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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_x4(size_t elements,const float * input,float * output,float * sum,float max)18 void xnn_f32_raddstoreexpminusmax_ukernel__sse2_p5_x4(
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   for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
45     // Load 4 (1x4) inputs at a time.
46     const __m128 vi0123 = _mm_loadu_ps(input);
47     input += 4;
48 
49     // Subtract maximum input x := i - i_max. This implies x <= 0.
50     const __m128 vx0123 = _mm_sub_ps(vi0123, vi_max);
51 
52     // Compute reduced argument elements := round(x / log(2)).
53     __m128 vn0123 = _mm_add_ps(_mm_mul_ps(vx0123, vlog2e), vmagic_bias);
54 
55     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
56     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
57     const __m128 vs0123 = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn0123), 23));
58 
59     // Subtract the large number back to get final elements := round(x / log(2)).
60     vn0123 = _mm_sub_ps(vn0123, vmagic_bias);
61 
62     // Compute reduced argument t := x - elements * log(2).
63     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
64     __m128 vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_hi), vx0123);
65 
66     vt0123 = _mm_add_ps(_mm_mul_ps(vn0123, vminus_ln2_lo), vt0123);
67 
68     // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
69     __m128 vp0123 = _mm_add_ps(_mm_mul_ps(vc5, vt0123), vc4);
70 
71     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc3);
72 
73     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc2);
74 
75     vp0123 = _mm_add_ps(_mm_mul_ps(vp0123, vt0123), vc1);
76 
77     // Reconstruct the final f value:
78     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
79     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
80     //     = s + (t * s) * p
81     vt0123 = _mm_mul_ps(vt0123, vs0123);
82 
83     __m128 vf0123 = _mm_add_ps(_mm_mul_ps(vt0123, vp0123), vs0123);
84 
85     // For inputs below zero cutoff, replace output with +0.0f.
86     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
87     vf0123 = _mm_andnot_ps(_mm_cmplt_ps(vx0123, vdenorm_cutoff), vf0123);
88 
89     // Store 4 (1x4) outputs at a time.
90     _mm_storeu_ps(output, vf0123);
91     output += 4;
92 
93     // Accumulate computed exponents.
94     vacc0 = _mm_add_ps(vacc0, vf0123);
95   }
96 
97   __m128 vacc = vacc0;
98   for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
99     // Load 4 inputs at a time.
100     const __m128 vi = _mm_loadu_ps(input);
101     input += 4;
102 
103     // Subtract maximum input x := i - i_max. This implies x <= 0.
104     const __m128 vx = _mm_sub_ps(vi, vi_max);
105 
106     // Compute reduced argument elements := round(x / log(2)).
107     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
108 
109     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
110     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
111     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
112 
113     // Subtract the large number back to get final elements := round(x / log(2)).
114     vn = _mm_sub_ps(vn, vmagic_bias);
115 
116     // Compute reduced argument t := x - elements * log(2).
117     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
118     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
119     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
120 
121     // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
122     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
123     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
124     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
125     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
126 
127     // Reconstruct the final f value:
128     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
129     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
130     //     = s + (t * s) * p
131     vt = _mm_mul_ps(vt, vs);
132     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
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     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
137 
138     // Store 4 outputs at a time.
139     _mm_storeu_ps(output, vf);
140     output += 4;
141 
142     // Accumulate computed exponents.
143     vacc = _mm_add_ps(vacc, vf);
144   }
145   if (elements != 0) {
146     assert(elements >= 1 * sizeof(float));
147     assert(elements <= 3 * sizeof(float));
148     // Load 4 inputs at a time.
149     const __m128 vi = _mm_loadu_ps(input);
150 
151     // Subtract maximum input x := i - i_max. This implies x <= 0.
152     const __m128 vx = _mm_sub_ps(vi, vi_max);
153 
154     // Compute reduced argument elements := round(x / log(2)).
155     __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e), vmagic_bias);
156 
157     // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e.
158     // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly.
159     const __m128 vs = _mm_castsi128_ps(_mm_slli_epi32(_mm_castps_si128(vn), 23));
160 
161     // Subtract the large number back to get final elements := round(x / log(2)).
162     vn = _mm_sub_ps(vn, vmagic_bias);
163 
164     // Compute reduced argument t := x - elements * log(2).
165     // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
166     __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_hi), vx);
167     vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_lo), vt);
168 
169     // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
170     __m128 vp = _mm_add_ps(_mm_mul_ps(vc5, vt), vc4);
171     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc3);
172     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc2);
173     vp = _mm_add_ps(_mm_mul_ps(vp, vt), vc1);
174 
175     // Reconstruct the final f value:
176     //   f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
177     //     = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
178     //     = s + (t * s) * p
179     vt = _mm_mul_ps(vt, vs);
180     __m128 vf = _mm_add_ps(_mm_mul_ps(vt, vp), vs);
181 
182     // For inputs below zero cutoff, replace output with +0.0f.
183     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
184     vf = _mm_andnot_ps(_mm_cmplt_ps(vx, vdenorm_cutoff), vf);
185 
186     if (elements & (2 * sizeof(float))) {
187       // Store 2 outputs at a time.
188       _mm_storel_pi((__m64*) output, vf);
189       output += 2;
190 
191       // Accumulate 2 computed exponents.
192       vacc = _mm_add_ps(vacc, _mm_movelh_ps(vf, _mm_setzero_ps()));
193 
194       vf = _mm_movehl_ps(vf, vf);
195     }
196     if (elements & (1 * sizeof(float))) {
197       // Store 1 output at a time.
198       _mm_store_ss(output, vf);
199 
200       // Accumulate 1 computed exponent.
201       vacc = _mm_add_ss(vacc, vf);
202     }
203   }
204   // Reduce 4 elements in the SIMD register
205   vacc = _mm_add_ps(vacc, _mm_movehl_ps(vacc, vacc));
206   vacc = _mm_add_ss(vacc, _mm_shuffle_ps(vacc, vacc, _MM_SHUFFLE(2, 3, 0, 1)));
207   _mm_store_ss(sum, vacc);
208 }
209