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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_x12_acc3(size_t elements,const float * input,float * output,float * sum,float max)18 void xnn_f32_raddstoreexpminusmax_ukernel__sse2_p5_x12_acc3(
19     size_t elements,
20     const float* input,
21     float* output,
22     float* sum,
23     float max)
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   for (; elements >= 12 * sizeof(float); elements -= 12 * sizeof(float)) {
47     // Load 12 (3x4) inputs at a time.
48     const __m128 vi0123 = _mm_loadu_ps(input);
49     const __m128 vi4567 = _mm_loadu_ps(input + 4);
50     const __m128 vi89AB = _mm_loadu_ps(input + 8);
51     input += 12;
52 
53     // Subtract maximum input x := i - i_max. This implies x <= 0.
54     const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
55     const __m128 vx4567 = _mm_sub_ps(vi4567, vi_max);
56     const __m128 vx89AB = _mm_sub_ps(vi89AB, vi_max);
57 
58     // Compute reduced argument elements := round(x / log(2)).
59     __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
60     __m128 vn4567 = _mm_add_ps(_mm_mul_ps(vx4567, vlog2e), vmagic_bias);
61     __m128 vn89AB = _mm_add_ps(_mm_mul_ps(vx89AB, vlog2e), vmagic_bias);
62 
63     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
64     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
65     const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
66     const __m128 vs4567 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn4567), 23));
67     const __m128 vs89AB = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn89AB), 23));
68 
69     // Subtract the large number back to get final elements := round(x / log(2)).
70     vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
71     vn4567 = _mm_sub_ps(vn4567, vmagic_bias);
72     vn89AB = _mm_sub_ps(vn89AB, vmagic_bias);
73 
74     // Compute reduced argument t := x - elements * log(2).
75     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
76     __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
77     __m128 vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_hi), vx4567);
78     __m128 vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_hi), vx89AB);
79 
80     vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
81     vt4567 = _mm_add_ps(_mm_mul_ps(vn4567, vminus_ln2_lo), vt4567);
82     vt89AB = _mm_add_ps(_mm_mul_ps(vn89AB, vminus_ln2_lo), vt89AB);
83 
84     // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
85     __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
86     __m128 vp4567 = _mm_add_ps(_mm_mul_ps(vc5, vt4567), vc4);
87     __m128 vp89AB = _mm_add_ps(_mm_mul_ps(vc5, vt89AB), vc4);
88 
89     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
90     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc3);
91     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc3);
92 
93     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
94     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc2);
95     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc2);
96 
97     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
98     vp4567 = _mm_add_ps(_mm_mul_ps(vp4567, vt4567), vc1);
99     vp89AB = _mm_add_ps(_mm_mul_ps(vp89AB, vt89AB), vc1);
100 
101     // Reconstruct the final f value:
102     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
103     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
104     //     = s + (t * s) * p
105     vt0123 = _mm_mul_ps(vt0123, vs0123);
106     vt4567 = _mm_mul_ps(vt4567, vs4567);
107     vt89AB = _mm_mul_ps(vt89AB, vs89AB);
108 
109     __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
110     __m128 vf4567 = _mm_add_ps(_mm_mul_ps(vt4567, vp4567), vs4567);
111     __m128 vf89AB = _mm_add_ps(_mm_mul_ps(vt89AB, vp89AB), vs89AB);
112 
113     // For inputs below zero cutoff, replace output with +0.0f.
114     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
115     vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
116     vf4567 = _mm_andnot_ps(_mm_cmplt_ps(vx4567, vdenorm_cutoff), vf4567);
117     vf89AB = _mm_andnot_ps(_mm_cmplt_ps(vx89AB, vdenorm_cutoff), vf89AB);
118 
119     // Store 12 (3x4) outputs at a time.
120     _mm_storeu_ps(output, vf0123);
121     _mm_storeu_ps(output + 4, vf4567);
122     _mm_storeu_ps(output + 8, vf89AB);
123     output += 12;
124 
125     // Accumulate computed exponents.
126     vacc0 = _mm_add_ps(vacc0, vf0123);
127     vacc1 = _mm_add_ps(vacc1, vf4567);
128     vacc2 = _mm_add_ps(vacc2, vf89AB);
129   }
130   // Add up all accumulators to vacc0
131   vacc0 = _mm_add_ps(vacc0, vacc1);
132   vacc0 = _mm_add_ps(vacc0, vacc2);
133 
134   __m128 vacc = vacc0;
135   for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
136     // Load 4 inputs at a time.
137     const __m128 vi = _mm_loadu_ps(input);
138     input += 4;
139 
140     // Subtract maximum input x := i - i_max. This implies x <= 0.
141     const __m128 vx = _mm_sub_ps(vi, vi_max);
142 
143     // Compute reduced argument elements := round(x / log(2)).
144     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
145 
146     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
147     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
148     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
149 
150     // Subtract the large number back to get final elements := round(x / log(2)).
151     vn = _mm_sub_ps(vn, vmagic_bias);
152 
153     // Compute reduced argument t := x - elements * log(2).
154     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
155     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
156     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
157 
158     // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
159     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
160     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
161     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
162     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
163 
164     // Reconstruct the final f value:
165     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
166     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
167     //     = s + (t * s) * p
168     vt = _mm_mul_ps(vt, vs);
169     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
170 
171     // For inputs below zero cutoff, replace output with +0.0f.
172     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
173     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
174 
175     // Store 4 outputs at a time.
176     _mm_storeu_ps(output, vf);
177     output += 4;
178 
179     // Accumulate computed exponents.
180     vacc = _mm_add_ps(vacc, vf);
181   }
182   if (elements != 0) {
183     assert(elements >= 1 * sizeof(float));
184     assert(elements <= 3 * sizeof(float));
185     // Load 4 inputs at a time.
186     const __m128 vi = _mm_loadu_ps(input);
187 
188     // Subtract maximum input x := i - i_max. This implies x <= 0.
189     const __m128 vx = _mm_sub_ps(vi, vi_max);
190 
191     // Compute reduced argument elements := round(x / log(2)).
192     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
193 
194     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
195     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
196     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
197 
198     // Subtract the large number back to get final elements := round(x / log(2)).
199     vn = _mm_sub_ps(vn, vmagic_bias);
200 
201     // Compute reduced argument t := x - elements * log(2).
202     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
203     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
204     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
205 
206     // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
207     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
208     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
209     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
210     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
211 
212     // Reconstruct the final f value:
213     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
214     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
215     //     = s + (t * s) * p
216     vt = _mm_mul_ps(vt, vs);
217     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
218 
219     // For inputs below zero cutoff, replace output with +0.0f.
220     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
221     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
222 
223     if (elements & (2 * sizeof(float))) {
224       // Store 2 outputs at a time.
225       _mm_storel_pi((__m64*) output, vf);
226       output += 2;
227 
228       // Accumulate 2 computed exponents.
229       vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
230 
231       vf = _mm_movehl_ps(vf, vf);
232     }
233     if (elements & (1 * sizeof(float))) {
234       // Store 1 output at a time.
235       _mm_store_ss(output, vf);
236 
237       // Accumulate 1 computed exponent.
238       vacc = _mm_add_ss(vacc, vf);
239     }
240   }
241   // Reduce 4 elements in the SIMD register
242   vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
243   vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
244   _mm_store_ss(sum, vacc);
245 }
246