Freddie Liardet | e572dff | 2022-05-16 14:09:10 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2022 Arm Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "activation_float_helpers.h" |
| 25 | #include "helpers.h" |
| 26 | #include "tile_helpers.h" |
| 27 | #if defined(GEMMLOWP_MM_RESHAPED_ONLY_RHS_MMUL) |
| 28 | /** This OpenCL kernel computes the matrix multiplication between 2 matrices using the MMUL extension: |
| 29 | * |
| 30 | * The LHS matrix is NOT reshaped |
| 31 | * The RHS is reshaped with @ref ClGemmMatrixMultiplyReshapedOnlyRhsKernel and the block K0xN0 is transposed |
| 32 | * |
| 33 | * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (e.g. -DN0=1, -DK0=1). |
| 34 | * @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=1) |
| 35 | * @note The number of output columns processed by the the cooperative mmul extension must be passed at compile time using -DMMUL_N0 (e.g., -DMMUL_N0=4) |
| 36 | * @note The number of output rows processed by the the cooperative mmul extension must be passed at compile time using -DMMUL_M0 (e.g., -DMMUL_M0=4) |
| 37 | * @note The number of lhs columns (or rhs rows) processed by the the cooperative mmul extension must be passed at compile time using -DMMUL_K0 (e.g., -DMMUL_K0=16) |
| 38 | * @note Only the following configurations of M0, N0 and K0 are currently supported: |
| 39 | * - M0 = 1, 2, 4 |
| 40 | * - N0 = 1, 4, 8 |
| 41 | * - K0 = 4 |
| 42 | * |
| 43 | * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively. |
| 44 | * The activation function is performed after the bias addition |
| 45 | * |
| 46 | * @param[in] lhs_ptr Pointer to the LHS tensor. Supported data types: QASYMM8/QASYMM8_SIGNED |
| 47 | * @param[in] lhs_stride_y Stride of the LHS tensor in Y dimension (in bytes) |
| 48 | * @param[in] lhs_stride_z Stride of the LHS tensor in Z dimension (in bytes) |
| 49 | * @param[in] lhs_w The size of the width dimension of the LHS tensor |
| 50 | * @param[in] lhs_h The size of the height dimension of the LHS tensor |
| 51 | * @param[in] lhs_n The size of the depth dimension of the LHS tensor |
| 52 | * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS tensor |
| 53 | * @param[in] rhs_ptr Pointer to the RHS reshaped tensor. Supported data type: same as @p lhs_ptr |
| 54 | * @param[in] rhs_stride_y Stride of the RHS tensor in Y dimension (in bytes) |
| 55 | * @param[in] rhs_stride_z Stride of the RHS tensor in Z dimension (in bytes) |
| 56 | * @param[in] rhs_w The size of the width dimension of the RHS tensor |
| 57 | * @param[in] rhs_h The size of the height dimension of the RHS tensor |
| 58 | * @param[in] rhs_n The size of the depth dimension of the RHS tensor |
| 59 | * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS tensor |
| 60 | * @param[in] bia_ptr (Optional) Pointer to the bias tensor. Supported data type: S32 |
| 61 | * @param[in] bia_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) |
| 62 | * @param[in] bia_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) |
| 63 | * @param[in] bia_w (Optional) The size of the width dimension of the bias tensor |
| 64 | * @param[in] bia_h (Optional) The size of the height dimension of the bias tensor |
| 65 | * @param[in] bia_n (Optional) The size of the depth dimension of the bias tensor |
| 66 | * @param[in] bia_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor |
| 67 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data type: same as @p lhs_ptr or S32 |
| 68 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 69 | * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) |
| 70 | * @param[in] dst_w The size of the width dimension of the destination tensor |
| 71 | * @param[in] dst_h The size of the height dimension of the destination tensor |
| 72 | * @param[in] dst_n The size of the depth dimension of the destination tensor |
| 73 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 74 | * @param[in] M Number of rows in LHS matrix not reshaped |
| 75 | * @param[in] N Number of columns in RHS matrix not reshaped |
| 76 | * @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped |
| 77 | * @param[in] sum_col_ptr (Optional) Pointer to the source tensor. Supported data type: S32 |
| 78 | * @param[in] sum_col_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) |
| 79 | * @param[in] sum_col_step_x (Optional) sum_col_stride_x * number of elements along X processed per workitem(in bytes) |
| 80 | * @param[in] sum_col_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) |
| 81 | * @param[in] sum_col_step_y (Optional) sum_col_stride_y * number of elements along Y processed per workitem(in bytes) |
| 82 | * @param[in] sum_col_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor |
| 83 | * @param[in] sum_row_ptr (Optional) Pointer to the source tensor. Supported data type: S32 |
| 84 | * @param[in] sum_row_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) |
| 85 | * @param[in] sum_row_step_x (Optional) sum_row_stride_x * number of elements along X processed per workitem(in bytes) |
| 86 | * @param[in] sum_row_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) |
| 87 | * @param[in] sum_row_step_y (Optional) sum_row_stride_y * number of elements along Y processed per workitem(in bytes) |
| 88 | * @param[in] sum_row_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor |
| 89 | */ |
| 90 | __kernel void gemmlowp_mm_reshaped_only_rhs_mmul( |
| 91 | TENSOR3D_T(lhs, BUFFER), |
| 92 | TENSOR3D_T(rhs, BUFFER), |
| 93 | #if defined(ADD_BIAS) |
| 94 | TENSOR3D_T(bia, BUFFER), |
| 95 | #endif // defined(ADD_BIAS) |
| 96 | TENSOR3D_T(dst, BUFFER), |
| 97 | const int M, |
| 98 | const int N, |
| 99 | const int K |
| 100 | #if defined(A_OFFSET) |
| 101 | , |
| 102 | TENSOR3D_T(sum_col, BUFFER) |
| 103 | #endif // defined(A_OFFSET) |
| 104 | #if defined(B_OFFSET) |
| 105 | , |
| 106 | TENSOR3D_T(sum_row, BUFFER) |
| 107 | #endif // defined(B_OFFSET) |
| 108 | ) |
| 109 | { |
| 110 | #define MMUL_BLOCK_SIZE (MMUL_N0 * MMUL_M0) |
| 111 | #define VEC_SIZE 4 // For int8 types input to mmul instruction is a length 4 vector |
| 112 | |
| 113 | uint x0 = get_global_id(0); |
| 114 | uint y0 = get_global_id(1); |
| 115 | uint z = get_global_id(2); |
| 116 | |
| 117 | // Get block ID and thread ID within the block |
| 118 | uint block_id = (x0 / MMUL_BLOCK_SIZE); |
| 119 | uint thread_id = (x0 % MMUL_BLOCK_SIZE); |
| 120 | |
| 121 | // Coordinate within a block |
| 122 | uint block_x = thread_id % MMUL_N0; |
| 123 | uint block_y = (thread_id / MMUL_M0); |
| 124 | |
| 125 | // Starting destination coordinates |
| 126 | uint dst_x = min(block_x * N0 + block_id * MMUL_N0 * N0, (uint)(N - 1)); |
| 127 | uint dst_y = min(block_y * M0 + y0 * M0 * MMUL_M0, (uint)(M - M0)); |
| 128 | |
| 129 | uint lhs_x = VEC_SIZE * block_x; |
| 130 | uint lhs_y = dst_y; |
| 131 | |
| 132 | uint rhs_x = VEC_SIZE * N0 * block_y; |
| 133 | uint rhs_y = 4 * block_id + block_x; |
| 134 | |
| 135 | // Compute LHS/RHS/DST matrix address |
| 136 | lhs_offset_first_element_in_bytes += lhs_x * sizeof(DATA_TYPE) + lhs_y * lhs_stride_y + z * lhs_stride_z; |
| 137 | rhs_offset_first_element_in_bytes += rhs_x * sizeof(DATA_TYPE) + rhs_y * rhs_stride_y + z * rhs_stride_z; |
| 138 | dst_offset_first_element_in_bytes += dst_x * sizeof(OUT_DATA_TYPE) + dst_y * dst_stride_y + z * dst_stride_z; |
| 139 | |
| 140 | TILE(ACC_DATA_TYPE, M0, N0, c); |
| 141 | LOOP_UNROLLING(int, i, 0, 1, M0, |
| 142 | { |
| 143 | c[i].v = 0; |
| 144 | }) |
| 145 | |
| 146 | for(int k = 0; k <= K - MMUL_K0; k += MMUL_K0) |
| 147 | { |
| 148 | TILE(DATA_TYPE, M0, VEC_SIZE, a); |
| 149 | T_LOAD(DATA_TYPE, M0, VEC_SIZE, BUFFER, lhs, 0, 0, 1, lhs_stride_y, a); |
| 150 | |
| 151 | TILE(DATA_TYPE, N0, VEC_SIZE, b); |
| 152 | T_LOAD(DATA_TYPE, N0, VEC_SIZE, BUFFER, rhs, 0, 0, 1, VEC_SIZE, b); |
| 153 | |
| 154 | LOOP_UNROLLING(int, m0, 0, 1, M0, |
| 155 | { |
| 156 | LOOP_UNROLLING(int, n0, 0, 1, N0, |
| 157 | { |
| 158 | VEC_TYPE vec_a = (VEC_TYPE)(a[m0].s[0], a[m0].s[1], a[m0].s[2], a[m0].s[3]); |
| 159 | VEC_TYPE vec_b = (VEC_TYPE)(b[n0].s[0], b[n0].s[1], b[n0].s[2], b[n0].s[3]); |
| 160 | c[m0].s[n0] = arm_matrix_multiply(vec_a, vec_b, c[m0].s[n0]); |
| 161 | }) |
| 162 | }) |
| 163 | |
| 164 | lhs_offset_first_element_in_bytes += MMUL_K0 * sizeof(DATA_TYPE); |
| 165 | rhs_offset_first_element_in_bytes += MMUL_K0 * N0 * sizeof(DATA_TYPE); |
| 166 | } |
| 167 | |
| 168 | if(block_x * N0 + block_id * MMUL_N0 * N0 >= N) |
| 169 | { |
| 170 | return; |
| 171 | } |
| 172 | |
| 173 | if(block_y * M0 + y0 * M0 * MMUL_M0 >= M) |
| 174 | { |
| 175 | return; |
| 176 | } |
| 177 | |
| 178 | #if defined(FUSED_OUTPUT_STAGE_FIXED_POINT) |
| 179 | |
| 180 | TILE(int, M0, N0, offset_s32); |
| 181 | LOOP_UNROLLING(int, i, 0, 1, M0, |
| 182 | { |
| 183 | offset_s32[i].v = (VEC_DATA_TYPE(int, N0))K_OFFSET; |
| 184 | }) |
| 185 | |
| 186 | #if defined(A_OFFSET) |
| 187 | |
| 188 | TILE(int, 1, N0, a_offset_s32); |
| 189 | |
| 190 | T_LOAD(int, 1, N0, BUFFER, sum_col, dst_x, z, 1, sum_col_stride_z, a_offset_s32); |
| 191 | |
| 192 | a_offset_s32[0].v *= A_OFFSET; |
| 193 | |
| 194 | T_ELTWISE_BROADCAST_ADD_X(int, M0, N0, offset_s32, a_offset_s32, offset_s32); |
| 195 | #endif // defined(A_OFFSET) |
| 196 | |
| 197 | #if defined(B_OFFSET) |
| 198 | |
| 199 | TILE(int, M0, 1, b_offset_s32); |
| 200 | |
| 201 | T_LOAD(int, M0, 1, BUFFER, sum_row, dst_y, z * M, 1, 4, b_offset_s32); |
| 202 | |
| 203 | LOOP_UNROLLING(int, m0, 0, 1, M0, |
| 204 | { |
| 205 | offset_s32[m0].v += b_offset_s32[m0].v *B_OFFSET; |
| 206 | }) |
| 207 | |
| 208 | #endif // defined(B_OFFSET) |
| 209 | |
| 210 | #if defined(ADD_BIAS) |
| 211 | #if defined(BROADCAST_BIAS) |
| 212 | bia_offset_first_element_in_bytes += dst_x * sizeof(ACC_DATA_TYPE) + z * bia_stride_y; |
| 213 | |
| 214 | TILE(int, M0, N0, bias); |
| 215 | |
| 216 | T_LOAD(int, M0, N0, BUFFER, bia, dst_x, dst_y, 1, 1, bias); |
| 217 | |
| 218 | T_ADD(ACC_DATA_TYPE, M0, N0, offset_s32, bias, offset_s32); |
| 219 | |
| 220 | #else // defined(BROADCAST_BIAS) |
| 221 | bia_offset_first_element_in_bytes += dst_x * sizeof(ACC_DATA_TYPE); |
| 222 | |
| 223 | TILE(int, 1, N0, bias); |
| 224 | |
| 225 | if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| 226 | { |
| 227 | bias[0].v = VLOAD(N0)(0, (ACC_DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes)); |
| 228 | } |
| 229 | else |
| 230 | { |
| 231 | VLOAD_PARTIAL(N0, N0_LEFTOVER) |
| 232 | (bias[0].v, 0, (ACC_DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes)); |
| 233 | } |
| 234 | |
| 235 | T_ELTWISE_BROADCAST_ADD_X(int, M0, N0, offset_s32, bias, offset_s32); |
| 236 | |
| 237 | #endif // defined(BROADCAST_BIAS) |
| 238 | #endif // defined(ADD_BIAS) |
| 239 | |
| 240 | T_ADD(ACC_DATA_TYPE, M0, N0, c, offset_s32, c); |
| 241 | TILE(OUT_DATA_TYPE, M0, N0, c_lp); |
| 242 | T_QUANTIZE8(ACC_DATA_TYPE, OUT_DATA_TYPE, PER_TENSOR, M0, N0, RESULT_OFFSET, RESULT_SHIFT, RESULT_MULTIPLIER, c, 0, 0, c_lp); |
| 243 | |
| 244 | #if defined(MIN_BOUND) |
| 245 | LOOP_UNROLLING(int, i, 0, 1, M0, |
| 246 | { |
| 247 | c_lp[i].v = max(c_lp[i].v, (VEC_DATA_TYPE(OUT_DATA_TYPE, N0))MIN_BOUND); |
| 248 | }) |
| 249 | #endif // defined(MIN_BOUND) |
| 250 | #if defined(MAX_BOUND) |
| 251 | LOOP_UNROLLING(int, i, 0, 1, M0, |
| 252 | { |
| 253 | c_lp[i].v = min(c_lp[i].v, (VEC_DATA_TYPE(OUT_DATA_TYPE, N0))MAX_BOUND); |
| 254 | }) |
| 255 | #endif // defined(MAX_BOUND) |
| 256 | |
| 257 | T_ACTIVATION(DATA_TYPE, M0, N0, ACTIVATION_TYPE, A_VAL, B_VAL, c, c); |
| 258 | |
| 259 | if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| 260 | { |
| 261 | LOOP_UNROLLING(int, m0, 0, 1, M0, |
| 262 | { |
| 263 | if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| 264 | { |
| 265 | VSTORE(N0) |
| 266 | (c_lp[m0].v, 0, (__global OUT_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| 267 | } |
| 268 | }) |
| 269 | } |
| 270 | else |
| 271 | { |
| 272 | LOOP_UNROLLING(int, m0, 0, 1, M0, |
| 273 | { |
| 274 | if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| 275 | { |
| 276 | VSTORE_PARTIAL(N0, N0_LEFTOVER) |
| 277 | (c_lp[m0].v, 0, (__global OUT_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| 278 | } |
| 279 | }) |
| 280 | } |
| 281 | |
| 282 | #else // FUSED_OUTPUT_STAGE_FIXED_POINT |
| 283 | // Store |
| 284 | if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| 285 | { |
| 286 | LOOP_UNROLLING(int, m0, 0, 1, M0, |
| 287 | { |
| 288 | if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| 289 | { |
| 290 | VSTORE(N0) |
| 291 | (c[m0].v, 0, (__global OUT_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| 292 | } |
| 293 | }) |
| 294 | } |
| 295 | else |
| 296 | { |
| 297 | LOOP_UNROLLING(int, m0, 0, 1, M0, |
| 298 | { |
| 299 | if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| 300 | { |
| 301 | VSTORE_PARTIAL(N0, N0_LEFTOVER) |
| 302 | (c[m0].v, 0, (__global OUT_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| 303 | } |
| 304 | }) |
| 305 | } |
| 306 | #endif // FUSED_OUTPUT_STAGE_FIXED_POINT |
| 307 | } |
| 308 | |
| 309 | #endif // defined(GEMMLOWP_MM_RESHAPED_ONLY_RHS_MMUL) |