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Marat Dukhanb39689d2020-01-24 13:32:20 -08001// Auto-generated file. Do not edit!
2// Template: src/f32-raddstoreexpminusmax/sse2-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 <emmintrin.h>
13
14#include <xnnpack/common.h>
15#include <xnnpack/raddstoreexpminusmax.h>
16
17
18void xnn_f32_raddstoreexpminusmax_ukernel__sse2_p5_x4(
19 size_t elements,
20 const float* input,
21 float* output,
22 float* sum,
Marat Dukhanb2217dd2020-05-28 17:30:28 -070023 float max) XNN_DISABLE_TSAN
Marat Dukhanb39689d2020-01-24 13:32:20 -080024{
25 assert(elements % sizeof(float) == 0);
26
27 const __m128 vmagic_bias = _mm_set1_ps(0x1.8000FEp23f);
28 // The smallest x for which expf(x) is normalized.
29 const __m128 vdenorm_cutoff = _mm_set1_ps(-0x1.5D589Ep6f);
30 const __m128 vlog2e = _mm_set1_ps(0x1.715476p+0f);
31 // Last 7 bits are zeroes
32 const __m128 vminus_ln2_hi = _mm_set1_ps(-0x1.62E400p-1f);
33 const __m128 vminus_ln2_lo = _mm_set1_ps(-0x1.7F7D1Cp-20f);
34
35 const __m128 vc1 = _mm_set1_ps(0x1.FFFFF6p-1f);
36 const __m128 vc2 = _mm_set1_ps(0x1.FFFDC6p-2f);
37 const __m128 vc3 = _mm_set1_ps(0x1.555A80p-3f);
38 const __m128 vc4 = _mm_set1_ps(0x1.573A1Ap-5f);
39 const __m128 vc5 = _mm_set1_ps(0x1.0F9F9Cp-7f);
40
41 const __m128 vi_max = _mm_set1_ps(max);
42
43 __m128 vacc0 = _mm_setzero_ps();
44 for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
45 // Load 4 (1x4) inputs at a time.
46 const __m128 vi0123 = _mm_loadu_ps(input);
47 input += 4;
48
49 // Subtract maximum input x := i - i_max. This implies x <= 0.
50 const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
51
52 // Compute reduced argument elements := round(x / log(2)).
53 __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
54
55 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
56 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
57 const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
58
59 // Subtract the large number back to get final elements := round(x / log(2)).
60 vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
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 __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
65
66 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
67
Marat Dukhan102a7392020-11-20 01:18:10 -080068 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
Marat Dukhanb39689d2020-01-24 13:32:20 -080069 __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
70
71 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
72
73 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
74
75 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
76
77 // Reconstruct the final f value:
78 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
79 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
80 // = s + (t * s) * p
81 vt0123 = _mm_mul_ps(vt0123, vs0123);
82
83 __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
84
85 // For inputs below zero cutoff, replace output with +0.0f.
86 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
87 vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
88
89 // Store 4 (1x4) outputs at a time.
90 _mm_storeu_ps(output, vf0123);
91 output += 4;
92
93 // Accumulate computed exponents.
94 vacc0 = _mm_add_ps(vacc0, vf0123);
95 }
96
97 __m128 vacc = vacc0;
98 for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
99 // Load 4 inputs at a time.
100 const __m128 vi = _mm_loadu_ps(input);
101 input += 4;
102
103 // Subtract maximum input x := i - i_max. This implies x <= 0.
104 const __m128 vx = _mm_sub_ps(vi, vi_max);
105
106 // Compute reduced argument elements := round(x / log(2)).
107 __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
108
109 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
110 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
111 const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
112
113 // Subtract the large number back to get final elements := round(x / log(2)).
114 vn = _mm_sub_ps(vn, 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 __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
119 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
120
Marat Dukhan102a7392020-11-20 01:18:10 -0800121 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
Marat Dukhanb39689d2020-01-24 13:32:20 -0800122 __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
123 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
124 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
125 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
126
127 // Reconstruct the final f value:
128 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
129 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
130 // = s + (t * s) * p
131 vt = _mm_mul_ps(vt, vs);
132 __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
133
134 // For inputs below zero cutoff, replace output with +0.0f.
135 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
136 vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
137
138 // Store 4 outputs at a time.
139 _mm_storeu_ps(output, vf);
140 output += 4;
141
142 // Accumulate computed exponents.
143 vacc = _mm_add_ps(vacc, vf);
144 }
145 if (elements != 0) {
146 assert(elements >= 1 * sizeof(float));
147 assert(elements <= 3 * sizeof(float));
148 // Load 4 inputs at a time.
Marat Dukhanb2217dd2020-05-28 17:30:28 -0700149 const __m128 vi = _mm_loadu_ps(input);
Marat Dukhanb39689d2020-01-24 13:32:20 -0800150
151 // Subtract maximum input x := i - i_max. This implies x <= 0.
152 const __m128 vx = _mm_sub_ps(vi, vi_max);
153
154 // Compute reduced argument elements := round(x / log(2)).
155 __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
156
157 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
158 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
159 const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
160
161 // Subtract the large number back to get final elements := round(x / log(2)).
162 vn = _mm_sub_ps(vn, vmagic_bias);
163
164 // Compute reduced argument t := x - elements * log(2).
165 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
166 __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
167 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
168
Marat Dukhan102a7392020-11-20 01:18:10 -0800169 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
Marat Dukhanb39689d2020-01-24 13:32:20 -0800170 __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
171 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
172 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
173 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
174
175 // Reconstruct the final f value:
176 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
177 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
178 // = s + (t * s) * p
179 vt = _mm_mul_ps(vt, vs);
180 __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
181
182 // For inputs below zero cutoff, replace output with +0.0f.
183 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
184 vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
185
186 if (elements & (2 * sizeof(float))) {
187 // Store 2 outputs at a time.
188 _mm_storel_pi((__m64*) output, vf);
189 output += 2;
190
191 // Accumulate 2 computed exponents.
192 vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
193
194 vf = _mm_movehl_ps(vf, vf);
195 }
196 if (elements & (1 * sizeof(float))) {
197 // Store 1 output at a time.
198 _mm_store_ss(output, vf);
199
200 // Accumulate 1 computed exponent.
201 vacc = _mm_add_ss(vacc, vf);
202 }
203 }
204 // Reduce 4 elements in the SIMD register
205 vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
206 vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
207 _mm_store_ss(sum, vacc);
208}