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1 // Auto-generated file. Do not edit!
2 //   Template: src/f32-vscaleextexp/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 
12 #include <immintrin.h>
13 
14 #include <xnnpack/common.h>
15 #include <xnnpack/intrinsics-polyfill.h>
16 #include <xnnpack/vscaleextexp.h>
17 
18 
xnn_f32_vscaleextexp_ukernel__avx512f_p5_scalef_x112(size_t elements,const float * x,float * y,float scale_value,float scale_exp)19 void xnn_f32_vscaleextexp_ukernel__avx512f_p5_scalef_x112(
20     size_t elements,
21     const float* x,
22     float* y,
23     float scale_value,
24     float scale_exp)
25 {
26   assert(elements % sizeof(float) == 0);
27 
28   const __m512 vlog2e = _mm512_set1_ps(0x1.715476p+0f);
29   const __m512 vminus_ln2_hi = _mm512_set1_ps(-0x1.62E43p-1f);
30   const __m512 vminus_ln2_lo = _mm512_set1_ps(0x1.05C61p-29f);
31 
32   const __m512 vc0 = _mm512_set1_ps(1.0f);
33   const __m512 vc1 = _mm512_set1_ps(0x1.FFFFF6p-1f);
34   const __m512 vc2 = _mm512_set1_ps(0x1.FFFDC6p-2f);
35   const __m512 vc3 = _mm512_set1_ps(0x1.555A80p-3f);
36   const __m512 vc4 = _mm512_set1_ps(0x1.573A1Ap-5f);
37   const __m512 vc5 = _mm512_set1_ps(0x1.0F9F9Cp-7f);
38 
39   const __m512 vscalev = _mm512_set1_ps(scale_value);
40   const __m512 vscalee = _mm512_set1_ps(scale_exp);
41 
42   for (; elements >= 112 * sizeof(float); elements -= 112 * sizeof(float)) {
43     // Load 112 (7x16) inputs at a time.
44     const __m512 vx0 = _mm512_loadu_ps(x);
45     const __m512 vx1 = _mm512_loadu_ps(x + 16);
46     const __m512 vx2 = _mm512_loadu_ps(x + 32);
47     const __m512 vx3 = _mm512_loadu_ps(x + 48);
48     const __m512 vx4 = _mm512_loadu_ps(x + 64);
49     const __m512 vx5 = _mm512_loadu_ps(x + 80);
50     const __m512 vx6 = _mm512_loadu_ps(x + 96);
51     x += 112;
52 
53     // Compute reduced argument elements := round(x / log(2)).
54     const __m512 vn0 = _mm512_roundscale_ps(_mm512_mul_ps(vx0, vlog2e), 0);
55     const __m512 vn1 = _mm512_roundscale_ps(_mm512_mul_ps(vx1, vlog2e), 0);
56     const __m512 vn2 = _mm512_roundscale_ps(_mm512_mul_ps(vx2, vlog2e), 0);
57     const __m512 vn3 = _mm512_roundscale_ps(_mm512_mul_ps(vx3, vlog2e), 0);
58     const __m512 vn4 = _mm512_roundscale_ps(_mm512_mul_ps(vx4, vlog2e), 0);
59     const __m512 vn5 = _mm512_roundscale_ps(_mm512_mul_ps(vx5, vlog2e), 0);
60     const __m512 vn6 = _mm512_roundscale_ps(_mm512_mul_ps(vx6, vlog2e), 0);
61 
62     // Compute reduced argument t := x - elements * log(2).
63     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
64     __m512 vt0 = _mm512_fmadd_ps(vn0, vminus_ln2_hi, vx0);
65     __m512 vt1 = _mm512_fmadd_ps(vn1, vminus_ln2_hi, vx1);
66     __m512 vt2 = _mm512_fmadd_ps(vn2, vminus_ln2_hi, vx2);
67     __m512 vt3 = _mm512_fmadd_ps(vn3, vminus_ln2_hi, vx3);
68     __m512 vt4 = _mm512_fmadd_ps(vn4, vminus_ln2_hi, vx4);
69     __m512 vt5 = _mm512_fmadd_ps(vn5, vminus_ln2_hi, vx5);
70     __m512 vt6 = _mm512_fmadd_ps(vn6, vminus_ln2_hi, vx6);
71 
72     vt0 = _mm512_fmadd_ps(vn0, vminus_ln2_lo, vt0);
73     vt1 = _mm512_fmadd_ps(vn1, vminus_ln2_lo, vt1);
74     vt2 = _mm512_fmadd_ps(vn2, vminus_ln2_lo, vt2);
75     vt3 = _mm512_fmadd_ps(vn3, vminus_ln2_lo, vt3);
76     vt4 = _mm512_fmadd_ps(vn4, vminus_ln2_lo, vt4);
77     vt5 = _mm512_fmadd_ps(vn5, vminus_ln2_lo, vt5);
78     vt6 = _mm512_fmadd_ps(vn6, vminus_ln2_lo, vt6);
79 
80     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
81     __m512 vp0 = _mm512_fmadd_ps(vc5, vt0, vc4);
82     __m512 vp1 = _mm512_fmadd_ps(vc5, vt1, vc4);
83     __m512 vp2 = _mm512_fmadd_ps(vc5, vt2, vc4);
84     __m512 vp3 = _mm512_fmadd_ps(vc5, vt3, vc4);
85     __m512 vp4 = _mm512_fmadd_ps(vc5, vt4, vc4);
86     __m512 vp5 = _mm512_fmadd_ps(vc5, vt5, vc4);
87     __m512 vp6 = _mm512_fmadd_ps(vc5, vt6, vc4);
88 
89     vp0 = _mm512_fmadd_ps(vp0, vt0, vc3);
90     vp1 = _mm512_fmadd_ps(vp1, vt1, vc3);
91     vp2 = _mm512_fmadd_ps(vp2, vt2, vc3);
92     vp3 = _mm512_fmadd_ps(vp3, vt3, vc3);
93     vp4 = _mm512_fmadd_ps(vp4, vt4, vc3);
94     vp5 = _mm512_fmadd_ps(vp5, vt5, vc3);
95     vp6 = _mm512_fmadd_ps(vp6, vt6, vc3);
96 
97     vp0 = _mm512_fmadd_ps(vp0, vt0, vc2);
98     vp1 = _mm512_fmadd_ps(vp1, vt1, vc2);
99     vp2 = _mm512_fmadd_ps(vp2, vt2, vc2);
100     vp3 = _mm512_fmadd_ps(vp3, vt3, vc2);
101     vp4 = _mm512_fmadd_ps(vp4, vt4, vc2);
102     vp5 = _mm512_fmadd_ps(vp5, vt5, vc2);
103     vp6 = _mm512_fmadd_ps(vp6, vt6, vc2);
104 
105     vp0 = _mm512_fmadd_ps(vp0, vt0, vc1);
106     vp1 = _mm512_fmadd_ps(vp1, vt1, vc1);
107     vp2 = _mm512_fmadd_ps(vp2, vt2, vc1);
108     vp3 = _mm512_fmadd_ps(vp3, vt3, vc1);
109     vp4 = _mm512_fmadd_ps(vp4, vt4, vc1);
110     vp5 = _mm512_fmadd_ps(vp5, vt5, vc1);
111     vp6 = _mm512_fmadd_ps(vp6, vt6, vc1);
112 
113     vp0 = _mm512_fmadd_ps(vp0, vt0, vc0);
114     vp1 = _mm512_fmadd_ps(vp1, vt1, vc0);
115     vp2 = _mm512_fmadd_ps(vp2, vt2, vc0);
116     vp3 = _mm512_fmadd_ps(vp3, vt3, vc0);
117     vp4 = _mm512_fmadd_ps(vp4, vt4, vc0);
118     vp5 = _mm512_fmadd_ps(vp5, vt5, vc0);
119     vp6 = _mm512_fmadd_ps(vp6, vt6, vc0);
120 
121     // Multiply "extended" floating-point numbers in ("mantissa", "exponent") representation where
122     //  - vnX is "exponent"
123     //  - vpX is "mantissa"
124     //
125     // exp2(ae) * av * exp2(be) * bv =
126     //   = exp2(ae + be) * (av * bv)
127     __m512 vf0 = _mm512_mul_ps(vp0, vscalev);
128     __m512 vf1 = _mm512_mul_ps(vp1, vscalev);
129     __m512 vf2 = _mm512_mul_ps(vp2, vscalev);
130     __m512 vf3 = _mm512_mul_ps(vp3, vscalev);
131     __m512 vf4 = _mm512_mul_ps(vp4, vscalev);
132     __m512 vf5 = _mm512_mul_ps(vp5, vscalev);
133     __m512 vf6 = _mm512_mul_ps(vp6, vscalev);
134 
135     const __m512 ve0 = _mm512_add_ps(vn0, vscalee);
136     const __m512 ve1 = _mm512_add_ps(vn1, vscalee);
137     const __m512 ve2 = _mm512_add_ps(vn2, vscalee);
138     const __m512 ve3 = _mm512_add_ps(vn3, vscalee);
139     const __m512 ve4 = _mm512_add_ps(vn4, vscalee);
140     const __m512 ve5 = _mm512_add_ps(vn5, vscalee);
141     const __m512 ve6 = _mm512_add_ps(vn6, vscalee);
142 
143     // Multiply "mantissa" by the exp2("exponent").
144     vf0 = _mm512_scalef_ps(vf0, ve0);
145     vf1 = _mm512_scalef_ps(vf1, ve1);
146     vf2 = _mm512_scalef_ps(vf2, ve2);
147     vf3 = _mm512_scalef_ps(vf3, ve3);
148     vf4 = _mm512_scalef_ps(vf4, ve4);
149     vf5 = _mm512_scalef_ps(vf5, ve5);
150     vf6 = _mm512_scalef_ps(vf6, ve6);
151 
152     // Store 128 (8x16) results at a time.
153     _mm512_storeu_ps(y, vf0);
154     _mm512_storeu_ps(y + 0, vf0);
155     _mm512_storeu_ps(y + 16, vf1);
156     _mm512_storeu_ps(y + 32, vf2);
157     _mm512_storeu_ps(y + 48, vf3);
158     _mm512_storeu_ps(y + 64, vf4);
159     _mm512_storeu_ps(y + 80, vf5);
160     _mm512_storeu_ps(y + 96, vf6);
161     y += 112;
162   }
163 
164   for (; elements >= 16 * sizeof(float); elements -= 16 * sizeof(float)) {
165     // Load 16 inputs at a time.
166     const __m512 vx = _mm512_loadu_ps(x);
167     x += 16;
168 
169     // Compute reduced argument elements := round(x / log(2)).
170     const __m512 vn = _mm512_roundscale_ps(_mm512_mul_ps(vx, vlog2e), 0);
171 
172     // Compute reduced argument t := x - elements * log(2).
173     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
174     __m512 vt = _mm512_fmadd_ps(vn, vminus_ln2_hi, vx);
175     vt = _mm512_fmadd_ps(vn, vminus_ln2_lo, vt);
176 
177     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
178     __m512 vp = _mm512_fmadd_ps(vc5, vt, vc4);
179     vp = _mm512_fmadd_ps(vp, vt, vc3);
180     vp = _mm512_fmadd_ps(vp, vt, vc2);
181     vp = _mm512_fmadd_ps(vp, vt, vc1);
182     vp = _mm512_fmadd_ps(vp, vt, vc0);
183 
184     // Multiply "extended" floating-point numbers in ("mantissa", "exponent") representation.
185     __m512 vf = _mm512_mul_ps(vp, vscalev);
186     const __m512 ve = _mm512_add_ps(vn, vscalee);
187 
188     // Multiply "mantissa" by the exp2("exponent").
189     vf = _mm512_scalef_ps(vf, ve);
190 
191     // Store 16 results at a time.
192     _mm512_storeu_ps(y, vf);
193     y += 16;
194   }
195   if XNN_UNLIKELY(elements != 0) {
196     // Prepare mask for valid 32-bit elements (depends on elements).
197     elements >>= 2 /* log2(sizeof(float)) */;
198     const __mmask16 vmask = _cvtu32_mask16((uint16_t) ((uint32_t) (UINT32_C(1) << elements) - UINT32_C(1)));
199 
200     // Load up to 15 inputs at a time.
201     const __m512 vx = _mm512_maskz_loadu_ps(vmask, x);
202 
203     // Compute reduced argument elements := round(x / log(2)).
204     const __m512 vn = _mm512_roundscale_ps(_mm512_mul_ps(vx, vlog2e), 0);
205 
206     // Compute reduced argument t := x - elements * log(2).
207     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
208     __m512 vt = _mm512_fmadd_ps(vn, vminus_ln2_hi, vx);
209     vt = _mm512_fmadd_ps(vn, vminus_ln2_lo, vt);
210 
211     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
212     __m512 vp = _mm512_fmadd_ps(vc5, vt, vc4);
213     vp = _mm512_fmadd_ps(vp, vt, vc3);
214     vp = _mm512_fmadd_ps(vp, vt, vc2);
215     vp = _mm512_fmadd_ps(vp, vt, vc1);
216     vp = _mm512_fmadd_ps(vp, vt, vc0);
217 
218     // Multiply "extended" floating-point numbers in ("mantissa", "exponent") representation.
219     __m512 vf = _mm512_mul_ps(vp, vscalev);
220     const __m512 ve = _mm512_add_ps(vn, vscalee);
221 
222     // Multiply "mantissa" by the exp2("exponent").
223     vf = _mm512_scalef_ps(vf, ve);
224 
225     // Store up to 15 results at a time.
226     _mm512_mask_storeu_ps(y, vmask, vf);
227   }
228   _mm256_zeroupper();
229 }
230