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1// Copyright 2019 Google LLC
2//
3// This source code is licensed under the BSD-style license found in the
4// LICENSE file in the root directory of this source tree.
5
6$assert ELEMENTS_TILE % 16 == 0
7$assert ELEMENTS_TILE >= 16
8$SIMD_TILE = ELEMENTS_TILE // 16
9$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
10#include <assert.h>
11
12#include <immintrin.h>
13
14#include <xnnpack/intrinsics-polyfill.h>
15#include <xnnpack/raddstoreexpminusmax.h>
16
17
18void xnn_f32_raddstoreexpminusmax_ukernel__avx512f_p5_scalef_x${ELEMENTS_TILE}${"" if ACCUMULATORS == 1 else "_acc%d" % ACCUMULATORS}(
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 __m512 vlog2e = _mm512_set1_ps(0x1.715476p+0f);
28  const __m512 vminus_ln2_hi = _mm512_set1_ps(-0x1.62E43p-1f);
29  const __m512 vminus_ln2_lo = _mm512_set1_ps(0x1.05C61p-29f);
30
31  const __m512 vc0 = _mm512_set1_ps(1.0f);
32  const __m512 vc1 = _mm512_set1_ps(0x1.FFFFF6p-1f);
33  const __m512 vc2 = _mm512_set1_ps(0x1.FFFDC6p-2f);
34  const __m512 vc3 = _mm512_set1_ps(0x1.555A80p-3f);
35  const __m512 vc4 = _mm512_set1_ps(0x1.573A1Ap-5f);
36  const __m512 vc5 = _mm512_set1_ps(0x1.0F9F9Cp-7f);
37
38  const __m512 vi_max = _mm512_set1_ps(max);
39
40  $for K in range(ACCUMULATORS):
41    __m512 vacc${K} = _mm512_setzero_ps();
42  for (; elements >= ${ELEMENTS_TILE} * sizeof(float); elements -= ${ELEMENTS_TILE} * sizeof(float)) {
43    // Load ${ELEMENTS_TILE} (${SIMD_TILE}x16) inputs at a time.
44    const __m512 vi0 = _mm512_loadu_ps(input);
45    $for N in range(1, SIMD_TILE):
46      const __m512 vi${N} = _mm512_loadu_ps(input + ${N * 16});
47    input += ${ELEMENTS_TILE};
48
49    // Subtract maximum input x := i - i_max.
50    $for N in range(SIMD_TILE):
51      const __m512 vx${N} = _mm512_sub_ps(vi${N}, vi_max);
52
53    // Compute reduced argument elements := round(x / log(2)).
54    $for N in range(SIMD_TILE):
55      const __m512 vn${N} = _mm512_roundscale_ps(_mm512_mul_ps(vx${N}, vlog2e), 0);
56
57    // Compute reduced argument t := x - elements * log(2).
58    // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
59    $for N in range(SIMD_TILE):
60      __m512 vt${N} = _mm512_fmadd_ps(vn${N}, vminus_ln2_hi, vx${N});
61
62    $for N in range(SIMD_TILE):
63      vt${N} = _mm512_fmadd_ps(vn${N}, vminus_ln2_lo, vt${N});
64
65    // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
66    $for N in range(SIMD_TILE):
67      __m512 vp${N} = _mm512_fmadd_ps(vc5, vt${N}, vc4);
68
69    $for N in range(SIMD_TILE):
70      vp${N} = _mm512_fmadd_ps(vp${N}, vt${N}, vc3);
71
72    $for N in range(SIMD_TILE):
73      vp${N} = _mm512_fmadd_ps(vp${N}, vt${N}, vc2);
74
75    $for N in range(SIMD_TILE):
76      vp${N} = _mm512_fmadd_ps(vp${N}, vt${N}, vc1);
77
78    $for N in range(SIMD_TILE):
79      vp${N} = _mm512_fmadd_ps(vp${N}, vt${N}, vc0);
80
81    // Reconstruct the final f value:
82    //   f = 2**elements * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
83    //     = 2**elements * p
84    $for N in range(SIMD_TILE):
85      const __m512 vf${N} = _mm512_scalef_ps(vp${N}, vn${N});
86
87    // Store ${ELEMENTS_TILE} (${SIMD_TILE}x16) outputs at a time.
88    _mm512_storeu_ps(output, vf0);
89    $for N in range(1, SIMD_TILE):
90      _mm512_storeu_ps(output + ${N * 16}, vf${N});
91    output += ${ELEMENTS_TILE};
92
93    // Accumulate computed exponents.
94    $for N in range(SIMD_TILE):
95      vacc${N % ACCUMULATORS} = _mm512_add_ps(vacc${N % ACCUMULATORS}, vf${N});
96  }
97  $if ACCUMULATORS > 1:
98    // Add up all accumulators to vacc0
99    $ACC_SLICE = 1
100    $while ACC_SLICE < ACCUMULATORS:
101      $for A in range(0, ACCUMULATORS, ACC_SLICE * 2):
102        $if A + ACC_SLICE < ACCUMULATORS:
103          vacc${A} = _mm512_add_ps(vacc${A}, vacc${A + ACC_SLICE});
104      $ACC_SLICE *= 2
105
106  __m512 vacc = vacc0;
107  for (; elements >= 16 * sizeof(float); elements -= 16 * sizeof(float)) {
108    // Load 16 inputs at a time.
109    const __m512 vi = _mm512_loadu_ps(input);
110    input += 16;
111
112    // Subtract maximum input x := i - i_max.
113    const __m512 vx = _mm512_sub_ps(vi, vi_max);
114
115    // Compute reduced argument elements := round(x / log(2)).
116    const __m512 vn = _mm512_roundscale_ps(_mm512_mul_ps(vx, vlog2e), 0);
117
118    // Compute reduced argument t := x - elements * log(2).
119    // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
120    __m512 vt = _mm512_fmadd_ps(vn, vminus_ln2_hi, vx);
121    vt = _mm512_fmadd_ps(vn, vminus_ln2_lo, vt);
122
123    // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
124    __m512 vp = _mm512_fmadd_ps(vc5, vt, vc4);
125    vp = _mm512_fmadd_ps(vp, vt, vc3);
126    vp = _mm512_fmadd_ps(vp, vt, vc2);
127    vp = _mm512_fmadd_ps(vp, vt, vc1);
128    vp = _mm512_fmadd_ps(vp, vt, vc0);
129
130    // Reconstruct the final f value:
131    //   f = 2**elements * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
132    //     = 2**elements * p
133    const __m512 vf = _mm512_scalef_ps(vp, vn);
134
135    // Store 16 outputs at a time.
136    _mm512_storeu_ps(output, vf);
137    output += 16;
138
139    // Accumulate computed exponents.
140    vacc = _mm512_add_ps(vacc, vf);
141  }
142  if (elements != 0) {
143    // Prepare mask for valid 32-bit elements (depends on elements).
144    elements >>= 2 /* log2(sizeof(float)) */;
145    const __mmask16 vmask = _cvtu32_mask16((uint16_t) ((uint32_t) (UINT32_C(1) << elements) - UINT32_C(1)));
146
147    // Load up to 15 inputs at a time.
148    const __m512 vi = _mm512_maskz_loadu_ps(vmask, input);
149
150    // Subtract maximum input x := i - i_max.
151    const __m512 vx = _mm512_sub_ps(vi, vi_max);
152
153    // Compute reduced argument elements := round(x / log(2)).
154    const __m512 vn = _mm512_roundscale_ps(_mm512_mul_ps(vx, vlog2e), 0);
155
156    // Compute reduced argument t := x - elements * log(2).
157    // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
158    __m512 vt = _mm512_fmadd_ps(vn, vminus_ln2_hi, vx);
159    vt = _mm512_fmadd_ps(vn, vminus_ln2_lo, vt);
160
161    // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
162    __m512 vp = _mm512_fmadd_ps(vc5, vt, vc4);
163    vp = _mm512_fmadd_ps(vp, vt, vc3);
164    vp = _mm512_fmadd_ps(vp, vt, vc2);
165    vp = _mm512_fmadd_ps(vp, vt, vc1);
166    vp = _mm512_fmadd_ps(vp, vt, vc0);
167
168    // Reconstruct the final f value:
169    //   f = 2**elements * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
170    //     = 2**elements * p
171    const __m512 vf = _mm512_scalef_ps(vp, vn);
172
173    // Store up to 15 outputs at a time.
174    _mm512_mask_storeu_ps(output, vmask, vf);
175
176    // Accumulate computed exponents.
177    vacc = _mm512_mask_add_ps(vacc, vmask, vacc, vf);
178  }
179  *sum = _mm512_reduce_add_ps(vacc);
180}
181