• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
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_acc5(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_acc5(
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   __m128 vacc1 = _mm_setzero_ps();
42   __m128 vacc2 = _mm_setzero_ps();
43   __m128 vacc3 = _mm_setzero_ps();
44   __m128 vacc4 = _mm_setzero_ps();
45   for (; elements >= 20 * sizeof(float); elements -= 20 * sizeof(float)) {
46     // Load 20 (5x4) inputs at a time.
47     const __m128 vi0123 = _mm_loadu_ps(input);
48     const __m128 vi4567 = _mm_loadu_ps(input + 4);
49     const __m128 vi89AB = _mm_loadu_ps(input + 8);
50     const __m128 viCDEF = _mm_loadu_ps(input + 12);
51     const __m128 viGHIJ = _mm_loadu_ps(input + 16);
52     input += 20;
53 
54     // Subtract maximum input x := i - i_max. This implies x <= 0.
55     const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
56     const __m128 vx4567 = _mm_sub_ps(vi4567, vi_max);
57     const __m128 vx89AB = _mm_sub_ps(vi89AB, vi_max);
58     const __m128 vxCDEF = _mm_sub_ps(viCDEF, vi_max);
59     const __m128 vxGHIJ = _mm_sub_ps(viGHIJ, vi_max);
60 
61     // Compute reduced argument elements := round(x / log(2)).
62     __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
63     __m128 vn4567 = _mm_add_ps(_mm_mul_ps(vx4567, vlog2e), vmagic_bias);
64     __m128 vn89AB = _mm_add_ps(_mm_mul_ps(vx89AB, vlog2e), vmagic_bias);
65     __m128 vnCDEF = _mm_add_ps(_mm_mul_ps(vxCDEF, vlog2e), vmagic_bias);
66     __m128 vnGHIJ = _mm_add_ps(_mm_mul_ps(vxGHIJ, vlog2e), vmagic_bias);
67 
68     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
69     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
70     const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
71     const __m128 vs4567 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn4567), 23));
72     const __m128 vs89AB = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn89AB), 23));
73     const __m128 vsCDEF = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vnCDEF), 23));
74     const __m128 vsGHIJ = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vnGHIJ), 23));
75 
76     // Subtract the large number back to get final elements := round(x / log(2)).
77     vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
78     vn4567 = _mm_sub_ps(vn4567, vmagic_bias);
79     vn89AB = _mm_sub_ps(vn89AB, vmagic_bias);
80     vnCDEF = _mm_sub_ps(vnCDEF, vmagic_bias);
81     vnGHIJ = _mm_sub_ps(vnGHIJ, vmagic_bias);
82 
83     // Compute reduced argument t := x - elements * log(2).
84     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
85     __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
86     __m128 vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_hi), vx4567);
87     __m128 vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_hi), vx89AB);
88     __m128 vtCDEF = _mm_add_ps(_mm_mul_ps(vnCDEF, vminus_ln2_hi), vxCDEF);
89     __m128 vtGHIJ = _mm_add_ps(_mm_mul_ps(vnGHIJ, vminus_ln2_hi), vxGHIJ);
90 
91     vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
92     vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_lo), vt4567);
93     vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_lo), vt89AB);
94     vtCDEF = _mm_add_ps(_mm_mul_ps(vnCDEF, vminus_ln2_lo), vtCDEF);
95     vtGHIJ = _mm_add_ps(_mm_mul_ps(vnGHIJ, vminus_ln2_lo), vtGHIJ);
96 
97     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
98     __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
99     __m128 vp4567 = _mm_add_ps(_mm_mul_ps(vc5, vt4567), vc4);
100     __m128 vp89AB = _mm_add_ps(_mm_mul_ps(vc5, vt89AB), vc4);
101     __m128 vpCDEF = _mm_add_ps(_mm_mul_ps(vc5, vtCDEF), vc4);
102     __m128 vpGHIJ = _mm_add_ps(_mm_mul_ps(vc5, vtGHIJ), vc4);
103 
104     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
105     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc3);
106     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc3);
107     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc3);
108     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc3);
109 
110     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
111     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc2);
112     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc2);
113     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc2);
114     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc2);
115 
116     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
117     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc1);
118     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc1);
119     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc1);
120     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc1);
121 
122     // Reconstruct the final f value:
123     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
124     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
125     //     = s + (t * s) * p
126     vt0123 = _mm_mul_ps(vt0123, vs0123);
127     vt4567 = _mm_mul_ps(vt4567, vs4567);
128     vt89AB = _mm_mul_ps(vt89AB, vs89AB);
129     vtCDEF = _mm_mul_ps(vtCDEF, vsCDEF);
130     vtGHIJ = _mm_mul_ps(vtGHIJ, vsGHIJ);
131 
132     __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
133     __m128 vf4567 = _mm_add_ps(_mm_mul_ps(vt4567, vp4567), vs4567);
134     __m128 vf89AB = _mm_add_ps(_mm_mul_ps(vt89AB, vp89AB), vs89AB);
135     __m128 vfCDEF = _mm_add_ps(_mm_mul_ps(vtCDEF, vpCDEF), vsCDEF);
136     __m128 vfGHIJ = _mm_add_ps(_mm_mul_ps(vtGHIJ, vpGHIJ), vsGHIJ);
137 
138     // For inputs below zero cutoff, replace output with +0.0f.
139     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
140     vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
141     vf4567 = _mm_andnot_ps(_mm_cmplt_ps(vx4567, vdenorm_cutoff), vf4567);
142     vf89AB = _mm_andnot_ps(_mm_cmplt_ps(vx89AB, vdenorm_cutoff), vf89AB);
143     vfCDEF = _mm_andnot_ps(_mm_cmplt_ps(vxCDEF, vdenorm_cutoff), vfCDEF);
144     vfGHIJ = _mm_andnot_ps(_mm_cmplt_ps(vxGHIJ, vdenorm_cutoff), vfGHIJ);
145 
146     // Store 20 (5x4) outputs at a time.
147     _mm_storeu_ps(output, vf0123);
148     _mm_storeu_ps(output + 4, vf4567);
149     _mm_storeu_ps(output + 8, vf89AB);
150     _mm_storeu_ps(output + 12, vfCDEF);
151     _mm_storeu_ps(output + 16, vfGHIJ);
152     output += 20;
153 
154     // Accumulate computed exponents.
155     vacc0 = _mm_add_ps(vacc0, vf0123);
156     vacc4 = _mm_add_ps(vacc4, vf4567);
157     vacc3 = _mm_add_ps(vacc3, vf89AB);
158     vacc2 = _mm_add_ps(vacc2, vfCDEF);
159     vacc1 = _mm_add_ps(vacc1, vfGHIJ);
160   }
161   // Add up all accumulators to vacc0
162   vacc0 = _mm_add_ps(vacc0, vacc1);
163   vacc2 = _mm_add_ps(vacc2, vacc3);
164   vacc0 = _mm_add_ps(vacc0, vacc2);
165   vacc0 = _mm_add_ps(vacc0, vacc4);
166 
167   __m128 vacc = vacc0;
168   for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
169     // Load 4 inputs at a time.
170     const __m128 vi = _mm_loadu_ps(input);
171     input += 4;
172 
173     // Subtract maximum input x := i - i_max. This implies x <= 0.
174     const __m128 vx = _mm_sub_ps(vi, vi_max);
175 
176     // Compute reduced argument elements := round(x / log(2)).
177     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
178 
179     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
180     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
181     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
182 
183     // Subtract the large number back to get final elements := round(x / log(2)).
184     vn = _mm_sub_ps(vn, vmagic_bias);
185 
186     // Compute reduced argument t := x - elements * log(2).
187     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
188     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
189     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
190 
191     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
192     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
193     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
194     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
195     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
196 
197     // Reconstruct the final f value:
198     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
199     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
200     //     = s + (t * s) * p
201     vt = _mm_mul_ps(vt, vs);
202     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
203 
204     // For inputs below zero cutoff, replace output with +0.0f.
205     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
206     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
207 
208     // Store 4 outputs at a time.
209     _mm_storeu_ps(output, vf);
210     output += 4;
211 
212     // Accumulate computed exponents.
213     vacc = _mm_add_ps(vacc, vf);
214   }
215   if (elements != 0) {
216     assert(elements >= 1 * sizeof(float));
217     assert(elements <= 3 * sizeof(float));
218     // Load 4 inputs at a time.
219     const __m128 vi = _mm_loadu_ps(input);
220 
221     // Subtract maximum input x := i - i_max. This implies x <= 0.
222     const __m128 vx = _mm_sub_ps(vi, vi_max);
223 
224     // Compute reduced argument elements := round(x / log(2)).
225     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
226 
227     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
228     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
229     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
230 
231     // Subtract the large number back to get final elements := round(x / log(2)).
232     vn = _mm_sub_ps(vn, vmagic_bias);
233 
234     // Compute reduced argument t := x - elements * log(2).
235     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
236     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
237     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
238 
239     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
240     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
241     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
242     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
243     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
244 
245     // Reconstruct the final f value:
246     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
247     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
248     //     = s + (t * s) * p
249     vt = _mm_mul_ps(vt, vs);
250     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
251 
252     // For inputs below zero cutoff, replace output with +0.0f.
253     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
254     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
255 
256     if (elements & (2 * sizeof(float))) {
257       // Store 2 outputs at a time.
258       _mm_storel_pi((__m64*) output, vf);
259       output += 2;
260 
261       // Accumulate 2 computed exponents.
262       vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
263 
264       vf = _mm_movehl_ps(vf, vf);
265     }
266     if (elements & (1 * sizeof(float))) {
267       // Store 1 output at a time.
268       _mm_store_ss(output, vf);
269 
270       // Accumulate 1 computed exponent.
271       vacc = _mm_add_ss(vacc, vf);
272     }
273   }
274   // Reduce 4 elements in the SIMD register
275   vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
276   vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
277   _mm_store_ss(sum, vacc);
278 }
279