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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_x20(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_x20(
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 >= 20 * sizeof(float); elements -= 20 * sizeof(float)) {
42     // Load 20 (5x4) 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     const __m128 viCDEF = _mm_loadu_ps(input + 12);
47     const __m128 viGHIJ = _mm_loadu_ps(input + 16);
48     input += 20;
49 
50     // Subtract maximum input x := i - i_max. This implies x <= 0.
51     const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
52     const __m128 vx4567 = _mm_sub_ps(vi4567, vi_max);
53     const __m128 vx89AB = _mm_sub_ps(vi89AB, vi_max);
54     const __m128 vxCDEF = _mm_sub_ps(viCDEF, vi_max);
55     const __m128 vxGHIJ = _mm_sub_ps(viGHIJ, vi_max);
56 
57     // Compute reduced argument elements := round(x / log(2)).
58     __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
59     __m128 vn4567 = _mm_add_ps(_mm_mul_ps(vx4567, vlog2e), vmagic_bias);
60     __m128 vn89AB = _mm_add_ps(_mm_mul_ps(vx89AB, vlog2e), vmagic_bias);
61     __m128 vnCDEF = _mm_add_ps(_mm_mul_ps(vxCDEF, vlog2e), vmagic_bias);
62     __m128 vnGHIJ = _mm_add_ps(_mm_mul_ps(vxGHIJ, vlog2e), vmagic_bias);
63 
64     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
65     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
66     const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
67     const __m128 vs4567 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn4567), 23));
68     const __m128 vs89AB = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn89AB), 23));
69     const __m128 vsCDEF = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vnCDEF), 23));
70     const __m128 vsGHIJ = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vnGHIJ), 23));
71 
72     // Subtract the large number back to get final elements := round(x / log(2)).
73     vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
74     vn4567 = _mm_sub_ps(vn4567, vmagic_bias);
75     vn89AB = _mm_sub_ps(vn89AB, vmagic_bias);
76     vnCDEF = _mm_sub_ps(vnCDEF, vmagic_bias);
77     vnGHIJ = _mm_sub_ps(vnGHIJ, vmagic_bias);
78 
79     // Compute reduced argument t := x - elements * log(2).
80     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
81     __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
82     __m128 vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_hi), vx4567);
83     __m128 vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_hi), vx89AB);
84     __m128 vtCDEF = _mm_add_ps(_mm_mul_ps(vnCDEF, vminus_ln2_hi), vxCDEF);
85     __m128 vtGHIJ = _mm_add_ps(_mm_mul_ps(vnGHIJ, vminus_ln2_hi), vxGHIJ);
86 
87     vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
88     vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_lo), vt4567);
89     vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_lo), vt89AB);
90     vtCDEF = _mm_add_ps(_mm_mul_ps(vnCDEF, vminus_ln2_lo), vtCDEF);
91     vtGHIJ = _mm_add_ps(_mm_mul_ps(vnGHIJ, vminus_ln2_lo), vtGHIJ);
92 
93     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
94     __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
95     __m128 vp4567 = _mm_add_ps(_mm_mul_ps(vc5, vt4567), vc4);
96     __m128 vp89AB = _mm_add_ps(_mm_mul_ps(vc5, vt89AB), vc4);
97     __m128 vpCDEF = _mm_add_ps(_mm_mul_ps(vc5, vtCDEF), vc4);
98     __m128 vpGHIJ = _mm_add_ps(_mm_mul_ps(vc5, vtGHIJ), vc4);
99 
100     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
101     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc3);
102     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc3);
103     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc3);
104     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc3);
105 
106     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
107     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc2);
108     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc2);
109     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc2);
110     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc2);
111 
112     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
113     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc1);
114     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc1);
115     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc1);
116     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc1);
117 
118     // Reconstruct the final f value:
119     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
120     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
121     //     = s + (t * s) * p
122     vt0123 = _mm_mul_ps(vt0123, vs0123);
123     vt4567 = _mm_mul_ps(vt4567, vs4567);
124     vt89AB = _mm_mul_ps(vt89AB, vs89AB);
125     vtCDEF = _mm_mul_ps(vtCDEF, vsCDEF);
126     vtGHIJ = _mm_mul_ps(vtGHIJ, vsGHIJ);
127 
128     __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
129     __m128 vf4567 = _mm_add_ps(_mm_mul_ps(vt4567, vp4567), vs4567);
130     __m128 vf89AB = _mm_add_ps(_mm_mul_ps(vt89AB, vp89AB), vs89AB);
131     __m128 vfCDEF = _mm_add_ps(_mm_mul_ps(vtCDEF, vpCDEF), vsCDEF);
132     __m128 vfGHIJ = _mm_add_ps(_mm_mul_ps(vtGHIJ, vpGHIJ), vsGHIJ);
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     vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
137     vf4567 = _mm_andnot_ps(_mm_cmplt_ps(vx4567, vdenorm_cutoff), vf4567);
138     vf89AB = _mm_andnot_ps(_mm_cmplt_ps(vx89AB, vdenorm_cutoff), vf89AB);
139     vfCDEF = _mm_andnot_ps(_mm_cmplt_ps(vxCDEF, vdenorm_cutoff), vfCDEF);
140     vfGHIJ = _mm_andnot_ps(_mm_cmplt_ps(vxGHIJ, vdenorm_cutoff), vfGHIJ);
141 
142     // Store 20 (5x4) outputs at a time.
143     _mm_storeu_ps(output, vf0123);
144     _mm_storeu_ps(output + 4, vf4567);
145     _mm_storeu_ps(output + 8, vf89AB);
146     _mm_storeu_ps(output + 12, vfCDEF);
147     _mm_storeu_ps(output + 16, vfGHIJ);
148     output += 20;
149 
150     // Accumulate computed exponents.
151     vacc0 = _mm_add_ps(vacc0, vf0123);
152     vacc0 = _mm_add_ps(vacc0, vf4567);
153     vacc0 = _mm_add_ps(vacc0, vf89AB);
154     vacc0 = _mm_add_ps(vacc0, vfCDEF);
155     vacc0 = _mm_add_ps(vacc0, vfGHIJ);
156   }
157 
158   __m128 vacc = vacc0;
159   for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
160     // Load 4 inputs at a time.
161     const __m128 vi = _mm_loadu_ps(input);
162     input += 4;
163 
164     // Subtract maximum input x := i - i_max. This implies x <= 0.
165     const __m128 vx = _mm_sub_ps(vi, vi_max);
166 
167     // Compute reduced argument elements := round(x / log(2)).
168     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
169 
170     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
171     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
172     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
173 
174     // Subtract the large number back to get final elements := round(x / log(2)).
175     vn = _mm_sub_ps(vn, vmagic_bias);
176 
177     // Compute reduced argument t := x - elements * log(2).
178     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
179     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
180     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
181 
182     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
183     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
184     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
185     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
186     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
187 
188     // Reconstruct the final f value:
189     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
190     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
191     //     = s + (t * s) * p
192     vt = _mm_mul_ps(vt, vs);
193     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
194 
195     // For inputs below zero cutoff, replace output with +0.0f.
196     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
197     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
198 
199     // Store 4 outputs at a time.
200     _mm_storeu_ps(output, vf);
201     output += 4;
202 
203     // Accumulate computed exponents.
204     vacc = _mm_add_ps(vacc, vf);
205   }
206   if (elements != 0) {
207     assert(elements >= 1 * sizeof(float));
208     assert(elements <= 3 * sizeof(float));
209     // Load 4 inputs at a time.
210     const __m128 vi = _mm_loadu_ps(input);
211 
212     // Subtract maximum input x := i - i_max. This implies x <= 0.
213     const __m128 vx = _mm_sub_ps(vi, vi_max);
214 
215     // Compute reduced argument elements := round(x / log(2)).
216     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
217 
218     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
219     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
220     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
221 
222     // Subtract the large number back to get final elements := round(x / log(2)).
223     vn = _mm_sub_ps(vn, vmagic_bias);
224 
225     // Compute reduced argument t := x - elements * log(2).
226     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
227     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
228     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
229 
230     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
231     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
232     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
233     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
234     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
235 
236     // Reconstruct the final f value:
237     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
238     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
239     //     = s + (t * s) * p
240     vt = _mm_mul_ps(vt, vs);
241     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
242 
243     // For inputs below zero cutoff, replace output with +0.0f.
244     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
245     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
246 
247     if (elements & (2 * sizeof(float))) {
248       // Store 2 outputs at a time.
249       _mm_storel_pi((__m64*) output, vf);
250       output += 2;
251 
252       // Accumulate 2 computed exponents.
253       vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
254 
255       vf = _mm_movehl_ps(vf, vf);
256     }
257     if (elements & (1 * sizeof(float))) {
258       // Store 1 output at a time.
259       _mm_store_ss(output, vf);
260 
261       // Accumulate 1 computed exponent.
262       vacc = _mm_add_ss(vacc, vf);
263     }
264   }
265   // Reduce 4 elements in the SIMD register
266   vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
267   vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
268   _mm_store_ss(sum, vacc);
269 }
270