8, vc4);
104     __m512 vp9 = _mm512_fmadd_ps(vc5, vt9, vc4);
105 
106     vp0 = _mm512_fmadd_ps(vp0, vt0, vc3);
107     vp1 = _mm512_fmadd_ps(vp1, vt1, vc3);
108     vp2 = _mm512_fmadd_ps(vp2, vt2, vc3);
109     vp3 = _mm512_fmadd_ps(vp3, vt3, vc3);
110     vp4 = _mm512_fmadd_ps(vp4, vt4, vc3);
111     vp5 = _mm512_fmadd_ps(vp5, vt5, vc3);
112     vp6 = _mm512_fmadd_ps(vp6, vt6, vc3);
113     vp7 = _mm512_fmadd_ps(vp7, vt7, vc3);
114     vp8 = _mm512_fmadd_ps(vp8, vt8, vc3);
115     vp9 = _mm512_fmadd_ps(vp9, vt9, vc3);
116 
117     vp0 = _mm512_fmadd_ps(vp0, vt0, vc2);
118     vp1 = _mm512_fmadd_ps(vp1, vt1, vc2);
119     vp2 = _mm512_fmadd_ps(vp2, vt2, vc2);
120     vp3 = _mm512_fmadd_ps(vp3, vt3, vc2);
121     vp4 = _mm512_fmadd_ps(vp4, vt4, vc2);
122     vp5 = _mm512_fmadd_ps(vp5, vt5, vc2);
123     vp6 = _mm512_fmadd_ps(vp6, vt6, vc2);
124     vp7 = _mm512_fmadd_ps(vp7, vt7, vc2);
125     vp8 = _mm512_fmadd_ps(vp8, vt8, vc2);
126     vp9 = _mm512_fmadd_ps(vp9, vt9, vc2);
127 
128     vp0 = _mm512_fmadd_ps(vp0, vt0, vc1);
129     vp1 = _mm512_fmadd_ps(vp1, vt1, vc1);
130     vp2 = _mm512_fmadd_ps(vp2, vt2, vc1);
131     vp3 = _mm512_fmadd_ps(vp3, vt3, vc1);
132     vp4 = _mm512_fmadd_ps(vp4, vt4, vc1);
133     vp5 = _mm512_fmadd_ps(vp5, vt5, vc1);
134     vp6 = _mm512_fmadd_ps(vp6, vt6, vc1);
135     vp7 = _mm512_fmadd_ps(vp7, vt7, vc1);
136     vp8 = _mm512_fmadd_ps(vp8, vt8, vc1);
137     vp9 = _mm512_fmadd_ps(vp9, vt9, vc1);
138 
139     vp0 = _mm512_fmadd_ps(vp0, vt0, vc0);
140     vp1 = _mm512_fmadd_ps(vp1, vt1, vc0);
141     vp2 = _mm512_fmadd_ps(vp2, vt2, vc0);
142     vp3 = _mm512_fmadd_ps(vp3, vt3, vc0);
143     vp4 = _mm512_fmadd_ps(vp4, vt4, vc0);
144     vp5 = _mm512_fmadd_ps(vp5, vt5, vc0);
145     vp6 = _mm512_fmadd_ps(vp6, vt6, vc0);
146     vp7 = _mm512_fmadd_ps(vp7, vt7, vc0);
147     vp8 = _mm512_fmadd_ps(vp8, vt8, vc0);
148     vp9 = _mm512_fmadd_ps(vp9, vt9, vc0);
149 
150     // Accumulate "extended" floating-point numbers in ("mantissa", "exponent") representation where
151     //  - vnX is "exponent"
152     //  - vpX is "mantissa"
153     //
154     // exp2(ae) * av + exp2(be) * bv =
155     //   = exp2(max(ae, be)) * exp2(ae - max(ae, be)) * av + exp2(max(ae, be)) * exp2(be - max(ae, be)) * bv
156     //   = exp2(max_e) * (exp2(ae - max_e) * av + exp2(be - max_e) * bv)
157     //   = exp2(max_e) * (exp2(delta_ae) * av + exp2(delta_be) * bv)
158     //
159     // For computational efficiency we add three "extended" floating-point numbers at a time.
160     __m512 vmax_e0 = _mm512_max_ps(vacce0, vn0);
161     __m512 vmax_e1 = _mm512_max_ps(vacce1, vn1);
162     vmax_e0 = _mm512_max_ps(vmax_e0, vn2);
163     vmax_e1 = _mm512_max_ps(vmax_e1, vn3);
164     vmax_e0 = _mm512_max_ps(vmax_e0, vn4);
165     vmax_e1 = _mm512_max_ps(vmax_e1, vn5);
166     vmax_e0 = _mm512_max_ps(vmax_e0, vn6);
167     vmax_e1 = _mm512_max_ps(vmax_e1, vn7);
168     vmax_e0 = _mm512_max_ps(vmax_e0, vn8);
169     vmax_e1 = _mm512_max_ps(vmax_e1, vn9);
170 
171     const __m512 vdelta_acce0 = _mm512_sub_ps(vacce0, vmax_e0);
172     const __m512 vdelta_acce1 = _mm512_sub_ps(vacce1, vmax_e1);
173     const __m512 vdelta_e0 = _mm512_sub_ps(vn0, vmax_e0);
174     const __m512 vdelta_e1 = _mm512_sub_ps(vn1, vmax_e1);
175     const __m512 vdelta_e2 = _mm512_sub_ps(vn2, vmax_e0);
176     const __m512 vdelta_e3 = _mm512_sub_ps(vn3, vmax_e1);
177     const __m512 vdelta_e4 = _mm512_sub_ps(vn4, vmax_e0);
178     const __m512 vdelta_e5 = _mm512_sub_ps(vn5, vmax_e1);
179     const __m512 vdelta_e6 = _mm512_sub_ps(vn6, vmax_e0);
180     const __m512 vdelta_e7 = _mm512_sub_ps(vn7, vmax_e1);
181     const __m512 vdelta_e8 = _mm512_sub_ps(vn8, vmax_e0);
182     const __m512 vdelta_e9 = _mm512_sub_ps(vn9, vmax_e1);
183 
184     // Update accumulated "mantissa" and "exponent" values
185     vaccv0 = _mm512_scalef_ps(vaccv0, vdelta_acce0);
186     vaccv1 = _mm512_scalef_ps(vaccv1, vdelta_acce1);
187     vaccv0 = _mm512_add_ps(vaccv0, _mm512_scalef_ps(vp0, vdelta_e0));
188     vaccv1 = _mm512_add_ps(vaccv1, _mm512_scalef_ps(vp1, vdelta_e1));
189     vaccv0 = _mm512_add_ps(vaccv0, _mm512_scalef_ps(vp2, vdelta_e2));
190     vaccv1 = _mm512_add_ps(vaccv1, _mm512_scalef_ps(vp3, vdelta_e3));
191     vaccv0 = _mm512_add_ps(vaccv0, _mm512_scalef_ps(vp4, vdelta_e4));
192     vaccv1 = _mm512_add_ps(vaccv1, _mm512_scalef_ps(vp5, vdelta_e5));
193     vaccv0 = _mm512_add_ps(vaccv0, _mm512_scalef_ps(vp6, vdelta_e6));
194     vaccv1 = _mm512_add_ps(vaccv1, _mm512_scalef_ps(vp7, vdelta_e7));
195     vaccv0 = _mm512_add_ps(vaccv0, _mm512_scalef_ps(vp8, vdelta_e8));
196     vaccv1 = _mm512_add_ps(vaccv1, _mm512_scalef_ps(vp9, vdelta_e9));
197 
198     vacce0 = vmax_e0;
199     vacce1 = vmax_e1;
200   }
201 
202   // Reduce partial sums of "extended" floating-point numbers into a single "extended" SIMD vector of sums.
203   const __m512 vmax_acce01 = _mm512_max_ps(vacce0, vacce1);
204 
205   const __m512 vdelta_acce0 = _mm512_sub_ps(vacce0, vmax_acce01);
206   const __m512 vdelta_acce1 = _mm512_sub_ps(vacce1, vmax_acce01);
207 
208   __m512 vaccv = _mm512_scalef_ps(vaccv0, vdelta_acce0);
209   vaccv = _mm512_add_ps(vaccv, _mm512_scalef_ps(vaccv1, vdelta_acce1));
210   __m512 vacce = vmax_acce01;
211 
212   for (; elements >= 16 * sizeof(float); elements -= 16 * sizeof(float)) {
213     // Load 16 inputs at a time.
214     const __m512 vx = _mm512_loadu_ps(x);
215     x += 16;
216 
217     // Compute reduced argument elements := round(x / log(2)).
218     const __m512 vn = _mm512_roundscale_ps(_mm512_mul_ps(vx, vlog2e), 0);
219 
220     // Compute reduced argument t := x - elements * log(2).
221     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
222     __m512 vt = _mm512_fmadd_ps(vn, vminus_ln2_hi, vx);
223     vt = _mm512_fmadd_ps(vn, vminus_ln2_lo, vt);
224 
225     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
226     __m512 vp = _mm512_fmadd_ps(vc5, vt, vc4);
227     vp = _mm512_fmadd_ps(vp, vt, vc3);
228     vp = _mm512_fmadd_ps(vp, vt, vc2);
229     vp = _mm512_fmadd_ps(vp, vt, vc1);
230     vp = _mm512_fmadd_ps(vp, vt, vc0);
231 
232     // Accumulate "extended" floating-point numbers in ("mantissa", "exponent") representation.
233     const __m512 vmax_e = _mm512_max_ps(vacce, vn);
234     const __m512 vdelta_acce = _mm512_sub_ps(vacce, vmax_e);
235     const __m512 vdelta_e = _mm512_sub_ps(vn, vmax_e);
236     vaccv = _mm512_scalef_ps(vaccv, vdelta_acce);
237     vaccv = _mm512_add_ps(vaccv, _mm512_scalef_ps(vp, vdelta_e));
238 
239     vacce = vmax_e;
240   }
241   if XNN_UNLIKELY(elements != 0) {
242     // Prepare mask for valid 32-bit elements (depends on elements).
243     elements >>= 2 /* log2(sizeof(float)) */;
244     const __mmask16 vmask = _cvtu32_mask16((uint16_t) ((uint32_t) (UINT32_C(1) << elements) - UINT32_C(1)));
245 
246     // Load up to 15 inputs at a time.
247     const __m512 vx = _mm512_maskz_loadu_ps(vmask, x);
248 
249     // Compute reduced argument elements := round(x / log(2)).
250     const __m512 vn = _mm512_roundscale_ps(_mm512_mul_ps(vx, vlog2e), 0);
251 
252     // Compute reduced argument t := x - elements * log(2).
253     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
254     __m512 vt = _mm512_fmadd_ps(vn, vminus_ln2_hi, vx);
255     vt = _mm512_fmadd_ps(vn, vminus_ln2_lo, vt);
256 
257     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
258     __m512 vp = _mm512_fmadd_ps(vc5, vt, vc4);
259     vp = _mm512_fmadd_ps(vp, vt, vc3);
260     vp = _mm512_fmadd_ps(vp, vt, vc2);
261     vp = _mm512_fmadd_ps(vp, vt, vc1);
262     vp = _mm512_fmadd_ps(vp, vt, vc0);
263 
264     // Accumulate "extended" floating-point numbers in ("mantissa", "exponent") representation.
265     const __m512 vmax_e = _mm512_mask_max_ps(vacce, vmask, vacce, vn);
266     const __m512 vdelta_acce = _mm512_sub_ps(vacce, vmax_e);
267     const __m512 vdelta_e = _mm512_sub_ps(vn, vmax_e);
268     vaccv = _mm512_mask_scalef_ps(vaccv, vmask, vaccv, vdelta_acce);
269     vaccv = _mm512_mask_add_ps(vaccv, vmask, vaccv, _mm512_maskz_scalef_ps(vmask, vp, vdelta_e));
270     vacce = vmax_e;
271   }
272 
273   // Reduce partial sums of "extended" floating-point numbers into a single "extended" floating-point sum.
274   const float vmax_acce = _mm512_reduce_max_ps(vacce);
275   const __m512 vdelta_acce = _mm512_sub_ps(vacce, _mm512_set1_ps(vmax_acce));
276 
277   sum[0] = _mm512_reduce_add_ps(_mm512_scalef_ps(vaccv, vdelta_acce));
278   sum[1] = vmax_acce;
279 
280   _mm256_zeroupper();
281 }
282