| /* |
| * Copyright (c) 2022-2023 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "activation_float_helpers.h" |
| #include "helpers.h" |
| #include "tile_helpers.h" |
| |
| #if defined(GEMM_MM_RESHAPED_ONLY_RHS_NT_MMUL) |
| /** This OpenCL kernel computes the matrix multiplication between 2 matrices using the MMUL extension: |
| * |
| * The LHS matrix is NOT reshaped |
| * The RHS is reshaped with @ref ClGemmMatrixMultiplyReshapedOnlyRhsKernel and the block K0xN0 is NOT transposed |
| * |
| * @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=8, -DK0=4). |
| * @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2) |
| * @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=2) |
| * @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=2) |
| * @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=2) |
| * @note Only the following configurations of M0, N0 and K0 are currently supported: |
| * - M0 > 0 |
| * - N0 = 1, 2, 3, 4, 8, 16 |
| * - K0 = 1 |
| * |
| * @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. |
| * The activation function is performed after the bias addition |
| * |
| * @param[in] lhs_ptr Pointer to the LHS tensor. Supported data types: F16/F32 |
| * @param[in] lhs_stride_y Stride of the LHS tensor in Y dimension (in bytes) |
| * @param[in] lhs_stride_z Stride of the LHS tensor in Z dimension (in bytes) |
| * @param[in] lhs_w The size of the width dimension of the LHS tensor |
| * @param[in] lhs_h The size of the height dimension of the LHS tensor |
| * @param[in] lhs_n The size of the depth dimension of the LHS tensor |
| * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS tensor |
| * @param[in] rhs_ptr Pointer to the RHS reshaped tensor. Supported data type: same as @p lhs_ptr |
| * @param[in] rhs_stride_y Stride of the RHS tensor in Y dimension (in bytes) |
| * @param[in] rhs_stride_z Stride of the RHS tensor in Z dimension (in bytes) |
| * @param[in] rhs_w The size of the width dimension of the RHS tensor |
| * @param[in] rhs_h The size of the height dimension of the RHS tensor |
| * @param[in] rhs_n The size of the depth dimension of the RHS tensor |
| * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS tensor |
| * @param[in] bia_ptr (Optional) Pointer to the bias tensor. Supported data type: same as @p lhs_ptr |
| * @param[in] bia_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) |
| * @param[in] bia_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) |
| * @param[in] bia_w (Optional) The size of the width dimension of the bias tensor |
| * @param[in] bia_h (Optional) The size of the height dimension of the bias tensor |
| * @param[in] bia_n (Optional) The size of the depth dimension of the bias tensor |
| * @param[in] bia_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor |
| * @param[out] dst_ptr Pointer to the destination tensor. Supported data type: same as @p lhs_ptr |
| * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) |
| * @param[in] dst_w The size of the width dimension of the destination tensor |
| * @param[in] dst_h The size of the height dimension of the destination tensor |
| * @param[in] dst_n The size of the depth dimension of the destination tensor |
| * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| * @param[in] M Number of rows in LHS matrix not reshaped |
| * @param[in] N Number of columns in RHS matrix not reshaped |
| * @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped |
| */ |
| __kernel void gemm_mm_reshaped_only_rhs_nt_mmul( |
| TENSOR3D_T(lhs, BUFFER), |
| TENSOR3D_T(rhs, BUFFER), |
| #if defined(BETA) |
| TENSOR3D_T(bia, BUFFER), |
| #endif // defined(BETA) |
| TENSOR3D_T(dst, BUFFER), |
| const int M, |
| const int N, |
| const int K) |
| { |
| #define MMUL_BLOCK_SIZE (MMUL_N0 * MMUL_K0) |
| |
| uint x0 = get_global_id(0); // (N / N0) * MMUL_K0 |
| uint y0 = get_global_id(1); // (M / M0) / MMUL_M0 |
| uint z = get_global_id(2); // Batch |
| |
| // Get block ID and thread ID within the block |
| uint block_id = (x0 / MMUL_BLOCK_SIZE); |
| uint thread_id = (x0 % MMUL_BLOCK_SIZE); |
| |
| // Coordinate within a block |
| uint block_x = thread_id % MMUL_N0; |
| uint block_y = (thread_id / MMUL_M0); |
| |
| // Starting destination coordinates |
| uint dst_x = min(block_x * N0 + block_id * MMUL_N0 * N0, (uint)(N - 1)); |
| uint dst_y = min(block_y * M0 + y0 * M0 * MMUL_M0, (uint)(M - M0)); |
| |
| // Note: We need to clamp dst_x and dst_y because we always need to execute a complete MMUL block! Only after the matrix multiplication |
| // part can we exit the kernel if it is out-of-bound. Remember, we have a cooperative matrix multiplication. Therefore, we need a full block to get the correct results |
| |
| // Starting LHS coordinates |
| uint lhs_x = block_x; |
| uint lhs_y = dst_y; |
| |
| // Starting RHS coordinates |
| uint rhs_x = block_y * N0 * MMUL_N0 + block_x * N0; |
| uint rhs_y = block_id; |
| |
| // Compute LHS/RHS/DST matrix address |
| #ifdef REINTERPRET_INPUT_AS_3D |
| lhs_offset_first_element_in_bytes += lhs_x * sizeof(DATA_TYPE) + (lhs_y + z * M) * lhs_stride_y; |
| #else // REINTERPRET_INPUT_AS_3D |
| lhs_offset_first_element_in_bytes += lhs_x * sizeof(DATA_TYPE) + lhs_y * lhs_stride_y + z * lhs_stride_z; |
| #endif // REINTERPRET_INPUT_AS_3D |
| |
| #ifdef BATCHED_RHS |
| rhs_offset_first_element_in_bytes += rhs_x * sizeof(DATA_TYPE) + rhs_y * rhs_stride_y + z * rhs_stride_z; |
| #else // BATCHED_RHS |
| rhs_offset_first_element_in_bytes += rhs_x * sizeof(DATA_TYPE) + rhs_y * rhs_stride_y; |
| #endif // BATCHED_RHS |
| |
| #ifdef REINTERPRET_OUTPUT_AS_3D |
| dst_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE) + (dst_y + z * M) * dst_stride_y; |
| #else // REINTERPRET_OUTPUT_AS_3D |
| dst_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE) + dst_y * dst_stride_y + z * dst_stride_z; |
| #endif // REINTERPRET_OUTPUT_AS_3D |
| |
| // Note: If RHS derives from the weights of convolution 2d layer, RHS will always be 2D and rhs_stride_z will always be equal to 0 for |
| // not sliding the tensor |
| |
| // Initialize the accumulators |
| // MMUL extension accumulate the result in F32 for both F32 and F16 |
| TILE(float, M0, N0, c_f32); |
| |
| #if !defined(HALF_PRECISION) |
| #define c c_f32 |
| #endif // !defined(HALF_PRECISION) |
| |
| LOOP_UNROLLING(int, i, 0, 1, M0, |
| { |
| c_f32[i].v = 0; |
| }) |
| |
| for(int k = 0; k <= K - MMUL_K0; k += MMUL_K0) |
| { |
| TILE(DATA_TYPE, M0, 1, a); |
| TILE(DATA_TYPE, 1, N0, b); |
| |
| // Load tile from the lhs/rhs tensors |
| T_LOAD(DATA_TYPE, M0, 1, BUFFER, lhs, 0, 0, 1, lhs_stride_y, a); |
| T_LOAD(DATA_TYPE, 1, N0, BUFFER, rhs, 0, 0, 1, 0, b); |
| |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| LOOP_UNROLLING(int, n0, 0, 1, N0, |
| { |
| c_f32[m0].s[n0] = arm_matrix_multiply(a[m0].s[0], b[0].s[n0], c_f32[m0].s[n0]); |
| }) |
| }) |
| |
| lhs_offset_first_element_in_bytes += MMUL_K0 * sizeof(DATA_TYPE); |
| rhs_offset_first_element_in_bytes += MMUL_K0 * MMUL_N0 * N0 * sizeof(DATA_TYPE); |
| } |
| |
| if(block_x * N0 + block_id * MMUL_N0 * N0 >= N) |
| { |
| return; |
| } |
| |
| if(block_y * M0 + y0 * M0 * MMUL_M0 >= M) |
| { |
| return; |
| } |
| |
| #if defined(HALF_PRECISION) |
| TILE(DATA_TYPE, M0, N0, c); |
| |
| // Conversion required for the half precision |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| LOOP_UNROLLING(int, n0, 0, 1, N0, |
| { |
| c[m0].s[n0] = c_f32[m0].s[n0]; |
| }) |
| }) |
| #endif // defined(HALF_PRECISION) |
| |
| // Multiply by the weight of matrix-matrix product and store the result |
| #if defined(ALPHA) |
| T_SCALE_CONSTANT(DATA_TYPE, M0, N0, c, (DATA_TYPE)ALPHA, c); |
| #endif // defined(ALPHA) |
| |
| // Add beta*bias |
| #if defined(BETA) |
| #if defined(BROADCAST_BIAS) |
| bia_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE); |
| |
| TILE(DATA_TYPE, 1, N0, bias0); |
| |
| if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| { |
| bias0[0].v = VLOAD(N0)(0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes)); |
| } |
| else |
| { |
| VLOAD_PARTIAL(N0, N0_LEFTOVER) |
| (bias0[0].v, 0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes)); |
| } |
| |
| #ifndef UNIT_BETA |
| T_SCALE_CONSTANT(DATA_TYPE, 1, N0, bias0, (DATA_TYPE)BETA, bias0); |
| #endif // UNIT_BIAS |
| |
| // c = c + bias[broadcasted] |
| T_ELTWISE_BROADCAST_X(V_ADD, DATA_TYPE, M0, N0, c, bias0, c); |
| #else // defined(BROADCAST_BIAS) |
| TILE(DATA_TYPE, M0, N0, bias0); |
| |
| bia_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE) + dst_y * bia_stride_y + z * bia_stride_z; |
| |
| if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| bias0[m0].v = VLOAD(N0)(0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes + m0 * bia_stride_y)); |
| } |
| }) |
| } |
| else |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| VLOAD_PARTIAL(N0, N0_LEFTOVER) |
| (bias0[m0].v, 0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes + m0 * bia_stride_y)); |
| } |
| }) |
| } |
| |
| #ifndef UNIT_BETA |
| T_SCALE_CONSTANT(DATA_TYPE, M0, N0, bias0, (DATA_TYPE)BETA, bias0); |
| #endif // UNIT_BIAS |
| |
| // c = c + bias |
| T_ADD(DATA_TYPE, M0, N0, c, bias0, c); |
| // c = c + bias |
| #endif // defined(BROADCAST_BIAS) |
| #endif // defined(BETA) |
| |
| T_ACTIVATION(DATA_TYPE, M0, N0, ACTIVATION_TYPE, A_VAL, B_VAL, c, c); |
| |
| // Store |
| if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| VSTORE(N0) |
| (c[m0].v, 0, (__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| } |
| }) |
| } |
| else |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| VSTORE_PARTIAL(N0, N0_LEFTOVER) |
| (c[m0].v, 0, (__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| } |
| }) |
| } |
| |
| #undef RHS_BLOCK_SIZE |
| #undef RHS_OFFSET_X |
| #undef RHS_STEP_X |
| } |
| #endif // defined(GEMM_MM_RESHAPED_ONLY_RHS_MMUL) |
| |
| #if defined(GEMM_MM_RESHAPED_ONLY_RHS_NT_MMUL_TEXTURE) |
| /** This OpenCL kernel computes the matrix multiplication between 2 matrices using the MMUL extension and the OpenCL image for RHS: |
| * |
| * The LHS matrix is NOT reshaped |
| * The RHS is reshaped with @ref ClGemmMatrixMultiplyReshapedOnlyRhsKernel and the block K0xN0 is NOT transposed |
| * |
| * @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=8, -DK0=4). |
| * @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2) |
| * @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=2) |
| * @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=2) |
| * @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=2) |
| * @note Only the following configurations of M0, N0 and K0 are currently supported: |
| * - M0 > 0 |
| * - N0 = 1, 2, 3, 4, 8, 16 |
| * - K0 = 1 |
| * |
| * @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. |
| * The activation function is performed after the bias addition |
| * |
| * @param[in] lhs_ptr Pointer to the LHS tensor. Supported data types: F16/F32 |
| * @param[in] lhs_stride_y Stride of the LHS tensor in Y dimension (in bytes) |
| * @param[in] lhs_stride_z Stride of the LHS tensor in Z dimension (in bytes) |
| * @param[in] lhs_w The size of the width dimension of the LHS tensor |
| * @param[in] lhs_h The size of the height dimension of the LHS tensor |
| * @param[in] lhs_n The size of the depth dimension of the LHS tensor |
| * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS tensor |
| * @param[in] rhs_ptr Pointer to the RHS reshaped tensor. Supported data type: same as @p lhs_ptr |
| * @param[in] rhs_stride_y Stride of the RHS tensor in Y dimension (in bytes) |
| * @param[in] rhs_stride_z Stride of the RHS tensor in Z dimension (in bytes) |
| * @param[in] rhs_w The size of the width dimension of the RHS tensor |
| * @param[in] rhs_h The size of the height dimension of the RHS tensor |
| * @param[in] rhs_n The size of the depth dimension of the RHS tensor |
| * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS tensor |
| * @param[in] bia_ptr (Optional) Pointer to the bias tensor. Supported data type: same as @p lhs_ptr |
| * @param[in] bia_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) |
| * @param[in] bia_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) |
| * @param[in] bia_w (Optional) The size of the width dimension of the bias tensor |
| * @param[in] bia_h (Optional) The size of the height dimension of the bias tensor |
| * @param[in] bia_n (Optional) The size of the depth dimension of the bias tensor |
| * @param[in] bia_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor |
| * @param[out] dst_ptr Pointer to the destination tensor. Supported data type: same as @p lhs_ptr |
| * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) |
| * @param[in] dst_w The size of the width dimension of the destination tensor |
| * @param[in] dst_h The size of the height dimension of the destination tensor |
| * @param[in] dst_n The size of the depth dimension of the destination tensor |
| * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| * @param[in] M Number of rows in LHS matrix not reshaped |
| * @param[in] N Number of columns in RHS matrix not reshaped |
| * @param[in] K Number of columns in LHS matrix and rows in RHS matrix not reshaped |
| */ |
| __kernel void gemm_mm_reshaped_only_rhs_nt_mmul_texture( |
| TENSOR3D_T(lhs, BUFFER), |
| TENSOR3D_T(rhs, IMAGE), |
| #if defined(BETA) |
| TENSOR3D_T(bia, BUFFER), |
| #endif // defined(BETA) |
| TENSOR3D_T(dst, BUFFER), |
| const int M, |
| const int N, |
| const int K) |
| { |
| #define MMUL_BLOCK_SIZE (MMUL_N0 * MMUL_K0) |
| |
| uint x0 = get_global_id(0); // (N / N0) * MMUL_K0 |
| uint y0 = get_global_id(1); // (M / M0) / MMUL_M0 |
| uint z = get_global_id(2); // Batch |
| |
| // Get block ID and thread ID within the block |
| uint block_id = (x0 / MMUL_BLOCK_SIZE); |
| uint thread_id = (x0 % MMUL_BLOCK_SIZE); |
| |
| // Coordinate within a block |
| uint block_x = thread_id % MMUL_N0; |
| uint block_y = (thread_id / MMUL_M0); |
| |
| // Starting destination coordinates |
| uint dst_x = min(block_x * N0 + block_id * MMUL_N0 * N0, (uint)(N - 1)); |
| uint dst_y = min(block_y * M0 + y0 * M0 * MMUL_M0, (uint)(M - M0)); |
| |
| // Note: We need to clamp dst_x and dst_y because we always need to execute a complete MMUL block! Only after the matrix multiplication |
| // part can we exit the kernel if it is out-of-bound. Remember, we have a cooperative matrix multiplication. Therefore, we need a full block to get the correct results |
| |
| // Starting LHS coordinates |
| uint lhs_x = block_x; |
| uint lhs_y = dst_y; |
| |
| // Starting RHS coordinates |
| uint rhs_x = block_y * N0 * MMUL_N0 + block_x * N0; |
| |
| #ifdef BATCHED_RHS |
| uint rhs_y = block_id + z * rhs_h; |
| #else // BATCHED_RHS |
| uint rhs_y = block_id; |
| #endif // BATCHED_RHS |
| |
| // Compute LHS/RHS/DST matrix address |
| #ifdef REINTERPRET_INPUT_AS_3D |
| lhs_offset_first_element_in_bytes += lhs_x * sizeof(DATA_TYPE) + (lhs_y + z * M) * lhs_stride_y; |
| #else // REINTERPRET_INPUT_AS_3D |
| lhs_offset_first_element_in_bytes += lhs_x * sizeof(DATA_TYPE) + lhs_y * lhs_stride_y + z * lhs_stride_z; |
| #endif // REINTERPRET_INPUT_AS_3D |
| |
| #ifdef REINTERPRET_OUTPUT_AS_3D |
| dst_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE) + (dst_y + z * M) * dst_stride_y; |
| #else // REINTERPRET_OUTPUT_AS_3D |
| dst_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE) + dst_y * dst_stride_y + z * dst_stride_z; |
| #endif // REINTERPRET_OUTPUT_AS_3D |
| |
| // Initialize the accumulators |
| // MMUL extension accumulate the result in F32 for both F32 and F16 |
| TILE(float, M0, N0, c_f32); |
| |
| #if !defined(HALF_PRECISION) |
| #define c c_f32 |
| #endif // !defined(HALF_PRECISION) |
| |
| LOOP_UNROLLING(int, i, 0, 1, M0, |
| { |
| c_f32[i].v = 0; |
| }) |
| |
| for(int k = 0; k <= K - MMUL_K0; k += MMUL_K0) |
| { |
| TILE(DATA_TYPE, M0, 1, a); |
| TILE(DATA_TYPE, 1, N0, b); |
| |
| // Load tile from the lhs/rhs tensors |
| T_LOAD(DATA_TYPE, M0, 1, BUFFER, lhs, 0, 0, 1, lhs_stride_y, a); |
| T_LOAD(DATA_TYPE, 1, N0, IMAGE, rhs, rhs_x, rhs_y, 1, rhs_stride_y, b); |
| |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| LOOP_UNROLLING(int, n0, 0, 1, N0, |
| { |
| c_f32[m0].s[n0] = arm_matrix_multiply(a[m0].s[0], b[0].s[n0], c_f32[m0].s[n0]); |
| }) |
| }) |
| |
| lhs_offset_first_element_in_bytes += MMUL_K0 * sizeof(DATA_TYPE); |
| rhs_x += MMUL_K0 * MMUL_N0 * N0; |
| } |
| |
| if(block_x * N0 + block_id * MMUL_N0 * N0 >= N) |
| { |
| return; |
| } |
| |
| if(block_y * M0 + y0 * M0 * MMUL_M0 >= M) |
| { |
| return; |
| } |
| |
| #if defined(HALF_PRECISION) |
| TILE(DATA_TYPE, M0, N0, c); |
| |
| // Conversion required for the half precision |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| LOOP_UNROLLING(int, n0, 0, 1, N0, |
| { |
| c[m0].s[n0] = c_f32[m0].s[n0]; |
| }) |
| }) |
| #endif // defined(HALF_PRECISION) |
| |
| // Multiply by the weight of matrix-matrix product and store the result |
| #if defined(ALPHA) |
| T_SCALE_CONSTANT(DATA_TYPE, M0, N0, c, (DATA_TYPE)ALPHA, c); |
| #endif // defined(ALPHA) |
| |
| // Add beta*bias |
| #if defined(BETA) |
| #if defined(BROADCAST_BIAS) |
| bia_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE); |
| |
| TILE(DATA_TYPE, 1, N0, bias0); |
| |
| if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| { |
| bias0[0].v = VLOAD(N0)(0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes)); |
| } |
| else |
| { |
| VLOAD_PARTIAL(N0, N0_LEFTOVER) |
| (bias0[0].v, 0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes)); |
| } |
| |
| #ifndef UNIT_BETA |
| T_SCALE_CONSTANT(DATA_TYPE, 1, N0, bias0, (DATA_TYPE)BETA, bias0); |
| #endif // UNIT_BIAS |
| |
| // c = c + bias[broadcasted] |
| T_ELTWISE_BROADCAST_X(V_ADD, DATA_TYPE, M0, N0, c, bias0, c); |
| #else // defined(BROADCAST_BIAS) |
| TILE(DATA_TYPE, M0, N0, bias0); |
| |
| bia_offset_first_element_in_bytes += dst_x * sizeof(DATA_TYPE) + dst_y * bia_stride_y + z * bia_stride_z; |
| |
| if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| bias0[m0].v = VLOAD(N0)(0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes + m0 * bia_stride_y)); |
| } |
| }) |
| } |
| else |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| VLOAD_PARTIAL(N0, N0_LEFTOVER) |
| (bias0[m0].v, 0, (DATA_TYPE *)(bia_ptr + bia_offset_first_element_in_bytes + m0 * bia_stride_y)); |
| } |
| }) |
| } |
| |
| #ifndef UNIT_BETA |
| T_SCALE_CONSTANT(DATA_TYPE, M0, N0, bias0, (DATA_TYPE)BETA, bias0); |
| #endif // UNIT_BIAS |
| |
| // c = c + bias |
| T_ADD(DATA_TYPE, M0, N0, c, bias0, c); |
| // c = c + bias |
| #endif // defined(BROADCAST_BIAS) |
| #endif // defined(BETA) |
| |
| T_ACTIVATION(DATA_TYPE, M0, N0, ACTIVATION_TYPE, A_VAL, B_VAL, c, c); |
| |
| // Store |
| if(dst_x + N0 <= N || N0_LEFTOVER == 0) |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| VSTORE(N0) |
| (c[m0].v, 0, (__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| } |
| }) |
| } |
| else |
| { |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| if(dst_y + m0 < M || M0_LEFTOVER == 0) |
| { |
| VSTORE_PARTIAL(N0, N0_LEFTOVER) |
| (c[m0].v, 0, (__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + m0 * dst_stride_y)); |
| } |
| }) |
| } |
| |
| #undef RHS_BLOCK_SIZE |
| #undef RHS_OFFSET_X |
| #undef RHS_STEP_X |
| } |
| #endif // defined(GEMM_MM_RESHAPED_ONLY_RHS_MMUL_TEXTURE) |