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$assert NR % 4 == 0 7$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ" 8#include <assert.h> 9 10#include <wasm_simd128.h> 11 12#include <xnnpack/gemm.h> 13 14 15$assert ACTIVATION in ["LINEAR", "RELU", "MINMAX"] 16$ACTIVATION_SUFFIX = {"LINEAR": ""}.get(ACTIVATION, "_" + ACTIVATION.lower()) 17$ARCH_SUFFIX = "" if ACTIVATION in ["LINEAR", "RELU"] else "_x86" if X86 else "_arm" 18$PARAMS = {"LINEAR": "xnn_f32_default_params", "RELU": "xnn_f32_relu_params", "MINMAX": "xnn_f32_minmax_params"}[ACTIVATION] 19void xnn_f32_gemm${"inc" if INC else ""}${ACTIVATION_SUFFIX}_ukernel_${MR}x${NR}s4__wasmsimd${ARCH_SUFFIX}( 20 size_t mr, 21 size_t nc, 22 size_t kc, 23 const float*restrict a, 24 size_t a_stride, 25 const float*restrict w, 26 float*restrict c, 27 size_t cm_stride, 28 size_t cn_stride, 29 $if INC: 30 const float*restrict acc, 31 const union ${PARAMS} params[restrict XNN_MIN_ELEMENTS(1)]) 32{ 33 assert(mr != 0); 34 assert(mr <= ${MR}); 35 assert(nc != 0); 36 assert(kc != 0); 37 assert(kc % sizeof(float) == 0); 38 assert(a != NULL); 39 assert(w != NULL); 40 assert(c != NULL); 41 $if INC: 42 assert(acc != NULL); 43 44 const float* a0 = a; 45 float* c0 = c; 46 $for M in range(1, MR): 47 const float* a${M} = (const float*) ((uintptr_t) a${M-1} + a_stride); 48 float* c${M} = (float*) ((uintptr_t) c${M-1} + cm_stride); 49 $if M % 2 == 0: 50 if XNN_UNPREDICTABLE(mr <= ${M}) { 51 a${M} = a${M-1}; 52 c${M} = c${M-1}; 53 } 54 $elif M + 1 == MR: 55 if XNN_UNPREDICTABLE(mr != ${M+1}) { 56 a${M} = a${M-1}; 57 c${M} = c${M-1}; 58 } 59 $else: 60 if XNN_UNPREDICTABLE(mr < ${M+1}) { 61 a${M} = a${M-1}; 62 c${M} = c${M-1}; 63 } 64 65 $if ACTIVATION == "MINMAX" and not X86: 66 const v128_t vmin = wasm_v32x4_load_splat(¶ms->scalar.min); 67 const v128_t vmax = wasm_v32x4_load_splat(¶ms->scalar.max); 68 do { 69 $if INC: 70 $for M in range(MR): 71 $for N in range(0, NR, 4): 72 v128_t vacc${M}x${ABC[N:N+4]} = wasm_v128_load(acc + ${M*NR+N}); 73 acc += ${MR*NR}; 74 $else: 75 $for N in range(0, NR, 4): 76 v128_t vacc0x${ABC[N:N+4]} = wasm_v128_load(w + ${N}); 77 $for M in range(1, MR): 78 $for N in range(0, NR, 4): 79 v128_t vacc${M}x${ABC[N:N+4]} = vacc0x${ABC[N:N+4]}; 80 w += ${NR}; 81 82 size_t k = kc; 83 while (k >= 4 * sizeof(float)) { 84 $for M in range(MR): 85 v128_t va${M} = wasm_v128_load(a${M}); 86 a${M} += 4; 87 88 $for L in range(4): 89 90 $for N in range(0, NR, 4): 91 const v128_t vb${ABC[N:N+4]}c${L} = wasm_v128_load(w + ${L * NR + N}); 92 93 $for N in range(0, NR, 4): 94 $for M in range(MR): 95 vacc${M}x${ABC[N:N+4]} = wasm_f32x4_add(vacc${M}x${ABC[N:N+4]}, wasm_f32x4_mul(va${M}, vb${ABC[N:N+4]}c${L})); 96 97 $if L + 1 != 4: 98 $for M in range(MR): 99 va${M} = wasm_v32x4_shuffle(va${M}, va${M}, 1, 2, 3, 0); 100 101 w += ${4 * NR}; 102 k -= 4 * sizeof(float); 103 } 104 if XNN_UNLIKELY(k != 0) { 105 do { 106 $for M in range(MR): 107 const v128_t va${M} = wasm_v32x4_load_splat(a${M}); 108 a${M} += 1; 109 110 const v128_t vb${ABC[0:4]} = wasm_v128_load(w); 111 $for N in range(4, NR, 4): 112 const v128_t vb${ABC[N:N+4]} = wasm_v128_load(w + ${N}); 113 w += ${NR}; 114 115 $for N in range(0, NR, 4): 116 $for M in range(MR): 117 vacc${M}x${ABC[N:N+4]} = wasm_f32x4_add(vacc${M}x${ABC[N:N+4]}, wasm_f32x4_mul(va${M}, vb${ABC[N:N+4]})); 118 119 k -= sizeof(float); 120 } while (k != 0); 121 } 122 123 $if ACTIVATION == "MINMAX": 124 $if X86: 125 const v128_t vmin = wasm_v32x4_load_splat(¶ms->scalar.min); 126 $for N in range(0, NR, 4): 127 $for M in range(MR): 128 vacc${M}x${ABC[N:N+4]} = wasm_v128_bitselect(vmin, vacc${M}x${ABC[N:N+4]}, wasm_f32x4_lt(vacc${M}x${ABC[N:N+4]}, vmin)); 129 130 const v128_t vmax = wasm_v32x4_load_splat(¶ms->scalar.max); 131 $for N in range(0, NR, 4): 132 $for M in range(MR): 133 vacc${M}x${ABC[N:N+4]} = wasm_v128_bitselect(vacc${M}x${ABC[N:N+4]}, vmax, wasm_f32x4_le(vacc${M}x${ABC[N:N+4]}, vmax)); 134 $else: 135 $for N in range(0, NR, 4): 136 $for M in range(MR): 137 vacc${M}x${ABC[N:N+4]} = wasm_f32x4_max(vacc${M}x${ABC[N:N+4]}, vmin); 138 139 $for N in range(0, NR, 4): 140 $for M in range(MR): 141 vacc${M}x${ABC[N:N+4]} = wasm_f32x4_min(vacc${M}x${ABC[N:N+4]}, vmax); 142 $elif ACTIVATION == "RELU": 143 const v128_t vzero = wasm_f32x4_splat(0.0f); 144 $for N in range(0, NR, 4): 145 $for M in range(MR): 146 vacc${M}x${ABC[N:N+4]} = wasm_i32x4_max(vacc${M}x${ABC[N:N+4]}, vzero); 147 148 if XNN_LIKELY(nc >= ${NR}) { 149 $for M in reversed(range(MR)): 150 wasm_v128_store(c${M}, vacc${M}x${ABC[0:4]}); 151 $for N in range(4, NR, 4): 152 wasm_v128_store(c${M} + ${N}, vacc${M}x${ABC[N:N+4]}); 153 c${M} = (float*) ((uintptr_t) c${M} + cn_stride); 154 155 $for M in reversed(range(MR)): 156 a${M} = (const float*) ((uintptr_t) a${M} - kc); 157 158 nc -= ${NR}; 159 } else { 160 $for LOG2N in reversed(range(NR.bit_length())): 161 $if NR != 1 << LOG2N: 162 if (nc & ${1 << LOG2N}) { 163 $if LOG2N >= 2: 164 $for M in reversed(range(MR)): 165 wasm_v128_store(c${M}, vacc${M}x${ABC[0:4]}); 166 $for N in range(4, 1 << LOG2N, 4): 167 wasm_v128_store(c${M} + ${N}, vacc${M}x${ABC[N:N+4]}); 168 169 $for M in reversed(range(MR)): 170 $for N in range(0, 1 << (LOG2N - 1), 4): 171 vacc${M}x${ABC[N:N+4]} = vacc${M}x${ABC[N + (1 << LOG2N):N + (1 << LOG2N)+4]}; 172 173 $for M in reversed(range(MR)): 174 c${M} += ${1 << LOG2N}; 175 $elif LOG2N == 1: 176 $for M in reversed(range(MR)): 177 *((double*) c${M}) = wasm_f64x2_extract_lane(vacc${M}x${ABC[0:4]}, 0); 178 179 $for M in reversed(range(MR)): 180 vacc${M}x${ABC[0:4]} = wasm_v32x4_shuffle(vacc${M}x${ABC[0:4]}, vacc${M}x${ABC[0:4]}, 2, 3, 2, 3); 181 182 $for M in reversed(range(MR)): 183 c${M} += 2; 184 $elif LOG2N == 0: 185 $for M in reversed(range(MR)): 186 *c${M} = wasm_f32x4_extract_lane(vacc${M}x${ABC[0:4]}, 0); 187 } 188 189 nc = 0; 190 } 191 } while (nc != 0); 192} 193