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_x4(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_x4(
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 >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
42 // Load 4 (1x4) inputs at a time.
43 const __m128 vi0123 = _mm_loadu_ps(input);
44 input += 4;
45
46 // Subtract maximum input x := i - i_max. This implies x <= 0.
47 const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
48
49 // Compute reduced argument elements := round(x / log(2)).
50 __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
51
52 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
53 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
54 const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
55
56 // Subtract the large number back to get final elements := round(x / log(2)).
57 vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
58
59 // Compute reduced argument t := x - elements * log(2).
60 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
61 __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
62
63 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
64
65 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
66 __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
67
68 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
69
70 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
71
72 vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
73
74 // Reconstruct the final f value:
75 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
76 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
77 // = s + (t * s) * p
78 vt0123 = _mm_mul_ps(vt0123, vs0123);
79
80 __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
81
82 // For inputs below zero cutoff, replace output with +0.0f.
83 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
84 vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
85
86 // Store 4 (1x4) outputs at a time.
87 _mm_storeu_ps(output, vf0123);
88 output += 4;
89
90 // Accumulate computed exponents.
91 vacc0 = _mm_add_ps(vacc0, vf0123);
92 }
93
94 __m128 vacc = vacc0;
95 for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
96 // Load 4 inputs at a time.
97 const __m128 vi = _mm_loadu_ps(input);
98 input += 4;
99
100 // Subtract maximum input x := i - i_max. This implies x <= 0.
101 const __m128 vx = _mm_sub_ps(vi, vi_max);
102
103 // Compute reduced argument elements := round(x / log(2)).
104 __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
105
106 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
107 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
108 const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
109
110 // Subtract the large number back to get final elements := round(x / log(2)).
111 vn = _mm_sub_ps(vn, vmagic_bias);
112
113 // Compute reduced argument t := x - elements * log(2).
114 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
115 __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
116 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
117
118 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
119 __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
120 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
121 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
122 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
123
124 // Reconstruct the final f value:
125 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
126 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
127 // = s + (t * s) * p
128 vt = _mm_mul_ps(vt, vs);
129 __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
130
131 // For inputs below zero cutoff, replace output with +0.0f.
132 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
133 vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
134
135 // Store 4 outputs at a time.
136 _mm_storeu_ps(output, vf);
137 output += 4;
138
139 // Accumulate computed exponents.
140 vacc = _mm_add_ps(vacc, vf);
141 }
142 if (elements != 0) {
143 assert(elements >= 1 * sizeof(float));
144 assert(elements <= 3 * sizeof(float));
145 // Load 4 inputs at a time.
146 const __m128 vi = _mm_loadu_ps(input);
147
148 // Subtract maximum input x := i - i_max. This implies x <= 0.
149 const __m128 vx = _mm_sub_ps(vi, vi_max);
150
151 // Compute reduced argument elements := round(x / log(2)).
152 __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
153
154 // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
155 // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
156 const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
157
158 // Subtract the large number back to get final elements := round(x / log(2)).
159 vn = _mm_sub_ps(vn, vmagic_bias);
160
161 // Compute reduced argument t := x - elements * log(2).
162 // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
163 __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
164 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
165
166 // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
167 __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
168 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
169 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
170 vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
171
172 // Reconstruct the final f value:
173 // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
174 // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
175 // = s + (t * s) * p
176 vt = _mm_mul_ps(vt, vs);
177 __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
178
179 // For inputs below zero cutoff, replace output with +0.0f.
180 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
181 vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
182
183 if (elements & (2 * sizeof(float))) {
184 // Store 2 outputs at a time.
185 _mm_storel_pi((__m64*) output, vf);
186 output += 2;
187
188 // Accumulate 2 computed exponents.
189 vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
190
191 vf = _mm_movehl_ps(vf, vf);
192 }
193 if (elements & (1 * sizeof(float))) {
194 // Store 1 output at a time.
195 _mm_store_ss(output, vf);
196
197 // Accumulate 1 computed exponent.
198 vacc = _mm_add_ss(vacc, vf);
199 }
200 }
201 // Reduce 4 elements in the SIMD register
202 vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
203 vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
204 _mm_store_ss(sum, vacc);
205 }
206