1// Copyright 2020 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$assert BATCH_TILE % 8 == 0 7$assert BATCH_TILE >= 8 8$SIMD_TILE = BATCH_TILE // 8 9#include <assert.h> 10 11#include <immintrin.h> 12 13#include <xnnpack/common.h> 14#include <xnnpack/vunary.h> 15 16 17extern XNN_INTERNAL const int xnn_table_exp2minus_k_over_16[16]; 18 19static const int32_t mask_table[14] = {-1, -1, -1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 0, 0}; 20 21void xnn_f32_velu_ukernel__avx2_rr1_lut16_p3_gather_x${BATCH_TILE}( 22 size_t n, 23 const float* x, 24 float* y, 25 const union xnn_f32_elu_params params[restrict XNN_MIN_ELEMENTS(1)]) 26{ 27 assert(n % sizeof(float) == 0); 28 29 const __m256 vprescale = _mm256_broadcast_ps((const __m128*) params->sse.prescale); 30 const __m256 valpha = _mm256_broadcast_ps((const __m128*) params->sse.alpha); 31 const __m256 vbeta = _mm256_broadcast_ps((const __m128*) params->sse.beta); 32 33 const __m256 vsat_cutoff = _mm256_set1_ps(-0x1.154246p+4f); 34 const __m256 vmagic_bias = _mm256_set1_ps(0x1.800000p19f); 35 const __m256 vlog2e = _mm256_set1_ps(0x1.715476p+0f); 36 const __m256i vindex_mask = _mm256_set1_epi32(0xF); 37 const __m256 vminus_ln2 = _mm256_set1_ps(-0x1.62E43p-1f); 38 const __m256 vc3 = _mm256_set1_ps(0x1.55561Cp-3f); 39 const __m256 vc2 = _mm256_set1_ps(0x1.0001ECp-1f); 40 41 $if BATCH_TILE > 8: 42 for (; n >= ${BATCH_TILE} * sizeof(float); n -= ${BATCH_TILE} * sizeof(float)) { 43 __m256 vx0 = _mm256_loadu_ps(x); 44 $for N in range(1, SIMD_TILE): 45 __m256 vx${N} = _mm256_loadu_ps(x + ${N * 8}); 46 x += ${BATCH_TILE}; 47 48 $for N in range(SIMD_TILE): 49 const __m256 vz${N} = _mm256_max_ps(vsat_cutoff, _mm256_mul_ps(vx${N}, vprescale)); 50 51 $for N in range(SIMD_TILE): 52 __m256 vn${N} = _mm256_fmadd_ps(vz${N}, vlog2e, vmagic_bias); 53 54 $for N in range(SIMD_TILE): 55 const __m256i vidx${N} = _mm256_and_si256(_mm256_castps_si256(vn${N}), vindex_mask); 56 const __m256i vl${N} = _mm256_i32gather_epi32(xnn_table_exp2minus_k_over_16, vidx${N}, sizeof(float)); 57 58 $for N in range(SIMD_TILE): 59 const __m256i ven${N} = _mm256_slli_epi32(_mm256_castps_si256(vn${N}), 19); 60 vn${N} = _mm256_sub_ps(vn${N}, vmagic_bias); 61 62 $for N in range(SIMD_TILE): 63 __m256 vs${N} = _mm256_castsi256_ps(_mm256_add_epi32(vl${N}, ven${N})); 64 __m256 vt${N} = _mm256_fmadd_ps(vn${N}, vminus_ln2, vz${N}); 65 66 $for N in range(SIMD_TILE): 67 __m256 vp${N} = _mm256_fmadd_ps(vc3, vt${N}, vc2); 68 69 $for N in range(SIMD_TILE): 70 vp${N} = _mm256_mul_ps(vp${N}, vt${N}); 71 vt${N} = _mm256_mul_ps(vt${N}, vs${N}); 72 73 $for N in range(SIMD_TILE): 74 vs${N} = _mm256_fmsub_ps(vs${N}, valpha, valpha); 75 vp${N} = _mm256_fmadd_ps(vp${N}, vt${N}, vt${N}); 76 77 $for N in range(SIMD_TILE): 78 const __m256 ve${N} = _mm256_fmadd_ps(vp${N}, valpha, vs${N}); 79 vx${N} = _mm256_mul_ps(vx${N}, vbeta); 80 81 $for N in range(SIMD_TILE): 82 const __m256 vy${N} = _mm256_blendv_ps(vx${N}, ve${N}, vx${N}); 83 84 _mm256_storeu_ps(y, vy0); 85 $for N in range(1, SIMD_TILE): 86 _mm256_storeu_ps(y + ${N * 8}, vy${N}); 87 y += ${BATCH_TILE}; 88 } 89 for (; n >= 8 * sizeof(float); n -= 8 * sizeof(float)) { 90 __m256 vx = _mm256_loadu_ps(x); 91 x += 8; 92 93 const __m256 vz = _mm256_max_ps(vsat_cutoff, _mm256_mul_ps(vx, vprescale)); 94 95 __m256 vn = _mm256_fmadd_ps(vz, vlog2e, vmagic_bias); 96 const __m256i vidx = _mm256_and_si256(_mm256_castps_si256(vn), vindex_mask); 97 const __m256i vl = _mm256_i32gather_epi32(xnn_table_exp2minus_k_over_16, vidx, sizeof(float)); 98 99 const __m256i ven = _mm256_slli_epi32(_mm256_castps_si256(vn), 19); 100 vn = _mm256_sub_ps(vn, vmagic_bias); 101 102 __m256 vs = _mm256_castsi256_ps(_mm256_add_epi32(vl, ven)); 103 __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2, vz); 104 105 __m256 vp = _mm256_fmadd_ps(vc3, vt, vc2); 106 vp = _mm256_mul_ps(vp, vt); 107 108 vt = _mm256_mul_ps(vt, vs); 109 vs = _mm256_fmsub_ps(vs, valpha, valpha); 110 vp = _mm256_fmadd_ps(vp, vt, vt); 111 const __m256 ve = _mm256_fmadd_ps(vp, valpha, vs); 112 113 vx = _mm256_mul_ps(vx, vbeta); 114 const __m256 vy = _mm256_blendv_ps(vx, ve, vx); 115 116 _mm256_storeu_ps(y, vy); 117 y += 8; 118 } 119 if XNN_UNLIKELY(n != 0) { 120 assert(n >= 1 * sizeof(float)); 121 assert(n <= 7 * sizeof(float)); 122 __m256i vmask = _mm256_loadu_si256((const __m256i*) ((uintptr_t) &mask_table[7] - n)); 123 124 __m256 vx = _mm256_maskload_ps(x, vmask); 125 126 const __m256 vz = _mm256_max_ps(vsat_cutoff, _mm256_mul_ps(vx, vprescale)); 127 128 __m256 vn = _mm256_fmadd_ps(vz, vlog2e, vmagic_bias); 129 const __m256i vidx = _mm256_and_si256(_mm256_castps_si256(vn), vindex_mask); 130 const __m256i vl = _mm256_i32gather_epi32(xnn_table_exp2minus_k_over_16, vidx, sizeof(float)); 131 132 const __m256i ven = _mm256_slli_epi32(_mm256_castps_si256(vn), 19); 133 vn = _mm256_sub_ps(vn, vmagic_bias); 134 135 __m256 vs = _mm256_castsi256_ps(_mm256_add_epi32(vl, ven)); 136 __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2, vz); 137 138 __m256 vp = _mm256_fmadd_ps(vc3, vt, vc2); 139 vp = _mm256_mul_ps(vp, vt); 140 141 vt = _mm256_mul_ps(vt, vs); 142 vs = _mm256_fmsub_ps(vs, valpha, valpha); 143 vp = _mm256_fmadd_ps(vp, vt, vt); 144 const __m256 ve = _mm256_fmadd_ps(vp, valpha, vs); 145 146 vx = _mm256_mul_ps(vx, vbeta); 147 const __m256 vy = _mm256_blendv_ps(vx, ve, vx); 148 149 // _mm256_maskstore_ps(y, vmask, vf) could be used here, but triggers msan failures (probably an msan bug). 150 __m128 vy_lo = _mm256_castps256_ps128(vy); 151 if (n & (4 * sizeof(float))) { 152 _mm_storeu_ps(y, vy_lo); 153 vy_lo = _mm256_extractf128_ps(vy, 1); 154 y += 4; 155 } 156 if (n & (2 * sizeof(float))) { 157 _mm_storel_pi((__m64*) y, vy_lo); 158 vy_lo = _mm_movehl_ps(vy_lo, vy_lo); 159 y += 2; 160 } 161 if (n & (1 * sizeof(float))) { 162 _mm_store_ss(y, vy_lo); 163 } 164 } 165} 166