Marat Dukhan | 52238f0 | 2020-07-16 15:30:28 -0700 | [diff] [blame] | 1 | // Auto-generated file. Do not edit! |
| 2 | // Template: src/f32-raddstoreexpminusmax/wasmsimd-p5.c.in |
| 3 | // Generator: tools/xngen |
| 4 | // |
| 5 | // Copyright 2020 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 <wasm_simd128.h> |
| 13 | |
| 14 | #include <xnnpack/common.h> |
| 15 | #include <xnnpack/raddstoreexpminusmax.h> |
| 16 | |
| 17 | |
| 18 | void xnn_f32_raddstoreexpminusmax_ukernel__wasmsimd_p5_x20_acc2( |
| 19 | size_t elements, |
| 20 | const float* input, |
| 21 | float* output, |
| 22 | float* sum, |
| 23 | float max) XNN_DISABLE_TSAN |
| 24 | { |
| 25 | assert(elements % sizeof(float) == 0); |
| 26 | |
| 27 | const v128_t vmagic_bias = wasm_f32x4_splat(0x1.8000FEp23f); |
| 28 | // The smallest x for which expf(x) is normalized. |
| 29 | const v128_t vdenorm_cutoff = wasm_f32x4_splat(-0x1.5D589Ep6f); |
| 30 | const v128_t vlog2e = wasm_f32x4_splat(0x1.715476p+0f); |
| 31 | // Last 7 bits are zeroes |
| 32 | const v128_t vminus_ln2_hi = wasm_f32x4_splat(-0x1.62E400p-1f); |
| 33 | const v128_t vminus_ln2_lo = wasm_f32x4_splat(-0x1.7F7D1Cp-20f); |
| 34 | |
| 35 | const v128_t vc1 = wasm_f32x4_splat(0x1.FFFFF6p-1f); |
| 36 | const v128_t vc2 = wasm_f32x4_splat(0x1.FFFDC6p-2f); |
| 37 | const v128_t vc3 = wasm_f32x4_splat(0x1.555A80p-3f); |
| 38 | const v128_t vc4 = wasm_f32x4_splat(0x1.573A1Ap-5f); |
| 39 | const v128_t vc5 = wasm_f32x4_splat(0x1.0F9F9Cp-7f); |
| 40 | |
| 41 | const v128_t vi_max = wasm_f32x4_splat(max); |
| 42 | |
| 43 | v128_t vacc0 = wasm_f32x4_splat(0.0f); |
| 44 | v128_t vacc1 = vacc0; |
| 45 | for (; elements >= 20 * sizeof(float); elements -= 20 * sizeof(float)) { |
| 46 | // Load 20 (5x4) inputs at a time. |
| 47 | const v128_t vi0123 = wasm_v128_load(input); |
| 48 | const v128_t vi4567 = wasm_v128_load(input + 4); |
| 49 | const v128_t vi89AB = wasm_v128_load(input + 8); |
| 50 | const v128_t viCDEF = wasm_v128_load(input + 12); |
| 51 | const v128_t viGHIJ = wasm_v128_load(input + 16); |
| 52 | input += 20; |
| 53 | |
| 54 | // Subtract maximum input x := i - i_max. This implies x <= 0. |
| 55 | const v128_t vx0123 = wasm_f32x4_sub(vi0123, vi_max); |
| 56 | const v128_t vx4567 = wasm_f32x4_sub(vi4567, vi_max); |
| 57 | const v128_t vx89AB = wasm_f32x4_sub(vi89AB, vi_max); |
| 58 | const v128_t vxCDEF = wasm_f32x4_sub(viCDEF, vi_max); |
| 59 | const v128_t vxGHIJ = wasm_f32x4_sub(viGHIJ, vi_max); |
| 60 | |
| 61 | // Compute reduced argument elements := round(x / log(2)). |
| 62 | v128_t vn0123 = wasm_f32x4_add(vmagic_bias, wasm_f32x4_mul(vx0123, vlog2e)); |
| 63 | v128_t vn4567 = wasm_f32x4_add(vmagic_bias, wasm_f32x4_mul(vx4567, vlog2e)); |
| 64 | v128_t vn89AB = wasm_f32x4_add(vmagic_bias, wasm_f32x4_mul(vx89AB, vlog2e)); |
| 65 | v128_t vnCDEF = wasm_f32x4_add(vmagic_bias, wasm_f32x4_mul(vxCDEF, vlog2e)); |
| 66 | v128_t vnGHIJ = wasm_f32x4_add(vmagic_bias, wasm_f32x4_mul(vxGHIJ, vlog2e)); |
| 67 | |
| 68 | // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e. |
| 69 | // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly. |
| 70 | const v128_t vs0123 = wasm_i32x4_shl(vn0123, 23); |
| 71 | const v128_t vs4567 = wasm_i32x4_shl(vn4567, 23); |
| 72 | const v128_t vs89AB = wasm_i32x4_shl(vn89AB, 23); |
| 73 | const v128_t vsCDEF = wasm_i32x4_shl(vnCDEF, 23); |
| 74 | const v128_t vsGHIJ = wasm_i32x4_shl(vnGHIJ, 23); |
| 75 | |
| 76 | // Subtract the large number back to get final elements := round(x / log(2)). |
| 77 | vn0123 = wasm_f32x4_sub(vn0123, vmagic_bias); |
| 78 | vn4567 = wasm_f32x4_sub(vn4567, vmagic_bias); |
| 79 | vn89AB = wasm_f32x4_sub(vn89AB, vmagic_bias); |
| 80 | vnCDEF = wasm_f32x4_sub(vnCDEF, vmagic_bias); |
| 81 | vnGHIJ = wasm_f32x4_sub(vnGHIJ, vmagic_bias); |
| 82 | |
| 83 | // Compute reduced argument t := x - elements * log(2). |
| 84 | // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. |
| 85 | v128_t vt0123 = wasm_f32x4_add(vx0123, wasm_f32x4_mul(vn0123, vminus_ln2_hi)); |
| 86 | v128_t vt4567 = wasm_f32x4_add(vx4567, wasm_f32x4_mul(vn4567, vminus_ln2_hi)); |
| 87 | v128_t vt89AB = wasm_f32x4_add(vx89AB, wasm_f32x4_mul(vn89AB, vminus_ln2_hi)); |
| 88 | v128_t vtCDEF = wasm_f32x4_add(vxCDEF, wasm_f32x4_mul(vnCDEF, vminus_ln2_hi)); |
| 89 | v128_t vtGHIJ = wasm_f32x4_add(vxGHIJ, wasm_f32x4_mul(vnGHIJ, vminus_ln2_hi)); |
| 90 | |
| 91 | vt0123 = wasm_f32x4_add(vt0123, wasm_f32x4_mul(vn0123, vminus_ln2_lo)); |
| 92 | vt4567 = wasm_f32x4_add(vt4567, wasm_f32x4_mul(vn4567, vminus_ln2_lo)); |
| 93 | vt89AB = wasm_f32x4_add(vt89AB, wasm_f32x4_mul(vn89AB, vminus_ln2_lo)); |
| 94 | vtCDEF = wasm_f32x4_add(vtCDEF, wasm_f32x4_mul(vnCDEF, vminus_ln2_lo)); |
| 95 | vtGHIJ = wasm_f32x4_add(vtGHIJ, wasm_f32x4_mul(vnGHIJ, vminus_ln2_lo)); |
| 96 | |
Marat Dukhan | 102a739 | 2020-11-20 01:18:10 -0800 | [diff] [blame^] | 97 | // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2]. |
Marat Dukhan | 52238f0 | 2020-07-16 15:30:28 -0700 | [diff] [blame] | 98 | v128_t vp0123 = wasm_f32x4_add(vc4, wasm_f32x4_mul(vc5, vt0123)); |
| 99 | v128_t vp4567 = wasm_f32x4_add(vc4, wasm_f32x4_mul(vc5, vt4567)); |
| 100 | v128_t vp89AB = wasm_f32x4_add(vc4, wasm_f32x4_mul(vc5, vt89AB)); |
| 101 | v128_t vpCDEF = wasm_f32x4_add(vc4, wasm_f32x4_mul(vc5, vtCDEF)); |
| 102 | v128_t vpGHIJ = wasm_f32x4_add(vc4, wasm_f32x4_mul(vc5, vtGHIJ)); |
| 103 | |
| 104 | vp0123 = wasm_f32x4_add(vc3, wasm_f32x4_mul(vp0123, vt0123)); |
| 105 | vp4567 = wasm_f32x4_add(vc3, wasm_f32x4_mul(vp4567, vt4567)); |
| 106 | vp89AB = wasm_f32x4_add(vc3, wasm_f32x4_mul(vp89AB, vt89AB)); |
| 107 | vpCDEF = wasm_f32x4_add(vc3, wasm_f32x4_mul(vpCDEF, vtCDEF)); |
| 108 | vpGHIJ = wasm_f32x4_add(vc3, wasm_f32x4_mul(vpGHIJ, vtGHIJ)); |
| 109 | |
| 110 | vp0123 = wasm_f32x4_add(vc2, wasm_f32x4_mul(vp0123, vt0123)); |
| 111 | vp4567 = wasm_f32x4_add(vc2, wasm_f32x4_mul(vp4567, vt4567)); |
| 112 | vp89AB = wasm_f32x4_add(vc2, wasm_f32x4_mul(vp89AB, vt89AB)); |
| 113 | vpCDEF = wasm_f32x4_add(vc2, wasm_f32x4_mul(vpCDEF, vtCDEF)); |
| 114 | vpGHIJ = wasm_f32x4_add(vc2, wasm_f32x4_mul(vpGHIJ, vtGHIJ)); |
| 115 | |
| 116 | vp0123 = wasm_f32x4_add(vc1, wasm_f32x4_mul(vp0123, vt0123)); |
| 117 | vp4567 = wasm_f32x4_add(vc1, wasm_f32x4_mul(vp4567, vt4567)); |
| 118 | vp89AB = wasm_f32x4_add(vc1, wasm_f32x4_mul(vp89AB, vt89AB)); |
| 119 | vpCDEF = wasm_f32x4_add(vc1, wasm_f32x4_mul(vpCDEF, vtCDEF)); |
| 120 | vpGHIJ = wasm_f32x4_add(vc1, wasm_f32x4_mul(vpGHIJ, vtGHIJ)); |
| 121 | |
| 122 | // Reconstruct the final f value: |
| 123 | // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))) |
| 124 | // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) |
| 125 | // = s + (t * s) * p |
| 126 | vt0123 = wasm_f32x4_mul(vt0123, vs0123); |
| 127 | vt4567 = wasm_f32x4_mul(vt4567, vs4567); |
| 128 | vt89AB = wasm_f32x4_mul(vt89AB, vs89AB); |
| 129 | vtCDEF = wasm_f32x4_mul(vtCDEF, vsCDEF); |
| 130 | vtGHIJ = wasm_f32x4_mul(vtGHIJ, vsGHIJ); |
| 131 | |
| 132 | v128_t vf0123 = wasm_f32x4_add(vs0123, wasm_f32x4_mul(vt0123, vp0123)); |
| 133 | v128_t vf4567 = wasm_f32x4_add(vs4567, wasm_f32x4_mul(vt4567, vp4567)); |
| 134 | v128_t vf89AB = wasm_f32x4_add(vs89AB, wasm_f32x4_mul(vt89AB, vp89AB)); |
| 135 | v128_t vfCDEF = wasm_f32x4_add(vsCDEF, wasm_f32x4_mul(vtCDEF, vpCDEF)); |
| 136 | v128_t vfGHIJ = wasm_f32x4_add(vsGHIJ, wasm_f32x4_mul(vtGHIJ, vpGHIJ)); |
| 137 | |
| 138 | // For inputs below zero cutoff, replace output with +0.0f. |
| 139 | // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| 140 | vf0123 = wasm_v128_andnot(vf0123, wasm_f32x4_lt(vx0123, vdenorm_cutoff)); |
| 141 | vf4567 = wasm_v128_andnot(vf4567, wasm_f32x4_lt(vx4567, vdenorm_cutoff)); |
| 142 | vf89AB = wasm_v128_andnot(vf89AB, wasm_f32x4_lt(vx89AB, vdenorm_cutoff)); |
| 143 | vfCDEF = wasm_v128_andnot(vfCDEF, wasm_f32x4_lt(vxCDEF, vdenorm_cutoff)); |
| 144 | vfGHIJ = wasm_v128_andnot(vfGHIJ, wasm_f32x4_lt(vxGHIJ, vdenorm_cutoff)); |
| 145 | |
| 146 | // Store 20 (5x4) outputs at a time. |
| 147 | wasm_v128_store(output, vf0123); |
| 148 | wasm_v128_store(output + 4, vf4567); |
| 149 | wasm_v128_store(output + 8, vf89AB); |
| 150 | wasm_v128_store(output + 12, vfCDEF); |
| 151 | wasm_v128_store(output + 16, vfGHIJ); |
| 152 | output += 20; |
| 153 | |
| 154 | // Accumulate computed exponents. |
| 155 | vacc0 = wasm_f32x4_add(vacc0, vf0123); |
| 156 | vacc0 = wasm_f32x4_add(vacc0, vf4567); |
| 157 | vacc0 = wasm_f32x4_add(vacc0, vf89AB); |
| 158 | vacc0 = wasm_f32x4_add(vacc0, vfCDEF); |
| 159 | vacc0 = wasm_f32x4_add(vacc0, vfGHIJ); |
| 160 | } |
| 161 | // Add up all accumulators to vacc0 |
| 162 | vacc0 = wasm_f32x4_add(vacc0, vacc1); |
| 163 | |
| 164 | v128_t vacc = vacc0; |
| 165 | for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) { |
| 166 | // Load 4 inputs at a time. |
| 167 | const v128_t vi = wasm_v128_load(input); |
| 168 | input += 4; |
| 169 | |
| 170 | // Subtract maximum input x := i - i_max. This implies x <= 0. |
| 171 | const v128_t vx = wasm_f32x4_sub(vi, vi_max); |
| 172 | |
| 173 | // Compute reduced argument elements := round(x / log(2)). |
| 174 | v128_t vn = wasm_f32x4_add(vmagic_bias, wasm_f32x4_mul(vx, vlog2e)); |
| 175 | |
| 176 | // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e. |
| 177 | // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly. |
| 178 | const v128_t vs = wasm_i32x4_shl(vn, 23); |
| 179 | |
| 180 | // Subtract the large number back to get final elements := round(x / log(2)). |
| 181 | vn = wasm_f32x4_sub(vn, vmagic_bias); |
| 182 | |
| 183 | // Compute reduced argument t := x - elements * log(2). |
| 184 | // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. |
| 185 | v128_t vt = wasm_f32x4_add(vx, wasm_f32x4_mul(vn, vminus_ln2_hi)); |
| 186 | vt = wasm_f32x4_add(vt, wasm_f32x4_mul(vn, vminus_ln2_lo)); |
| 187 | |
Marat Dukhan | 102a739 | 2020-11-20 01:18:10 -0800 | [diff] [blame^] | 188 | // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2]. |
Marat Dukhan | 52238f0 | 2020-07-16 15:30:28 -0700 | [diff] [blame] | 189 | v128_t vp = wasm_f32x4_add(vc4, wasm_f32x4_mul(vc5, vt)); |
| 190 | vp = wasm_f32x4_add(vc3, wasm_f32x4_mul(vp, vt)); |
| 191 | vp = wasm_f32x4_add(vc2, wasm_f32x4_mul(vp, vt)); |
| 192 | vp = wasm_f32x4_add(vc1, wasm_f32x4_mul(vp, vt)); |
| 193 | |
| 194 | // Reconstruct the final f value: |
| 195 | // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))) |
| 196 | // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) |
| 197 | // = s + (t * s) * p |
| 198 | vt = wasm_f32x4_mul(vt, vs); |
| 199 | v128_t vf = wasm_f32x4_add(vs, wasm_f32x4_mul(vt, vp)); |
| 200 | |
| 201 | // For inputs below zero cutoff, replace output with +0.0f. |
| 202 | // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| 203 | vf = wasm_v128_andnot(vf, wasm_f32x4_lt(vx, vdenorm_cutoff)); |
| 204 | |
| 205 | // Store 4 outputs at a time. |
| 206 | wasm_v128_store(output, vf); |
| 207 | output += 4; |
| 208 | |
| 209 | // Accumulate computed exponents. |
| 210 | vacc = wasm_f32x4_add(vacc, vf); |
| 211 | } |
| 212 | vacc = wasm_f32x4_add(vacc, wasm_v32x4_shuffle(vacc, vacc, 2, 3, 2, 3)); |
| 213 | float vsum = wasm_f32x4_extract_lane(vacc, 0) + wasm_f32x4_extract_lane(vacc, 1); |
| 214 | if (elements != 0) { |
| 215 | assert(elements >= 1 * sizeof(float)); |
| 216 | assert(elements <= 3 * sizeof(float)); |
| 217 | // Load 4 inputs at a time. |
| 218 | const v128_t vi = wasm_v128_load(input); |
| 219 | |
| 220 | // Subtract maximum input x := i - i_max. This implies x <= 0. |
| 221 | const v128_t vx = wasm_f32x4_sub(vi, vi_max); |
| 222 | |
| 223 | // Compute reduced argument elements := round(x / log(2)). |
| 224 | v128_t vn = wasm_f32x4_add(vmagic_bias, wasm_f32x4_mul(vx, vlog2e)); |
| 225 | |
| 226 | // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e. |
| 227 | // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly. |
| 228 | const v128_t vs = wasm_i32x4_shl(vn, 23); |
| 229 | |
| 230 | // Subtract the large number back to get final elements := round(x / log(2)). |
| 231 | vn = wasm_f32x4_sub(vn, vmagic_bias); |
| 232 | |
| 233 | // Compute reduced argument t := x - elements * log(2). |
| 234 | // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. |
| 235 | v128_t vt = wasm_f32x4_add(vx, wasm_f32x4_mul(vn, vminus_ln2_hi)); |
| 236 | vt = wasm_f32x4_add(vt, wasm_f32x4_mul(vn, vminus_ln2_lo)); |
| 237 | |
Marat Dukhan | 102a739 | 2020-11-20 01:18:10 -0800 | [diff] [blame^] | 238 | // Compute degree-5 polynomial approximation for exp(t) on [-log(2)/2, log(2)/2]. |
Marat Dukhan | 52238f0 | 2020-07-16 15:30:28 -0700 | [diff] [blame] | 239 | v128_t vp = wasm_f32x4_add(vc4, wasm_f32x4_mul(vc5, vt)); |
| 240 | vp = wasm_f32x4_add(vc3, wasm_f32x4_mul(vp, vt)); |
| 241 | vp = wasm_f32x4_add(vc2, wasm_f32x4_mul(vp, vt)); |
| 242 | vp = wasm_f32x4_add(vc1, wasm_f32x4_mul(vp, vt)); |
| 243 | |
| 244 | // Reconstruct the final f value: |
| 245 | // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))) |
| 246 | // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) |
| 247 | // = s + (t * s) * p |
| 248 | vt = wasm_f32x4_mul(vt, vs); |
| 249 | v128_t vf = wasm_f32x4_add(vs, wasm_f32x4_mul(vt, vp)); |
| 250 | |
| 251 | // For inputs below zero cutoff, replace output with +0.0f. |
| 252 | // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| 253 | vf = wasm_v128_andnot(vf, wasm_f32x4_lt(vx, vdenorm_cutoff)); |
| 254 | |
| 255 | if (elements & (2 * sizeof(float))) { |
| 256 | // Store and accumulate 2 outputs at a time. |
| 257 | const float vf0 = wasm_f32x4_extract_lane(vf, 0); |
| 258 | output[0] = vf0; |
| 259 | vsum += vf0; |
| 260 | |
| 261 | const float vf1 = wasm_f32x4_extract_lane(vf, 1); |
| 262 | output[1] = vf1; |
| 263 | vsum += vf1; |
| 264 | |
| 265 | vf = wasm_v32x4_shuffle(vf, vf, 2, 3, 2, 3); |
| 266 | output += 2; |
| 267 | } |
| 268 | if (elements & (1 * sizeof(float))) { |
| 269 | // Store 1 output at a time. |
| 270 | const float vf0 = wasm_f32x4_extract_lane(vf, 0); |
| 271 | *output = vf0; |
| 272 | vsum += vf0; |
| 273 | } |
| 274 | } |
| 275 | // Reduce 4 elements in the SIMD register |
| 276 | *sum = vsum; |
| 277 | } |