1 // Auto-generated file. Do not edit!
2 // Template: src/f32-raddstoreexpminusmax/sse2-rr2-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
xnn_f32_raddstoreexpminusmax_ukernel__sse2_rr2_p5_x12(size_t elements,const float * input,const float * max,float * output,float * sum,const union xnn_f32_expminus_params params[restrict XNN_MIN_ELEMENTS (1)])18 void xnn_f32_raddstoreexpminusmax_ukernel__sse2_rr2_p5_x12(
19 size_t elements,
20 const float* input,
21 const float* max,
22 float* output,
23 float* sum,
24 const union xnn_f32_expminus_params params[restrict XNN_MIN_ELEMENTS(1)]) XNN_OOB_READS
25 {
26 assert(elements % sizeof(float) == 0);
27
28 const __m128 vi_max = _mm_load1_ps(max);
29 const __m128 vlog2e = _mm_load_ps(params->sse2_rr2_p5.log2e);
30 const __m128 vmagic_bias = _mm_load_ps(params->sse2_rr2_p5.magic_bias);
31 const __m128 vminus_ln2_hi = _mm_load_ps(params->sse2_rr2_p5.minus_ln2_hi);
32 const __m128 vminus_ln2_lo = _mm_load_ps(params->sse2_rr2_p5.minus_ln2_lo);
33 const __m128 vc5 = _mm_load_ps(params->sse2_rr2_p5.c5);
34 const __m128 vc4 = _mm_load_ps(params->sse2_rr2_p5.c4);
35 const __m128 vc3 = _mm_load_ps(params->sse2_rr2_p5.c3);
36 const __m128 vc2 = _mm_load_ps(params->sse2_rr2_p5.c2);
37 const __m128 vc1 = _mm_load_ps(params->sse2_rr2_p5.c1);
38 const __m128 vdenorm_cutoff = _mm_load_ps(params->sse2_rr2_p5.denorm_cutoff);
39
40 __m128 vacc0 = _mm_setzero_ps();
41 for (; elements >= 12 * sizeof(float); elements -= 12 * sizeof(float)) {
42 // Load 12 (3x4) inputs at a time.
43 const __m128 vi0123 = _mm_loadu_ps(input);
44 const __m128 vi4567 = _mm_loadu_ps(input + 4);
45 const __m128 vi89AB = _mm_loadu_ps(input + 8);
46 input += 12;
47
48 // Subtract maximum input x := i - i_max. This implies x <= 0.
49 const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
50 const __m128 vx4567 = _mm_sub_ps(vi4567, vi_max);
51 const __m128 vx89AB = _mm_sub_ps(vi89AB, vi_max);
52
53 // Compute reduced argument elements := round(x / log(2)).
54 __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
55 __m128 vn4567 = _mm_add_ps(_mm_mul_ps(vx4567, vlog2e), vmagic_bias);
56 __m128 vn89AB = _mm_add_ps(_mm_mul_ps(vx89AB, vlog2e), vmagic_bias);
57
58 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
59 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
60 const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
61 const __m128 vs4567 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn4567), 23));
62 const __m128 vs89AB = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn89AB), 23));
63
64 // Subtract the large number back to get final elements := round(x / log(2)).
65 vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
66 vn4567 = _mm_sub_ps(vn4567, vmagic_bias);
67 vn89AB = _mm_sub_ps(vn89AB, vmagic_bias);
68
69 // Compute reduced argument t := x - elements * log(2).
70 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
71 __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
72 __m128 vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_hi), vx4567);
73 __m128 vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_hi), vx89AB);
74
75 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
76 vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_lo), vt4567);
77 vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_lo), vt89AB);
78
79 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
80 __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
81 __m128 vp4567 = _mm_add_ps(_mm_mul_ps(vc5, vt4567), vc4);
82 __m128 vp89AB = _mm_add_ps(_mm_mul_ps(vc5, vt89AB), vc4);
83
84 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
85 vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc3);
86 vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc3);
87
88 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
89 vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc2);
90 vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc2);
91
92 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
93 vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc1);
94 vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc1);
95
96 // Reconstruct the final f value:
97 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
98 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
99 // = s + (t * s) * p
100 vt0123 = _mm_mul_ps(vt0123, vs0123);
101 vt4567 = _mm_mul_ps(vt4567, vs4567);
102 vt89AB = _mm_mul_ps(vt89AB, vs89AB);
103
104 __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
105 __m128 vf4567 = _mm_add_ps(_mm_mul_ps(vt4567, vp4567), vs4567);
106 __m128 vf89AB = _mm_add_ps(_mm_mul_ps(vt89AB, vp89AB), vs89AB);
107
108 // For inputs below zero cutoff, replace output with +0.0f.
109 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
110 vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
111 vf4567 = _mm_andnot_ps(_mm_cmplt_ps(vx4567, vdenorm_cutoff), vf4567);
112 vf89AB = _mm_andnot_ps(_mm_cmplt_ps(vx89AB, vdenorm_cutoff), vf89AB);
113
114 // Store 12 (3x4) outputs at a time.
115 _mm_storeu_ps(output, vf0123);
116 _mm_storeu_ps(output + 4, vf4567);
117 _mm_storeu_ps(output + 8, vf89AB);
118 output += 12;
119
120 // Accumulate computed exponents.
121 vacc0 = _mm_add_ps(vacc0, vf0123);
122 vacc0 = _mm_add_ps(vacc0, vf4567);
123 vacc0 = _mm_add_ps(vacc0, vf89AB);
124 }
125
126 __m128 vacc = vacc0;
127 for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
128 // Load 4 inputs at a time.
129 const __m128 vi = _mm_loadu_ps(input);
130 input += 4;
131
132 // Subtract maximum input x := i - i_max. This implies x <= 0.
133 const __m128 vx = _mm_sub_ps(vi, vi_max);
134
135 // Compute reduced argument elements := round(x / log(2)).
136 __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
137
138 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
139 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
140 const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
141
142 // Subtract the large number back to get final elements := round(x / log(2)).
143 vn = _mm_sub_ps(vn, vmagic_bias);
144
145 // Compute reduced argument t := x - elements * log(2).
146 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
147 __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
148 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
149
150 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
151 __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
152 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
153 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
154 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
155
156 // Reconstruct the final f value:
157 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
158 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
159 // = s + (t * s) * p
160 vt = _mm_mul_ps(vt, vs);
161 __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
162
163 // For inputs below zero cutoff, replace output with +0.0f.
164 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
165 vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
166
167 // Store 4 outputs at a time.
168 _mm_storeu_ps(output, vf);
169 output += 4;
170
171 // Accumulate computed exponents.
172 vacc = _mm_add_ps(vacc, vf);
173 }
174 if (elements != 0) {
175 assert(elements >= 1 * sizeof(float));
176 assert(elements <= 3 * sizeof(float));
177 // Load 4 inputs at a time.
178 const __m128 vi = _mm_loadu_ps(input);
179
180 // Subtract maximum input x := i - i_max. This implies x <= 0.
181 const __m128 vx = _mm_sub_ps(vi, vi_max);
182
183 // Compute reduced argument elements := round(x / log(2)).
184 __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
185
186 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
187 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
188 const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
189
190 // Subtract the large number back to get final elements := round(x / log(2)).
191 vn = _mm_sub_ps(vn, vmagic_bias);
192
193 // Compute reduced argument t := x - elements * log(2).
194 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
195 __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
196 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
197
198 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
199 __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
200 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
201 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
202 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
203
204 // Reconstruct the final f value:
205 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
206 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
207 // = s + (t * s) * p
208 vt = _mm_mul_ps(vt, vs);
209 __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
210
211 // For inputs below zero cutoff, replace output with +0.0f.
212 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
213 vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
214
215 if (elements & (2 * sizeof(float))) {
216 // Store 2 outputs at a time.
217 _mm_storel_pi((__m64*) output, vf);
218 output += 2;
219
220 // Accumulate 2 computed exponents.
221 vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
222
223 vf = _mm_movehl_ps(vf, vf);
224 }
225 if (elements & (1 * sizeof(float))) {
226 // Store 1 output at a time.
227 _mm_store_ss(output, vf);
228
229 // Accumulate 1 computed exponent.
230 vacc = _mm_add_ss(vacc, vf);
231 }
232 }
233 // Reduce 4 elements in the SIMD register
234 vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
235 vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
236 _mm_store_ss(sum, vacc);
237 }
238