xref: /aosp_15_r20/external/XNNPACK/src/f32-raddstoreexpminusmax/gen/sse2-rr2-p5-x12.c (revision 4bdc94577ba0e567308109d787f7fec7b531ce36)
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