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1 // Auto-generated file. Do not edit!
2 //   Template: src/f32-raddstoreexpminusmax/sse2-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_p5_x20_acc5(size_t elements,const float * input,float * output,float * sum,float max)18 void xnn_f32_raddstoreexpminusmax_ukernel__sse2_p5_x20_acc5(
19     size_t elements,
20     const float* input,
21     float* output,
22     float* sum,
23     float max) XNN_DISABLE_TSAN
24 {
25   assert(elements % sizeof(float) == 0);
26 
27   const __m128 vmagic_bias = _mm_set1_ps(0x1.8000FEp23f);
28   // The smallest x for which expf(x) is normalized.
29   const __m128 vdenorm_cutoff = _mm_set1_ps(-0x1.5D589Ep6f);
30   const __m128 vlog2e = _mm_set1_ps(0x1.715476p+0f);
31   // Last 7 bits are zeroes
32   const __m128 vminus_ln2_hi = _mm_set1_ps(-0x1.62E400p-1f);
33   const __m128 vminus_ln2_lo = _mm_set1_ps(-0x1.7F7D1Cp-20f);
34 
35   const __m128 vc1 = _mm_set1_ps(0x1.FFFFF6p-1f);
36   const __m128 vc2 = _mm_set1_ps(0x1.FFFDC6p-2f);
37   const __m128 vc3 = _mm_set1_ps(0x1.555A80p-3f);
38   const __m128 vc4 = _mm_set1_ps(0x1.573A1Ap-5f);
39   const __m128 vc5 = _mm_set1_ps(0x1.0F9F9Cp-7f);
40 
41   const __m128 vi_max = _mm_set1_ps(max);
42 
43   __m128 vacc0 = _mm_setzero_ps();
44   __m128 vacc1 = _mm_setzero_ps();
45   __m128 vacc2 = _mm_setzero_ps();
46   __m128 vacc3 = _mm_setzero_ps();
47   __m128 vacc4 = _mm_setzero_ps();
48   for (; elements >= 20 * sizeof(float); elements -= 20 * sizeof(float)) {
49     // Load 20 (5x4) inputs at a time.
50     const __m128 vi0123 = _mm_loadu_ps(input);
51     const __m128 vi4567 = _mm_loadu_ps(input + 4);
52     const __m128 vi89AB = _mm_loadu_ps(input + 8);
53     const __m128 viCDEF = _mm_loadu_ps(input + 12);
54     const __m128 viGHIJ = _mm_loadu_ps(input + 16);
55     input += 20;
56 
57     // Subtract maximum input x := i - i_max. This implies x <= 0.
58     const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
59     const __m128 vx4567 = _mm_sub_ps(vi4567, vi_max);
60     const __m128 vx89AB = _mm_sub_ps(vi89AB, vi_max);
61     const __m128 vxCDEF = _mm_sub_ps(viCDEF, vi_max);
62     const __m128 vxGHIJ = _mm_sub_ps(viGHIJ, vi_max);
63 
64     // Compute reduced argument elements := round(x / log(2)).
65     __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
66     __m128 vn4567 = _mm_add_ps(_mm_mul_ps(vx4567, vlog2e), vmagic_bias);
67     __m128 vn89AB = _mm_add_ps(_mm_mul_ps(vx89AB, vlog2e), vmagic_bias);
68     __m128 vnCDEF = _mm_add_ps(_mm_mul_ps(vxCDEF, vlog2e), vmagic_bias);
69     __m128 vnGHIJ = _mm_add_ps(_mm_mul_ps(vxGHIJ, vlog2e), vmagic_bias);
70 
71     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
72     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
73     const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
74     const __m128 vs4567 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn4567), 23));
75     const __m128 vs89AB = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn89AB), 23));
76     const __m128 vsCDEF = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vnCDEF), 23));
77     const __m128 vsGHIJ = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vnGHIJ), 23));
78 
79     // Subtract the large number back to get final elements := round(x / log(2)).
80     vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
81     vn4567 = _mm_sub_ps(vn4567, vmagic_bias);
82     vn89AB = _mm_sub_ps(vn89AB, vmagic_bias);
83     vnCDEF = _mm_sub_ps(vnCDEF, vmagic_bias);
84     vnGHIJ = _mm_sub_ps(vnGHIJ, vmagic_bias);
85 
86     // Compute reduced argument t := x - elements * log(2).
87     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
88     __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
89     __m128 vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_hi), vx4567);
90     __m128 vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_hi), vx89AB);
91     __m128 vtCDEF = _mm_add_ps(_mm_mul_ps(vnCDEF, vminus_ln2_hi), vxCDEF);
92     __m128 vtGHIJ = _mm_add_ps(_mm_mul_ps(vnGHIJ, vminus_ln2_hi), vxGHIJ);
93 
94     vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
95     vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_lo), vt4567);
96     vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_lo), vt89AB);
97     vtCDEF = _mm_add_ps(_mm_mul_ps(vnCDEF, vminus_ln2_lo), vtCDEF);
98     vtGHIJ = _mm_add_ps(_mm_mul_ps(vnGHIJ, vminus_ln2_lo), vtGHIJ);
99 
100     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
101     __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
102     __m128 vp4567 = _mm_add_ps(_mm_mul_ps(vc5, vt4567), vc4);
103     __m128 vp89AB = _mm_add_ps(_mm_mul_ps(vc5, vt89AB), vc4);
104     __m128 vpCDEF = _mm_add_ps(_mm_mul_ps(vc5, vtCDEF), vc4);
105     __m128 vpGHIJ = _mm_add_ps(_mm_mul_ps(vc5, vtGHIJ), vc4);
106 
107     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
108     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc3);
109     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc3);
110     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc3);
111     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc3);
112 
113     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
114     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc2);
115     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc2);
116     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc2);
117     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc2);
118 
119     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
120     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc1);
121     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc1);
122     vpCDEF = _mm_add_ps(_mm_mul_ps(vpCDEF, vtCDEF), vc1);
123     vpGHIJ = _mm_add_ps(_mm_mul_ps(vpGHIJ, vtGHIJ), vc1);
124 
125     // Reconstruct the final f value:
126     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
127     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
128     //     = s + (t * s) * p
129     vt0123 = _mm_mul_ps(vt0123, vs0123);
130     vt4567 = _mm_mul_ps(vt4567, vs4567);
131     vt89AB = _mm_mul_ps(vt89AB, vs89AB);
132     vtCDEF = _mm_mul_ps(vtCDEF, vsCDEF);
133     vtGHIJ = _mm_mul_ps(vtGHIJ, vsGHIJ);
134 
135     __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
136     __m128 vf4567 = _mm_add_ps(_mm_mul_ps(vt4567, vp4567), vs4567);
137     __m128 vf89AB = _mm_add_ps(_mm_mul_ps(vt89AB, vp89AB), vs89AB);
138     __m128 vfCDEF = _mm_add_ps(_mm_mul_ps(vtCDEF, vpCDEF), vsCDEF);
139     __m128 vfGHIJ = _mm_add_ps(_mm_mul_ps(vtGHIJ, vpGHIJ), vsGHIJ);
140 
141     // For inputs below zero cutoff, replace output with +0.0f.
142     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
143     vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
144     vf4567 = _mm_andnot_ps(_mm_cmplt_ps(vx4567, vdenorm_cutoff), vf4567);
145     vf89AB = _mm_andnot_ps(_mm_cmplt_ps(vx89AB, vdenorm_cutoff), vf89AB);
146     vfCDEF = _mm_andnot_ps(_mm_cmplt_ps(vxCDEF, vdenorm_cutoff), vfCDEF);
147     vfGHIJ = _mm_andnot_ps(_mm_cmplt_ps(vxGHIJ, vdenorm_cutoff), vfGHIJ);
148 
149     // Store 20 (5x4) outputs at a time.
150     _mm_storeu_ps(output, vf0123);
151     _mm_storeu_ps(output + 4, vf4567);
152     _mm_storeu_ps(output + 8, vf89AB);
153     _mm_storeu_ps(output + 12, vfCDEF);
154     _mm_storeu_ps(output + 16, vfGHIJ);
155     output += 20;
156 
157     // Accumulate computed exponents.
158     vacc0 = _mm_add_ps(vacc0, vf0123);
159     vacc4 = _mm_add_ps(vacc4, vf4567);
160     vacc3 = _mm_add_ps(vacc3, vf89AB);
161     vacc2 = _mm_add_ps(vacc2, vfCDEF);
162     vacc1 = _mm_add_ps(vacc1, vfGHIJ);
163   }
164   // Add up all accumulators to vacc0
165   vacc0 = _mm_add_ps(vacc0, vacc1);
166   vacc2 = _mm_add_ps(vacc2, vacc3);
167   vacc0 = _mm_add_ps(vacc0, vacc2);
168   vacc0 = _mm_add_ps(vacc0, vacc4);
169 
170   __m128 vacc = vacc0;
171   for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
172     // Load 4 inputs at a time.
173     const __m128 vi = _mm_loadu_ps(input);
174     input += 4;
175 
176     // Subtract maximum input x := i - i_max. This implies x <= 0.
177     const __m128 vx = _mm_sub_ps(vi, vi_max);
178 
179     // Compute reduced argument elements := round(x / log(2)).
180     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
181 
182     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
183     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
184     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
185 
186     // Subtract the large number back to get final elements := round(x / log(2)).
187     vn = _mm_sub_ps(vn, vmagic_bias);
188 
189     // Compute reduced argument t := x - elements * log(2).
190     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
191     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
192     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
193 
194     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
195     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
196     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
197     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
198     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
199 
200     // Reconstruct the final f value:
201     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
202     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
203     //     = s + (t * s) * p
204     vt = _mm_mul_ps(vt, vs);
205     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
206 
207     // For inputs below zero cutoff, replace output with +0.0f.
208     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
209     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
210 
211     // Store 4 outputs at a time.
212     _mm_storeu_ps(output, vf);
213     output += 4;
214 
215     // Accumulate computed exponents.
216     vacc = _mm_add_ps(vacc, vf);
217   }
218   if (elements != 0) {
219     assert(elements >= 1 * sizeof(float));
220     assert(elements <= 3 * sizeof(float));
221     // Load 4 inputs at a time.
222     const __m128 vi = _mm_loadu_ps(input);
223 
224     // Subtract maximum input x := i - i_max. This implies x <= 0.
225     const __m128 vx = _mm_sub_ps(vi, vi_max);
226 
227     // Compute reduced argument elements := round(x / log(2)).
228     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
229 
230     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
231     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
232     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
233 
234     // Subtract the large number back to get final elements := round(x / log(2)).
235     vn = _mm_sub_ps(vn, vmagic_bias);
236 
237     // Compute reduced argument t := x - elements * log(2).
238     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
239     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
240     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
241 
242     // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2].
243     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
244     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
245     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
246     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
247 
248     // Reconstruct the final f value:
249     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
250     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
251     //     = s + (t * s) * p
252     vt = _mm_mul_ps(vt, vs);
253     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
254 
255     // For inputs below zero cutoff, replace output with +0.0f.
256     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
257     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
258 
259     if (elements & (2 * sizeof(float))) {
260       // Store 2 outputs at a time.
261       _mm_storel_pi((__m64*) output, vf);
262       output += 2;
263 
264       // Accumulate 2 computed exponents.
265       vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
266 
267       vf = _mm_movehl_ps(vf, vf);
268     }
269     if (elements & (1 * sizeof(float))) {
270       // Store 1 output at a time.
271       _mm_store_ss(output, vf);
272 
273       // Accumulate 1 computed exponent.
274       vacc = _mm_add_ss(vacc, vf);
275     }
276   }
277   // Reduce 4 elements in the SIMD register
278   vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
279   vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
280   _mm_store_ss(sum, vacc);
281 }
282