/* * Copyright (c) 2017-2022 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 "gemm_helpers.h" #include "repeat.h" #if defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(DATA_TYPE) #define CONCAT(a, b) a##b #define ARM_DOT1(a, b, c) \ ({ \ c = fma(a, b, c); \ }) #define ARM_DOT2(a, b, c) \ ({ \ c = fma(a.s0, b.s0, c); \ c = fma(a.s1, b.s1, c); \ }) #define ARM_DOT3(a, b, c) \ ({ \ ARM_DOT2(a, b, c); \ c = fma((a.s2), (b.s2), c); \ }) #define ARM_DOT4(a, b, c) \ ({ \ ARM_DOT3(a, b, c); \ c = fma((a.s3), (b.s3), c); \ }) #define ARM_DOT8(a, b, c) \ ({ \ ARM_DOT4((a.lo), (b.lo), c); \ ARM_DOT4((a.hi), (b.hi), c); \ }) #define ARM_DOT16(a, b, c) \ ({ \ ARM_DOT8((a.lo), (b.lo), c); \ ARM_DOT8((a.hi), (b.hi), c); \ }) #if N0 == 2 #define ARM_DOT_K0XN0(k0, a, b, c) \ ({ \ CONCAT(ARM_DOT, k0) \ ((a), (b##0), (c.s0)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##1), (c.s1)); \ }) #elif N0 == 3 // N0 == 3 #define ARM_DOT_K0XN0(k0, a, b, c) \ ({ \ CONCAT(ARM_DOT, k0) \ ((a), (b##0), (c.s0)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##1), (c.s1)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##2), (c.s2)); \ }) #elif N0 == 4 // N0 == 4 #define ARM_DOT_K0XN0(k0, a, b, c) \ ({ \ CONCAT(ARM_DOT, k0) \ ((a), (b##0), (c.s0)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##1), (c.s1)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##2), (c.s2)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##3), (c.s3)); \ }) #elif N0 == 8 // N0 == 8 #define ARM_DOT_K0XN0(k0, a, b, c) \ ({ \ CONCAT(ARM_DOT, k0) \ ((a), (b##0), (c.s0)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##1), (c.s1)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##2), (c.s2)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##3), (c.s3)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##4), (c.s4)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##5), (c.s5)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##6), (c.s6)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##7), (c.s7)); \ }) #elif N0 == 16 // N0 == 16 #define ARM_DOT_K0XN0(k0, a, b, c) \ ({ \ CONCAT(ARM_DOT, k0) \ ((a), (b##0), (c.s0)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##1), (c.s1)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##2), (c.s2)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##3), (c.s3)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##4), (c.s4)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##5), (c.s5)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##6), (c.s6)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##7), (c.s7)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##8), (c.s8)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##9), (c.s9)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##A), (c.sA)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##B), (c.sB)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##C), (c.sC)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##D), (c.sD)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##E), (c.sE)); \ CONCAT(ARM_DOT, k0) \ ((a), (b##F), (c.sF)); \ }) #else // N0 not supported #error "N0 value not supported" #endif // N0 conditions #if defined(GEMM_MM_RESHAPED_ONLY_RHS_T) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. * The LHS matrix is NOT reshaped * The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl * * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters. * @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 K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 * - N0 = 2, 3, 4, 8, 16 * - K0 = 2, 3, 4, 8, 16 * - H0 >= 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 * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix * * @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F16/F32 * @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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_t(IMAGE_DECLARATION(lhs), IMAGE_DECLARATION(rhs), #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_INPUT_AS_3D) , uint lhs_cross_plane_pad #endif // REINTERPRET_INPUT_AS_3D #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Block size #define RHS_BLOCK_SIZE ((K0) * (N0)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (K0) #define RHS_STEP_X ((K0) * (H0)) #define RHS_STEP_LOOP (1) #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X (K0) #define RHS_STEP_LOOP (H0) #endif // defined(RHS_INTERLEAVE) uint x = get_global_id(0); uint y = get_global_id(1); uint z = get_global_id(2); const bool cond_y = y == 0; const bool cond_x = ((x + 1) * N0 >= N); #if defined(DUMMY_WORK_ITEMS) if((x * N0 >= N) || (y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; // Compute RHS reshaped matrix address uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (x / (uint)H0) * rhs_stride_y; #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z; #else // defined(MATRIX_B_DEPTH) rhs_offset += z * rhs_stride_z; #endif // defined(MATRIX_B_DEPTH) REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); //uint zlhs0=0,zlhs1=0,zlhs2=0,... zlhs7=0; REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); #if defined(REINTERPRET_INPUT_AS_3D) // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply lhs_stride_z by DEPTH_GEMM3D lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_INPUT_AS_3D) // Add offset for batched GEMM lhs_offset += z * lhs_stride_z; #endif // defined(REINTERPRET_INPUT_AS_3D) // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(M0-1)=0; int i = 0; for(; i <= (K - K0); i += K0) { // Supported cases (M0, K0): // 1,2 - 1,3 - 1,4 - 1,8 - 1,16 // 2,2 - 2,3 - 2,4 - 2,8 - 2,16 // 3,2 - 3,3 - 3,4 - 3,8 - 3,16 // 4,2 - 4,3 - 4,4 - 4,8 - 4,16 // 5,2 - 5,3 - 5,4 - 5,8 - 5,16 // 6,2 - 6,3 - 6,4 - 6,8 - 6,16 // 7,2 - 7,3 - 7,4 - 7,8 - 7,16 // 8,2 - 8,3 - 8,4 - 8,8 - 8,16 // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); // Load values from RHS reshaped matrix LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X * sizeof(DATA_TYPE), zero); // Accumulate ARM_DOT_K0XN0(K0, a0, b, c0); #if M0 > 1 ARM_DOT_K0XN0(K0, a1, b, c1); #endif // M0 > 1 #if M0 > 2 ARM_DOT_K0XN0(K0, a2, b, c2); #endif // M0 > 2 #if M0 > 3 ARM_DOT_K0XN0(K0, a3, b, c3); #endif // M0 > 3 #if M0 > 4 ARM_DOT_K0XN0(K0, a4, b, c4); #endif // M0 > 4 #if M0 > 5 ARM_DOT_K0XN0(K0, a5, b, c5); #endif // M0 > 5 #if M0 > 6 ARM_DOT_K0XN0(K0, a6, b, c6); #endif // M0 > 6 #if M0 > 7 ARM_DOT_K0XN0(K0, a7, b, c7); #endif // M0 > 7 lhs_offset += K0 * sizeof(DATA_TYPE); rhs_offset += (N0 * RHS_STEP_X * RHS_STEP_LOOP) * sizeof(DATA_TYPE); } // Left-over accumulations for(; i < K; ++i) { // Load values from LHS matrix LOAD_BLOCK(M0, 1, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); // Load values from RHS reshaped matrix LOAD_BLOCK(N0, 1, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X * sizeof(DATA_TYPE), zero); // Accumulate ARM_DOT_K0XN0(1, a0, b, c0); #if M0 > 1 ARM_DOT_K0XN0(1, a1, b, c1); #endif // M0 > 1 #if M0 > 2 ARM_DOT_K0XN0(1, a2, b, c2); #endif // M0 > 2 #if M0 > 3 ARM_DOT_K0XN0(1, a3, b, c3); #endif // M0 > 3 #if M0 > 4 ARM_DOT_K0XN0(1, a4, b, c4); #endif // M0 > 4 #if M0 > 5 ARM_DOT_K0XN0(1, a5, b, c5); #endif // M0 > 5 #if M0 > 6 ARM_DOT_K0XN0(1, a6, b, c6); #endif // M0 > 6 #if M0 > 7 ARM_DOT_K0XN0(1, a7, b, c7); #endif // M0 > 7 lhs_offset += sizeof(DATA_TYPE); rhs_offset += sizeof(DATA_TYPE); } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += z * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += z * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] ADD_BLOCK_BROADCAST(M0, c, bias0); #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias ADD_BLOCK(M0, c, bias); #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(ACTIVATION_TYPE) // Store output block STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X #undef RHS_STEP_LOOP } #endif // defined(GEMM_MM_RESHAPED_ONLY_RHS_T) #if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_T_TEXTURE) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. The RHS matrix is stored in OpenCL image * The LHS matrix is NOT reshaped * The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl * * @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters. * @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT= (e.g. -DRHS_HEIGHT=32) * Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT * could be different from the value returned by get_image_height(rhs_img). * @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 K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 * - N0 = 4, 8, 16 * - K0 = 4, 8, 16 * - H0 >= 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 * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix * * @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F32 * @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix * @param[in] rhs_img The RHS reshaped matrix as OpenCL image object. Supported data type: same as @p lhs_ptr * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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_t_texture(IMAGE_DECLARATION(lhs), __read_only image2d_t rhs_img, #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_INPUT_AS_3D) , uint lhs_cross_plane_pad #endif // REINTERPRET_INPUT_AS_3D #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Pixel unit #define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(K0) const uint LEFTOVER_K = K % K0; // Block size #define RHS_BLOCK_SIZE (PIXEL_UNIT * (N0)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (PIXEL_UNIT) #define RHS_STEP_X (PIXEL_UNIT * (H0)) #define RHS_STEP_LOOP (1) #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X PIXEL_UNIT #define RHS_STEP_LOOP (H0) #endif // defined(RHS_INTERLEAVE) uint x = get_global_id(0); uint y = get_global_id(1); uint z = get_global_id(2); const bool cond_y = y == 0; const bool cond_x = ((x + 1) * N0 >= N); #if defined(DUMMY_WORK_ITEMS) if((x * N0 >= N) || (y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 const uint z_rhs = (get_global_id(2) % MATRIX_B_DEPTH); #else // defined(MATRIX_B_DEPTH) const uint z_rhs = get_global_id(2); #endif // defined(MATRIX_B_DEPTH) // Compute RHS matrix coordinates uint x_rhs = (get_global_id(0) % H0) * (uint)RHS_OFFSET_X; const uint y_rhs = (get_global_id(0) / (uint)H0) + z_rhs * RHS_HEIGHT; REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0); REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); #if defined(REINTERPRET_INPUT_AS_3D) // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply lhs_stride_z by DEPTH_GEMM3D lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_INPUT_AS_3D) // Add offset for batched GEMM lhs_offset += z * lhs_stride_z; #endif // defined(REINTERPRET_INPUT_AS_3D) // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); int i = 0; for(; i <= (K - K0); i += K0) { // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); // Load values from RHS matrix stored in a cl_image REPEAT_VAR_INIT_TO_CONST(N0, VEC_DATA_TYPE(DATA_TYPE, K0), b, 0); LOAD_TEXTURE2D(N0, PIXEL_UNIT, DATA_TYPE, b, rhs_img, x_rhs, y_rhs, RHS_STEP_X, 0); // Accumulate ARM_DOT_K0XN0(K0, a0, b, c0); #if M0 > 1 ARM_DOT_K0XN0(K0, a1, b, c1); #endif // M0 > 1 #if M0 > 2 ARM_DOT_K0XN0(K0, a2, b, c2); #endif // M0 > 2 #if M0 > 3 ARM_DOT_K0XN0(K0, a3, b, c3); #endif // M0 > 3 #if M0 > 4 ARM_DOT_K0XN0(K0, a4, b, c4); #endif // M0 > 4 #if M0 > 5 ARM_DOT_K0XN0(K0, a5, b, c5); #endif // M0 > 5 #if M0 > 6 ARM_DOT_K0XN0(K0, a6, b, c6); #endif // M0 > 6 #if M0 > 7 ARM_DOT_K0XN0(K0, a7, b, c7); #endif // M0 > 7 lhs_offset += K0 * sizeof(DATA_TYPE); x_rhs += N0 * RHS_STEP_X * RHS_STEP_LOOP; } if(LEFTOVER_K != 0) { // Note: We cannot read out-of-bound elements from the RHS matrix because // the RHS width is always multiple of K0. This is not be true for the LHS matrix // Left-over accumulations for LHS matrix union UNION_VEC_TYPE { DATA_TYPE s[K0]; VEC_DATA_TYPE(DATA_TYPE, K0) v; }; union UNION_VEC_TYPE a0 = {.v = 0 }; #if M0 > 1 union UNION_VEC_TYPE a1 = {.v = 0 }; #endif // M0 > 1 #if M0 > 2 union UNION_VEC_TYPE a2 = {.v = 0 }; #endif // M0 > 2 #if M0 > 3 union UNION_VEC_TYPE a3 = {.v = 0 }; #endif // M0 > 3 #if M0 > 4 union UNION_VEC_TYPE a4 = {.v = 0 }; #endif // M0 > 4 #if M0 > 5 union UNION_VEC_TYPE a5 = {.v = 0 }; #endif // M0 > 5 #if M0 > 6 union UNION_VEC_TYPE a6 = {.v = 0 }; #endif // M0 > 6 #if M0 > 7 union UNION_VEC_TYPE a7 = {.v = 0 }; #endif // M0 > 7 REPEAT_VAR_INIT_TO_CONST(N0, VEC_DATA_TYPE(DATA_TYPE, K0), b, 0); // Load from RHS matrix LOAD_TEXTURE2D(N0, PIXEL_UNIT, DATA_TYPE, b, rhs_img, x_rhs, y_rhs, RHS_STEP_X, 0); // Load from LHS matrix for(int k = 0; k < LEFTOVER_K; ++k) { a0.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zlhs0); #if M0 > 1 a1.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zlhs1); #endif // M0 > 1 #if M0 > 2 a2.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zlhs2); #endif // M0 > 2 #if M0 > 3 a3.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zlhs3); #endif // M0 > 3 #if M0 > 4 a4.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zlhs4); #endif // M0 > 4 #if M0 > 5 a5.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zlhs5); #endif // M0 > 5 #if M0 > 6 a6.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zlhs6); #endif // M0 > 6 #if M0 > 7 a7.s[k] = *(__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zlhs7); #endif // M0 > 7 lhs_offset += sizeof(DATA_TYPE); } // Accumulate ARM_DOT_K0XN0(K0, a0.v, b, c0); #if M0 > 1 ARM_DOT_K0XN0(K0, a1.v, b, c1); #endif // M0 > 1 #if M0 > 2 ARM_DOT_K0XN0(K0, a2.v, b, c2); #endif // M0 > 2 #if M0 > 3 ARM_DOT_K0XN0(K0, a3.v, b, c3); #endif // M0 > 3 #if M0 > 4 ARM_DOT_K0XN0(K0, a4.v, b, c4); #endif // M0 > 4 #if M0 > 5 ARM_DOT_K0XN0(K0, a5.v, b, c5); #endif // M0 > 5 #if M0 > 6 ARM_DOT_K0XN0(K0, a6.v, b, c6); #endif // M0 > 6 #if M0 > 7 ARM_DOT_K0XN0(K0, a7.v, b, c7); #endif // M0 > 7 } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += z * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += z * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] ADD_BLOCK_BROADCAST(M0, c, bias0); #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias ADD_BLOCK(M0, c, bias); #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(ACTIVATION_TYPE) // Store output block STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X #undef RHS_STEP_LOOP #undef PIXEL_UNIT } #endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_T_TEXTURE) #define VFMA(a, b, c) \ ({ \ c = fma(a, b, c); \ }) #if M0 == 1 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ }) #elif M0 == 2 // M0 == 2 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ }) #elif M0 == 3 // M0 == 3 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ }) #elif M0 == 4 // M0 == 4 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ }) #elif M0 == 5 // M0 == 5 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ }) #elif M0 == 6 // M0 == 6 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ }) #elif M0 == 7 // M0 == 7 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \ }) #elif M0 == 8 // M0 == 8 #define VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##7).s##i), b, (c##7)); \ }) #else // M0 not supported #error "M0 not supported" #endif // M0 not supported #if defined(GEMM_MM_RESHAPED_ONLY_RHS_NT) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. * The LHS matrix is NOT reshaped * The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is NOT transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl * * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters. * @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 K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 * - N0 = 2, 3, 4, 8, 16 * - K0 = 2, 3, 4, 8, 16 * - H0 >= 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 * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix * * @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F16/F32 * @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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(IMAGE_DECLARATION(lhs), IMAGE_DECLARATION(rhs), #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_INPUT_AS_3D) , uint lhs_cross_plane_pad #endif // REINTERPRET_INPUT_AS_3D #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Block size #define RHS_BLOCK_SIZE ((K0) * (N0)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (N0) #define RHS_STEP_X ((N0) * (H0)) #define RHS_STEP_LOOP (1) #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X (N0) #define RHS_STEP_LOOP (H0) #endif // defined(RHS_INTERLEAVE) uint x = get_global_id(0); uint y = get_global_id(1); uint z = get_global_id(2); const bool cond_y = y == 0; const bool cond_x = ((x + 1) * N0 >= N); #if defined(DUMMY_WORK_ITEMS) if((x * N0 >= N) || (y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; // Compute RHS reshaped matrix address uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (x / (uint)H0) * rhs_stride_y; #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z; #else // defined(MATRIX_B_DEPTH) rhs_offset += z * rhs_stride_z; #endif // defined(MATRIX_B_DEPTH) REPEAT_VAR_INIT_TO_CONST(8, uint, zin, 0); //uint zin0=0,zin1=0,zin2=0,... zin7=0; REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); //uint zero0=0,zero1=0,zero2=0,... zero7=0; #if defined(REINTERPRET_INPUT_AS_3D) // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zin, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply lhs_stride_z by DEPTH_GEMM3D lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_INPUT_AS_3D) // Add offset for batched GEMM lhs_offset += z * lhs_stride_z; #endif // defined(REINTERPRET_INPUT_AS_3D) // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(N0-1)=0; int i = 0; for(; i <= (K - K0); i += K0) { // Supported cases (M0, K0): // 1,2 - 1,3 - 1,4 - 1,8 - 1,16 // 2,2 - 2,3 - 2,4 - 2,8 - 2,16 // 3,2 - 3,3 - 3,4 - 3,8 - 3,16 // 4,2 - 4,3 - 4,4 - 4,8 - 4,16 // 5,2 - 5,3 - 5,4 - 5,8 - 5,16 // 6,2 - 6,3 - 6,4 - 6,8 - 6,16 // 7,2 - 7,3 - 7,4 - 7,8 - 7,16 // 8,2 - 8,3 - 8,4 - 8,8 - 8,16 // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zin); VEC_DATA_TYPE(DATA_TYPE, N0) b0; b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 0 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(0, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 1 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(1, a, b0, c); #if K0 > 2 b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 2 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(2, a, b0, c); #endif // K0 > 2 #if K0 > 3 b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 3 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(3, a, b0, c); #endif // K0 > 3 #if K0 > 4 b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 4 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(4, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 5 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(5, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 6 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(6, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 7 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(7, a, b0, c); #endif // K0 > 4 #if K0 > 8 b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 8 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(8, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 9 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(9, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 10 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(A, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 11 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(B, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 12 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(C, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 13 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(D, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 14 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(E, a, b0, c); b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 15 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(F, a, b0, c); #endif // K0 > 8 lhs_offset += K0 * sizeof(DATA_TYPE); rhs_offset += K0 * RHS_STEP_X * RHS_STEP_LOOP * sizeof(DATA_TYPE); } // Left-over accumulations for(; i < K; ++i) { // Load values from LHS matrix VEC_DATA_TYPE(DATA_TYPE, 2) a0 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zin0)); #if M0 > 1 VEC_DATA_TYPE(DATA_TYPE, 2) a1 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zin1)); #endif // M0 > 1 #if M0 > 2 VEC_DATA_TYPE(DATA_TYPE, 2) a2 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zin2)); #endif // M0 > 2 #if M0 > 3 VEC_DATA_TYPE(DATA_TYPE, 2) a3 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zin3)); #endif // M0 > 3 #if M0 > 4 VEC_DATA_TYPE(DATA_TYPE, 2) a4 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zin4)); #endif // M0 > 4 #if M0 > 5 VEC_DATA_TYPE(DATA_TYPE, 2) a5 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zin5)); #endif // M0 > 5 #if M0 > 6 VEC_DATA_TYPE(DATA_TYPE, 2) a6 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zin6)); #endif // M0 > 6 #if M0 > 7 VEC_DATA_TYPE(DATA_TYPE, 2) a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zin7)); #endif // M0 > 7 VEC_DATA_TYPE(DATA_TYPE, N0) b0; b0 = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 0 * RHS_STEP_X * sizeof(DATA_TYPE))); VFMA_M0xN0(0, a, b0, c); lhs_offset += sizeof(DATA_TYPE); rhs_offset += RHS_STEP_X * sizeof(DATA_TYPE); } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += z * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += z * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] ADD_BLOCK_BROADCAST(M0, c, bias0); #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias ADD_BLOCK(M0, c, bias); #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(ACTIVATION_TYPE) // Store output block STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X #undef RHS_STEP_LOOP } #endif // defined(GEMM_MM_RESHAPED_ONLY_RHS_NT) #if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_NT_TEXTURE) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. * The LHS matrix is NOT reshaped * The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is NOT transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped_only_rhs.cl * * @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters. * @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT= (e.g. -DRHS_HEIGHT=32) * Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT * could be different from the value returned by get_image_height(rhs_img). * @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 K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 * - N0 = 4, 8, 16 * - K0 = 4, 8, 16 * - H0 >= 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 * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix * * @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F32 * @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix * @param[in] rhs_img The RHS reshaped matrix as OpenCL image object. Supported data type: same as @p lhs_ptr * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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_texture(IMAGE_DECLARATION(lhs), __read_only image2d_t rhs_img, #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_INPUT_AS_3D) , uint lhs_cross_plane_pad #endif // REINTERPRET_INPUT_AS_3D #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Pixel unit #define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(N0) // Block size #define RHS_BLOCK_SIZE ((K0) * (PIXEL_UNIT)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (PIXEL_UNIT) #define RHS_STEP_X ((PIXEL_UNIT) * (H0)) #define RHS_STEP_LOOP 1 #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X (PIXEL_UNIT) #define RHS_STEP_LOOP (H0) #endif // defined(RHS_INTERLEAVE) uint x = get_global_id(0); uint y = get_global_id(1); uint z = get_global_id(2); const bool cond_y = y == 0; const bool cond_x = ((x + 1) * N0 >= N); #if defined(DUMMY_WORK_ITEMS) if((x * N0 >= N) || (y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 const uint z_rhs = (z % MATRIX_B_DEPTH); #else // defined(MATRIX_B_DEPTH) const uint z_rhs = z; #endif // defined(MATRIX_B_DEPTH) // Compute RHS matrix coordinates uint x_rhs = (x % H0) * (uint)RHS_OFFSET_X; const uint y_rhs = (x / (uint)H0) + z_rhs * RHS_HEIGHT; REPEAT_VAR_INIT_TO_CONST(8, uint, zin, 0); REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); #if defined(REINTERPRET_INPUT_AS_3D) // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zin, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply lhs_stride_z by DEPTH_GEMM3D lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_INPUT_AS_3D) // Add offset for batched GEMM lhs_offset += z * lhs_stride_z; #endif // defined(REINTERPRET_INPUT_AS_3D) // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); int i = 0; for(; i <= (K - K0); i += K0) { // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zin); VEC_DATA_TYPE(DATA_TYPE, N0) b0; b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 0 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(0, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 1 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(1, a, b0, c); #if K0 > 2 b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 2 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(2, a, b0, c); #endif // K0 > 2 #if K0 > 3 b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 3 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(3, a, b0, c); #endif // K0 > 3 #if K0 > 4 b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 4 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(4, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 5 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(5, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 6 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(6, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 7 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(7, a, b0, c); #endif // K0 > 4 #if K0 > 8 b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 8 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(8, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 9 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(9, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 10 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(A, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 11 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(B, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 12 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(C, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 13 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(D, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 14 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(E, a, b0, c); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 15 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(F, a, b0, c); #endif // K0 > 8 lhs_offset += K0 * sizeof(DATA_TYPE); x_rhs += K0 * RHS_STEP_X * RHS_STEP_LOOP; } // Left-over accumulations for(; i < K; ++i) { // Load values from LHS matrix VEC_DATA_TYPE(DATA_TYPE, 2) a0 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zin0)); #if M0 > 1 VEC_DATA_TYPE(DATA_TYPE, 2) a1 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zin1)); #endif // M0 > 1 #if M0 > 2 VEC_DATA_TYPE(DATA_TYPE, 2) a2 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zin2)); #endif // M0 > 2 #if M0 > 3 VEC_DATA_TYPE(DATA_TYPE, 2) a3 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zin3)); #endif // M0 > 3 #if M0 > 4 VEC_DATA_TYPE(DATA_TYPE, 2) a4 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zin4)); #endif // M0 > 4 #if M0 > 5 VEC_DATA_TYPE(DATA_TYPE, 2) a5 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zin5)); #endif // M0 > 5 #if M0 > 6 VEC_DATA_TYPE(DATA_TYPE, 2) a6 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zin6)); #endif // M0 > 6 #if M0 > 7 VEC_DATA_TYPE(DATA_TYPE, 2) a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zin7)); #endif // M0 > 7 VEC_DATA_TYPE(DATA_TYPE, N0) b0; b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 0 * RHS_STEP_X), (y_rhs)); VFMA_M0xN0(0, a, b0, c); lhs_offset += sizeof(DATA_TYPE); x_rhs += RHS_STEP_X; } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += z * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += z * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] ADD_BLOCK_BROADCAST(M0, c, bias0); #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias ADD_BLOCK(M0, c, bias); #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(ACTIVATION_TYPE) // Store output block STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X #undef RHS_STEP_LOOP } #endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_ONLY_RHS_NT_TEXTURE) #endif // defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(DATA_TYPE) #if defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(DATA_TYPE) && defined(DATA_TYPE_ACCUMULATOR) #if defined(MIXED_PRECISION) #if K0 == 2 #define ARM_DOT_K0(a, b, c) \ ({ \ c += a.s0 * b.s0; \ c += a.s1 * b.s1; \ }) #elif K0 == 3 // K0 == 3 #define ARM_DOT_K0(a, b, c) \ ({ \ c += a.s0 * b.s0; \ c += a.s1 * b.s1; \ c += a.s2 * b.s2; \ }) #elif K0 == 4 // K0 == 4 #define ARM_DOT_K0(a, b, c) \ ({ \ c += a.s0 * b.s0; \ c += a.s1 * b.s1; \ c += a.s2 * b.s2; \ c += a.s3 * b.s3; \ }) #elif K0 == 8 // K0 == 8 #define ARM_DOT_K0(a, b, c) \ ({ \ c += a.s0 * b.s0; \ c += a.s1 * b.s1; \ c += a.s2 * b.s2; \ c += a.s3 * b.s3; \ c += a.s4 * b.s4; \ c += a.s5 * b.s5; \ c += a.s6 * b.s6; \ c += a.s7 * b.s7; \ }) #elif K0 == 16 // K0 == 16 #define ARM_DOT_K0(a, b, c) \ ({ \ c += a.s0 * b.s0; \ c += a.s1 * b.s1; \ c += a.s2 * b.s2; \ c += a.s3 * b.s3; \ c += a.s4 * b.s4; \ c += a.s5 * b.s5; \ c += a.s6 * b.s6; \ c += a.s7 * b.s7; \ c += a.s8 * b.s8; \ c += a.s9 * b.s9; \ c += a.sA * b.sA; \ c += a.sB * b.sB; \ c += a.sC * b.sC; \ c += a.sD * b.sD; \ c += a.sE * b.sE; \ c += a.sF * b.sF; \ }) #else // K0 not supported #error "K0 value not supported" #endif // K0 conditions #else // defined(MIXED_PRECISION) #if K0 == 2 #define ARM_DOT_K0(a, b, c) \ ({ \ c = fma(a.s0, b.s0, c); \ c = fma(a.s1, b.s1, c); \ }) #elif K0 == 3 // K0 == 3 #define ARM_DOT_K0(a, b, c) \ ({ \ c = fma(a.s0, b.s0, c); \ c = fma(a.s1, b.s1, c); \ c = fma(a.s2, b.s2, c); \ }) #elif K0 == 4 // K0 == 4 #define ARM_DOT_K0(a, b, c) \ ({ \ c = fma(a.s0, b.s0, c); \ c = fma(a.s1, b.s1, c); \ c = fma(a.s2, b.s2, c); \ c = fma(a.s3, b.s3, c); \ }) #elif K0 == 8 // K0 == 8 #define ARM_DOT_K0(a, b, c) \ ({ \ c = fma(a.s0, b.s0, c); \ c = fma(a.s1, b.s1, c); \ c = fma(a.s2, b.s2, c); \ c = fma(a.s3, b.s3, c); \ c = fma(a.s4, b.s4, c); \ c = fma(a.s5, b.s5, c); \ c = fma(a.s6, b.s6, c); \ c = fma(a.s7, b.s7, c); \ }) #elif K0 == 16 // K0 == 16 #define ARM_DOT_K0(a, b, c) \ ({ \ c = fma(a.s0, b.s0, c); \ c = fma(a.s1, b.s1, c); \ c = fma(a.s2, b.s2, c); \ c = fma(a.s3, b.s3, c); \ c = fma(a.s4, b.s4, c); \ c = fma(a.s5, b.s5, c); \ c = fma(a.s6, b.s6, c); \ c = fma(a.s7, b.s7, c); \ c = fma(a.s8, b.s8, c); \ c = fma(a.s9, b.s9, c); \ c = fma(a.sA, b.sA, c); \ c = fma(a.sB, b.sB, c); \ c = fma(a.sC, b.sC, c); \ c = fma(a.sD, b.sD, c); \ c = fma(a.sE, b.sE, c); \ c = fma(a.sF, b.sF, c); \ }) #else // K0 not supported #error "K0 value not supported" #endif // K0 conditions #endif // defined(MIXED_PRECISION) #if defined(ARM_DOT_K0XN0) #undef ARM_DOT_K0XN0 #endif // defined(ARM_DOT_K0XN0) #if N0 == 2 #define ARM_DOT_K0XN0(a, b, c) \ ({ \ ARM_DOT_K0((a), (b##0), (c.s0)); \ ARM_DOT_K0((a), (b##1), (c.s1)); \ }) #elif N0 == 3 // N0 == 3 #define ARM_DOT_K0XN0(a, b, c) \ ({ \ ARM_DOT_K0((a), (b##0), (c.s0)); \ ARM_DOT_K0((a), (b##1), (c.s1)); \ ARM_DOT_K0((a), (b##2), (c.s2)); \ }) #elif N0 == 4 // N0 == 4 #define ARM_DOT_K0XN0(a, b, c) \ ({ \ ARM_DOT_K0((a), (b##0), (c.s0)); \ ARM_DOT_K0((a), (b##1), (c.s1)); \ ARM_DOT_K0((a), (b##2), (c.s2)); \ ARM_DOT_K0((a), (b##3), (c.s3)); \ }) #elif N0 == 8 // N0 == 8 #define ARM_DOT_K0XN0(a, b, c) \ ({ \ ARM_DOT_K0((a), (b##0), (c.s0)); \ ARM_DOT_K0((a), (b##1), (c.s1)); \ ARM_DOT_K0((a), (b##2), (c.s2)); \ ARM_DOT_K0((a), (b##3), (c.s3)); \ ARM_DOT_K0((a), (b##4), (c.s4)); \ ARM_DOT_K0((a), (b##5), (c.s5)); \ ARM_DOT_K0((a), (b##6), (c.s6)); \ ARM_DOT_K0((a), (b##7), (c.s7)); \ }) #elif N0 == 16 // N0 == 16 #define ARM_DOT_K0XN0(a, b, c) \ ({ \ ARM_DOT_K0((a), (b##0), (c.s0)); \ ARM_DOT_K0((a), (b##1), (c.s1)); \ ARM_DOT_K0((a), (b##2), (c.s2)); \ ARM_DOT_K0((a), (b##3), (c.s3)); \ ARM_DOT_K0((a), (b##4), (c.s4)); \ ARM_DOT_K0((a), (b##5), (c.s5)); \ ARM_DOT_K0((a), (b##6), (c.s6)); \ ARM_DOT_K0((a), (b##7), (c.s7)); \ ARM_DOT_K0((a), (b##8), (c.s8)); \ ARM_DOT_K0((a), (b##9), (c.s9)); \ ARM_DOT_K0((a), (b##A), (c.sA)); \ ARM_DOT_K0((a), (b##B), (c.sB)); \ ARM_DOT_K0((a), (b##C), (c.sC)); \ ARM_DOT_K0((a), (b##D), (c.sD)); \ ARM_DOT_K0((a), (b##E), (c.sE)); \ ARM_DOT_K0((a), (b##F), (c.sF)); \ }) #else // N0 not supported #error "N0 value not supported" #endif // N0 conditions #if defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. * The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be NOT transposed * The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl * * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float) * @note The data type used for the accumulators must be passed at compile time using -DDATA_TYPE_ACCUMULATOR (e.g. -DDATA_TYPE_ACCUMULATOR=float) * @note The F16 computation also supports mixed precision through the option -DMIXED_PRECISION passed at compile time. If enabled, DATA_TYPE_ACCUMULATOR should be set to float * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions M, N and K must be passed at compile time using -DM, -DN and -DK (e.g. -DM=52, -DN=90 and -DK=24). * @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4). * @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2) * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time. * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 2, 3, 4, 5, 6, 7, 8 * - N0 = 2, 3, 4, 8, 16 * - K0 = 2, 3, 4, 8, 16 * - V0 >= 1 * - H0 >= 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 * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time: * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped * * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F16/F32 * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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_lhs_nt_rhs_t(IMAGE_DECLARATION(lhs), IMAGE_DECLARATION(rhs), #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Block size #define LHS_BLOCK_SIZE ((K0) * (M0)) #if defined(LHS_INTERLEAVE) #define LHS_OFFSET_X (K0) #define LHS_STEP_X ((K0) * (V0)) #define LHS_STEP_LOOP (1) #else // defined(INTERLEAVE) #define LHS_OFFSET_X (LHS_BLOCK_SIZE) #define LHS_STEP_X (K0) #define LHS_STEP_LOOP (V0) #endif // defined(INTERLEAVE) // Block size #define RHS_BLOCK_SIZE ((K0) * (N0)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (K0) #define RHS_STEP_X ((K0) * (H0)) #define RHS_STEP_LOOP (1) #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X (K0) #define RHS_STEP_LOOP (H0) #endif // defined(RHS_INTERLEAVE) #if defined(DUMMY_WORK_ITEMS) if((get_global_id(0) * N0 >= N) || (get_global_id(1) * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address __global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (get_global_id(1) % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (get_global_id(1) / V0) * (uint)lhs_stride_y + (get_global_id(2) * lhs_stride_z); // Compute RHS matrix address __global uchar *rhs_addr = rhs_ptr + rhs_offset_first_element_in_bytes + (get_global_id(0) % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (get_global_id(0) / (uint)H0) * rhs_stride_y; #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 rhs_addr += (get_global_id(2) % MATRIX_B_DEPTH) * rhs_stride_z; #else // defined(MATRIX_B_DEPTH) rhs_addr += get_global_id(2) * rhs_stride_z; #endif // defined(MATRIX_B_DEPTH) // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0); REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0); //uint zlhs0=0,zlhs1=0,zlhs2=0,... zlhs7=0; REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); for(int i = 0; i < K; i += K0) { // Supported cases (M0, K0): // 1,2 - 1,3 - 1,4 - 1,8 - 1,16 // 2,2 - 2,3 - 2,4 - 2,8 - 2,16 // 3,2 - 3,3 - 3,4 - 3,8 - 3,16 // 4,2 - 4,3 - 4,4 - 4,8 - 4,16 // 5,2 - 5,3 - 5,4 - 5,8 - 5,16 // 6,2 - 6,3 - 6,4 - 6,8 - 6,16 // 7,2 - 7,3 - 7,4 - 7,8 - 7,16 // 8,2 - 8,3 - 8,4 - 8,8 - 8,16 // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_addr, 0, LHS_STEP_X * sizeof(DATA_TYPE), zlhs); // Load values from RHS matrix LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_addr, 0, RHS_STEP_X * sizeof(DATA_TYPE), zero); // Accumulate ARM_DOT_K0XN0(a0, b, c0); #if M0 > 1 ARM_DOT_K0XN0(a1, b, c1); #endif // M0 > 1 #if M0 > 2 ARM_DOT_K0XN0(a2, b, c2); #endif // M0 > 2 #if M0 > 3 ARM_DOT_K0XN0(a3, b, c3); #endif // M0 > 3 #if M0 > 4 ARM_DOT_K0XN0(a4, b, c4); #endif // M0 > 4 #if M0 > 5 ARM_DOT_K0XN0(a5, b, c5); #endif // M0 > 5 #if M0 > 6 ARM_DOT_K0XN0(a6, b, c6); #endif // M0 > 6 #if M0 > 7 ARM_DOT_K0XN0(a7, b, c7); #endif // M0 > 7 lhs_addr += (M0 * LHS_STEP_X * LHS_STEP_LOOP) * sizeof(DATA_TYPE); rhs_addr += (N0 * RHS_STEP_X * RHS_STEP_LOOP) * sizeof(DATA_TYPE); } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); const bool cond_y = ((get_global_id(1) + 1) * M0 >= M); const bool cond_x = ((get_global_id(0) + 1) * N0 >= N); #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, get_global_id(1) * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += get_global_id(2) * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += get_global_id(2) * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] #if defined(MIXED_PRECISION) CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK_BROADCAST(M0, c, bias_hp0); #else // defined(MIXED_PRECISION) ADD_BLOCK_BROADCAST(M0, c, bias0); #endif // defined(MIXED_PRECISION) #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * bias_stride_y) + get_global_id( 2) * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK(M0, c, bias_hp); #else // defined(MIXED_PRECISION) ADD_BLOCK(M0, c, bias); #endif // defined(MIXED_PRECISION) #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) #if defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, N0, c, A_VAL, B_VAL); #else // defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(MIXED_PRECISION) #endif // defined(ACTIVATION_TYPE) // Store output block #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp); STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #else // defined(MIXED_PRECISION) STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #endif // defined(MIXED_PRECISION) #undef LHS_BLOCK_SIZE #undef LHS_OFFSET_X #undef LHS_STEP_X #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X #undef LHS_STEP_LOOP #undef RHS_STEP_LOOP } #endif // defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T) #if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T_TEXTURE) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. The RHS matrix is stored in OpenCL image object. * The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be NOT transposed * The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl * * @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float) * @note The data type used for the accumulators must be passed at compile time using -DDATA_TYPE_ACCUMULATOR (e.g. -DDATA_TYPE_ACCUMULATOR=float) * @note The F16 computation also supports mixed precision through the option -DMIXED_PRECISION passed at compile time. If enabled, DATA_TYPE_ACCUMULATOR should be set to float * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions M, N and K must be passed at compile time using -DM, -DN and -DK (e.g. -DM=52, -DN=90 and -DK=24). * @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT= (e.g. -DRHS_HEIGHT=32) * Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT * could be different from the value returned by get_image_height(rhs_img). * @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4). * @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2) * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time. * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 2, 3, 4, 5, 6, 7, 8 * - N0 = 4, 8, 16 * - K0 = 4, 8, 16 * - V0 >= 1 * - H0 >= 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 * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time: * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped * * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F32 * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix * @param[in] rhs_img The RHS reshaped matrix as OpenCL image object. Supported data type: same as @p lhs_ptr * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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_lhs_nt_rhs_t_texture(IMAGE_DECLARATION(lhs), __read_only image2d_t rhs_img, #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Pixel unit #define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(K0) // Block size #define LHS_BLOCK_SIZE ((K0) * (M0)) #if defined(LHS_INTERLEAVE) #define LHS_OFFSET_X (K0) #define LHS_STEP_X ((K0) * (V0)) #define LHS_STEP_LOOP (1) #else // defined(INTERLEAVE) #define LHS_OFFSET_X (LHS_BLOCK_SIZE) #define LHS_STEP_X (K0) #define LHS_STEP_LOOP (V0) #endif // defined(INTERLEAVE) // Block size #define RHS_BLOCK_SIZE (PIXEL_UNIT * (N0)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (PIXEL_UNIT) #define RHS_STEP_X (PIXEL_UNIT * (H0)) #define RHS_STEP_LOOP (1) #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X PIXEL_UNIT #define RHS_STEP_LOOP (H0) #endif // defined(RHS_INTERLEAVE) #if defined(DUMMY_WORK_ITEMS) if((get_global_id(0) * N0 >= N) || (get_global_id(1) * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address __global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (get_global_id(1) % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (get_global_id(1) / V0) * (uint)lhs_stride_y + (get_global_id(2) * lhs_stride_z); #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 const uint z_rhs = (get_global_id(2) % MATRIX_B_DEPTH); #else // defined(MATRIX_B_DEPTH) const uint z_rhs = get_global_id(2); #endif // defined(MATRIX_B_DEPTH) // Compute RHS matrix coordinates uint x_rhs = (get_global_id(0) % H0) * (uint)RHS_OFFSET_X; const uint y_rhs = (get_global_id(0) / (uint)H0) + z_rhs * RHS_HEIGHT; // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0); REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0); //uint zlhs0=0,zlhs1=0,zlhs2=0,... zlhs7=0; REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); for(int i = 0; i < K; i += K0) { // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_addr, 0, LHS_STEP_X * sizeof(DATA_TYPE), zlhs); // Load values from RHS matrix stored in a cl_image REPEAT_VAR_INIT_TO_CONST(N0, VEC_DATA_TYPE(DATA_TYPE, K0), b, 0); LOAD_TEXTURE2D(N0, PIXEL_UNIT, DATA_TYPE, b, rhs_img, x_rhs, y_rhs, RHS_STEP_X, 0); // Accumulate ARM_DOT_K0XN0(a0, b, c0); #if M0 > 1 ARM_DOT_K0XN0(a1, b, c1); #endif // M0 > 1 #if M0 > 2 ARM_DOT_K0XN0(a2, b, c2); #endif // M0 > 2 #if M0 > 3 ARM_DOT_K0XN0(a3, b, c3); #endif // M0 > 3 #if M0 > 4 ARM_DOT_K0XN0(a4, b, c4); #endif // M0 > 4 #if M0 > 5 ARM_DOT_K0XN0(a5, b, c5); #endif // M0 > 5 #if M0 > 6 ARM_DOT_K0XN0(a6, b, c6); #endif // M0 > 6 #if M0 > 7 ARM_DOT_K0XN0(a7, b, c7); #endif // M0 > 7 lhs_addr += (M0 * LHS_STEP_X * LHS_STEP_LOOP) * sizeof(DATA_TYPE); x_rhs += N0 * RHS_STEP_X * RHS_STEP_LOOP; } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); const bool cond_y = ((get_global_id(1) + 1) * M0 >= M); const bool cond_x = ((get_global_id(0) + 1) * N0 >= N); #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, get_global_id(1) * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += get_global_id(2) * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += get_global_id(2) * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] #if defined(MIXED_PRECISION) CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK_BROADCAST(M0, c, bias_hp0); #else // defined(MIXED_PRECISION) ADD_BLOCK_BROADCAST(M0, c, bias0); #endif // defined(MIXED_PRECISION) #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * bias_stride_y) + get_global_id( 2) * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK(M0, c, bias_hp); #else // defined(MIXED_PRECISION) ADD_BLOCK(M0, c, bias); #endif // defined(MIXED_PRECISION) #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) #if defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, N0, c, A_VAL, B_VAL); #else // defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(MIXED_PRECISION) #endif // defined(ACTIVATION_TYPE) // Store output block #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp); STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #else // defined(MIXED_PRECISION) STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #endif // defined(MIXED_PRECISION) #undef LHS_BLOCK_SIZE #undef LHS_OFFSET_X #undef LHS_STEP_X #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X #undef PIXEL_UNIT #undef LHS_STEP_LOOP #undef RHS_STEP_LOOP } #endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_NT_RHS_T_TEXTURE) #if defined(LHS_TRANSPOSE) #define VTYPE(TYPE, SIZE) VEC_DATA_TYPE(TYPE, SIZE) #if defined(MIXED_PRECISION) #if(GPU_ARCH == GPU_ARCH_MIDGARD) #define ARM_VFMA(N0, a, b, c) c += (CONVERT(a, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0))) * (CONVERT(b, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0))); #else // GPU_ARCH == GPU_ARCH_MIDGARD #define ARM_VFMA(N0, a, b, c) c = fma((CONVERT(a, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0))), (CONVERT(b, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0))), (c)); #endif // GPU_ARCH == GPU_ARCH_MIDGARD #else // defined(MIXED_PRECISION #if(GPU_ARCH == GPU_ARCH_MIDGARD) #define ARM_VFMA(N0, a, b, c) c += (a) * (b); #else // GPU_ARCH == GPU_ARCH_MIDGARD #define ARM_VFMA(N0, a, b, c) c = fma((a), (b), (c)); #endif // GPU_ARCH == GPU_ARCH_MIDGARD #endif // defined(MIXED_PRECISION) #define ARM_VVM_T_NT_1xN0x1(N0, TYPE, a, b, C) \ ({ \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a), b, (C##0)); \ }) #define ARM_VVM_T_NT_2xN0x1(N0, TYPE, a, b, C) \ ({ \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s0), b, (C##0)); \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s1), b, (C##1)); \ }) #define ARM_VVM_T_NT_3xN0x1(N0, TYPE, a, b, C) \ ({ \ ARM_VVM_T_NT_2xN0x1(N0, TYPE, a, b, C); \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s2), b, (C##2)); \ }) #define ARM_VVM_T_NT_4xN0x1(N0, TYPE, a, b, C) \ ({ \ ARM_VVM_T_NT_3xN0x1(N0, TYPE, a, b, C); \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s3), b, (C##3)); \ }) #define ARM_VVM_T_NT_8xN0x1(N0, TYPE, a, b, C) \ ({ \ ARM_VVM_T_NT_4xN0x1(N0, TYPE, a, b, C); \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s4), b, (C##4)); \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s5), b, (C##5)); \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s6), b, (C##6)); \ ARM_VFMA(N0, (VTYPE(TYPE, N0))(a.s7), b, (C##7)); \ }) // Factory macro for the column-vector (transposed) by row-vector (not transposed) multiplication. K0 = 1 // a is the column-vector (transposed) // b is the row-vector (not transposed) // C is the output matrix // Lower case is a vector (a, b) // Upper case is a matrix (C) #define ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, a, b, C) ARM_VVM_T_NT_##M0##xN0x1(N0, TYPE, a, b, C) #define ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, A, B, C) \ ({ \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##0), (B##0), C); \ }) #define ARM_MM_T_NT_M0xN0x2(M0, N0, TYPE, A, B, C) \ ({ \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, A, B, C); \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##1), (B##1), C); \ }) #define ARM_MM_T_NT_M0xN0x3(M0, N0, TYPE, A, B, C) \ ({ \ ARM_MM_T_NT_M0xN0x2(M0, N0, TYPE, A, B, C); \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##2), (B##2), C); \ }) #define ARM_MM_T_NT_M0xN0x4(M0, N0, TYPE, A, B, C) \ ({ \ ARM_MM_T_NT_M0xN0x3(M0, N0, TYPE, A, B, C); \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##3), (B##3), C); \ }) #define ARM_MM_T_NT_M0xN0x8(M0, N0, TYPE, A, B, C) \ ({ \ ARM_MM_T_NT_M0xN0x4(M0, N0, TYPE, A, B, C); \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##4), (B##4), C); \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##5), (B##5), C); \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##6), (B##6), C); \ ARM_VVM_T_NT_M0xN0x1(M0, N0, TYPE, (A##7), (B##7), C); \ }) #define ARM_MM_T_NT_M0xN0x16(M0, N0, TYPE, A, B, C) \ ({ \ ARM_MM_T_NT_M0xN0x8(M0, N0, TYPE, A, B, C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##8), (B##8), C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##9), (B##9), C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##A), (B##A), C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##B), (B##B), C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##C), (B##C), C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##D), (B##D), C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##E), (B##E), C); \ ARM_MM_T_NT_M0xN0x1(M0, N0, TYPE, (A##F), (B##F), C); \ }) // Factory macro for the matrix (transposed) by matrix (not transposed) multiplication. // The dimensions for this matrix multiplications are defined through M0, N0 and K0 // The dimensions supported are: // M0: 1, 2, 3, 4, 8 // N0: 1, 2, 3, 4, 8, 16 // K0: 1, 2, 3, 4, 8, 16 // This macro calls the vector-by-matrix macro K0 times // A, B and C are matrices #define ARM_MM_T_NT(M0, N0, K0, TYPE, A, B, C) \ CONCAT(ARM_MM_T_NT_M0xN0x, K0) \ (M0, N0, TYPE, A, B, C) #if defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. * The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be transposed * The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be NOT transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl * * @note LHS_TRANSPOSE should be passed at compile time in order to compile this OpenCL kernel (e.g. -DLHS_TRANSPOSE). * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions M, N and K must be passed at compile time using -DM, -DN and -DK (e.g. -DM=52, -DN=90 and -DK=24). * @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4). * @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2) * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time. * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 2, 3, 4, 8 * - N0 = 2, 3, 4, 8, 16 * - K0 = 2, 3, 4, 8, 16 * - V0 >= 1 * - H0 >= 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 * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time: * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped * * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F16/F32 * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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_lhs_t_rhs_nt(IMAGE_DECLARATION(lhs), IMAGE_DECLARATION(rhs), #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Block size #define LHS_BLOCK_SIZE ((K0) * (M0)) #if defined(LHS_INTERLEAVE) #define LHS_OFFSET_X (M0) #define LHS_STEP_X ((M0) * (V0)) #define LHS_STEP_LOOP (1) #else // defined(INTERLEAVE) #define LHS_OFFSET_X (LHS_BLOCK_SIZE) #define LHS_STEP_X (M0) #define LHS_STEP_LOOP (V0) #endif // defined(INTERLEAVE) // Block size #define RHS_BLOCK_SIZE ((K0) * (N0)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (N0) #define RHS_STEP_X ((N0) * (H0)) #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X (N0) #endif // defined(RHS_INTERLEAVE) const uint x = get_global_id(0); const uint y = get_global_id(1); const uint z = get_global_id(2); const bool cond_y = ((get_global_id(1) + 1) * M0 >= M); const bool cond_x = ((get_global_id(0) + 1) * N0 >= N); #if defined(DUMMY_WORK_ITEMS) if((x * N0 >= N) || (y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address __global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (y % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (y / V0) * (uint)lhs_stride_y + (z * lhs_stride_z); // Compute RHS matrix address __global uchar *rhs_addr = rhs_ptr + rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X * sizeof(DATA_TYPE) + (x / (uint)H0) * rhs_stride_y; #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 rhs_addr += (z % MATRIX_B_DEPTH) * rhs_stride_z; #else // defined(MATRIX_B_DEPTH) rhs_addr += z * rhs_stride_z; #endif // defined(MATRIX_B_DEPTH) // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0); REPEAT_VAR_INIT_TO_CONST(M0, uint, zero, 0); __global DATA_TYPE *lhs = (__global DATA_TYPE *)(lhs_addr); __global DATA_TYPE *rhs = (__global DATA_TYPE *)(rhs_addr); for(int i = 0; i < K; i += K0) { VEC_DATA_TYPE(DATA_TYPE, M0) a0; VEC_DATA_TYPE(DATA_TYPE, N0) b0; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; #if K0 > 1 a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; #endif // K0 > 1 #if K0 > 2 a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; #endif // K0 > 2 #if K0 > 3 a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; #endif // K0 > 3 #if K0 > 4 a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; #endif // K0 > 4 #if K0 > 8 a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = VLOAD(N0)(0, rhs); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; rhs += RHS_STEP_X; #endif // K0 > 8 #ifndef LHS_INTERLEAVE lhs += (M0 * K0 * (V0 - 1)); #endif // LHS_INTERLEAVE #ifndef RHS_INTERLEAVE rhs += (N0 * K0 * (H0 - 1)); #endif // RHS_INTERLEAVE } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (y * (uint)M0 * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, y * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += z * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += z * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] #if defined(MIXED_PRECISION) CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK_BROADCAST(M0, c, bias_hp0); #else // defined(MIXED_PRECISION) ADD_BLOCK_BROADCAST(M0, c, bias0); #endif // defined(MIXED_PRECISION) #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)) + (get_global_id(1) * (uint)M0 * bias_stride_y) + get_global_id( 2) * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK(M0, c, bias_hp); #else // defined(MIXED_PRECISION) ADD_BLOCK(M0, c, bias); #endif // defined(MIXED_PRECISION) #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) #if defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, N0, c, A_VAL, B_VAL); #else // defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(MIXED_PRECISION) #endif // defined(ACTIVATION_TYPE) // Store output block #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp); STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #else // defined(MIXED_PRECISION) STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #endif // defined(MIXED_PRECISION) #undef LHS_BLOCK_SIZE #undef LHS_OFFSET_X #undef LHS_STEP_X #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X } #endif // defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT) #if defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT_TEXTURE) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. The RHS matrix is stored in OpenCL image object. * The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be transposed * The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be NOT transposed * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_reshaped.cl * * @note -DOPENCL_IMAGE_SUPPORT must be passed at compile time in order to compile this OpenCL kernel * @note LHS_TRANSPOSE should be passed at compile time in order to compile this OpenCL kernel (e.g. -DLHS_TRANSPOSE). * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions M, N and K must be passed at runtime. * @note The height of the RHS matrix, defined before creating the OpenCL image object from the OpenCL buffer, should be passed at compile time using -DRHS_HEIGHT= (e.g. -DRHS_HEIGHT=32) * Since we cannot create a 3d image from a buffer, the third dimension could be collapsed with the second dimension so RHS_HEIGHT * could be different from the value returned by get_image_height(rhs_img). * @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4). * @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2) * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2) * @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time. * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 2, 3, 4, 8 * - N0 = 4, 8, 16 * - K0 = 4, 8, 16 * - V0 >= 1 * - H0 >= 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 * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time: * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped * * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: F32 * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix * @param[in] rhs_img The RHS reshaped matrix as cl_image 2d. Supported data type: same as @p lhs_ptr * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) * @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_lhs_t_rhs_nt_texture(IMAGE_DECLARATION(lhs), __read_only image2d_t rhs_img, #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D , const int M, const int N, const int K) { // Pixel unit #define PIXEL_UNIT CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(N0) // Block size #define LHS_BLOCK_SIZE ((K0) * (M0)) #if defined(LHS_INTERLEAVE) #define LHS_OFFSET_X (M0) #define LHS_STEP_X ((M0) * (V0)) #define LHS_STEP_LOOP (1) #else // defined(INTERLEAVE) #define LHS_OFFSET_X (LHS_BLOCK_SIZE) #define LHS_STEP_X (M0) #define LHS_STEP_LOOP (V0) #endif // defined(INTERLEAVE) // Block size #define RHS_BLOCK_SIZE ((K0) * (PIXEL_UNIT)) // RHS offset and step X #if defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (PIXEL_UNIT) #define RHS_STEP_X ((PIXEL_UNIT) * (H0)) #else // defined(RHS_INTERLEAVE) #define RHS_OFFSET_X (RHS_BLOCK_SIZE) #define RHS_STEP_X (PIXEL_UNIT) #endif // defined(RHS_INTERLEAVE) const uint x = get_global_id(0); const uint y = get_global_id(1); const uint z = get_global_id(2); #if defined(DUMMY_WORK_ITEMS) if((x * N0 >= N) || (y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address __global uchar *lhs_addr = lhs_ptr + lhs_offset_first_element_in_bytes + (y % V0) * (uint)LHS_OFFSET_X * sizeof(DATA_TYPE) + (y / V0) * (uint)lhs_stride_y + (z * lhs_stride_z); #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 const uint z_rhs = (z % MATRIX_B_DEPTH); #else // defined(MATRIX_B_DEPTH) const uint z_rhs = z; #endif // defined(MATRIX_B_DEPTH) // Compute RHS matrix coordinates uint x_rhs = (x % H0) * (uint)RHS_OFFSET_X; const uint y_rhs = (x / (uint)H0) + z_rhs * RHS_HEIGHT; // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE_ACCUMULATOR, N0), c, 0); REPEAT_VAR_INIT_TO_CONST(M0, uint, zero, 0); __global DATA_TYPE *lhs = (__global DATA_TYPE *)(lhs_addr); for(int i = 0; i < K; i += K0) { VEC_DATA_TYPE(DATA_TYPE, M0) a0; VEC_DATA_TYPE(DATA_TYPE, N0) b0; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 0 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; #if K0 > 1 a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 1 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; #endif // K0 > 1 #if K0 > 2 a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 2 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; #endif // K0 > 2 #if K0 > 3 a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 3 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; #endif // K0 > 3 #if K0 > 4 a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 4 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 5 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 6 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 7 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; #endif // K0 > 4 #if K0 > 8 a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 8 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 9 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 10 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 11 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 12 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 13 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 14 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; a0 = VLOAD(M0)(0, lhs); b0 = READ_IMAGE2D(DATA_TYPE, PIXEL_UNIT, rhs_img, (x_rhs + 15 * RHS_STEP_X), (y_rhs)); ARM_MM_T_NT(M0, N0, 1, DATA_TYPE, a, b, c); lhs += LHS_STEP_X; #endif // K0 > 8 #ifndef LHS_INTERLEAVE lhs += (M0 * K0 * (V0 - 1)); #endif // LHS_INTERLEAVE x_rhs += K0 * RHS_STEP_X; #ifndef RHS_INTERLEAVE x_rhs += (PIXEL_UNIT * K0 * (H0 - 1)); #endif // RHS_INTERLEAVE } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (y * (uint)M0 * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); const bool cond_y = ((get_global_id(1) + 1) * M0 >= M); const bool cond_x = ((get_global_id(0) + 1) * N0 >= N); #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zin) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, y * (uint)M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += z * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += z * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK_BOUNDARY_AWARE(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, 1, PARTIAL_STORE_N0, false, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] #if defined(MIXED_PRECISION) CONVERT_BLOCK(1, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK_BROADCAST(M0, c, bias_hp0); #else // defined(MIXED_PRECISION) ADD_BLOCK_BROADCAST(M0, c, bias0); #endif // defined(MIXED_PRECISION) #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (y * (uint)M0 * bias_stride_y) + z * bias_stride_z; LOAD_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE_ACCUMULATOR, bias, bias_hp); ADD_BLOCK(M0, c, bias_hp); #else // defined(MIXED_PRECISION) ADD_BLOCK(M0, c, bias); #endif // defined(MIXED_PRECISION) #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) #if defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE_ACCUMULATOR, N0, c, A_VAL, B_VAL); #else // defined(MIXED_PRECISION) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(MIXED_PRECISION) #endif // defined(ACTIVATION_TYPE) // Store output block #if defined(MIXED_PRECISION) CONVERT_BLOCK(M0, N0, DATA_TYPE, c, c_lp); STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #else // defined(MIXED_PRECISION) STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); #endif // defined(MIXED_PRECISION) #undef LHS_BLOCK_SIZE #undef LHS_OFFSET_X #undef LHS_STEP_X #undef RHS_BLOCK_SIZE #undef RHS_OFFSET_X #undef RHS_STEP_X #undef PIXEL_UNIT #undef LHS_STEP_LOOP #undef RHS_STEP_LOOP } #endif // defined(OPENCL_IMAGE_SUPPORT) && defined(GEMM_MM_RESHAPED_LHS_T_RHS_NT_TEXTURE) #endif // defined(LHS_TRANSPOSE) #endif // defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(DATA_TYPE) && defined(DATA_TYPE_ACCUMULATOR) #if defined(M0) && defined(N0) && defined(K0) && defined(DATA_TYPE) #define VFMA(a, b, c) \ ({ \ c = fma(a, b, c); \ }) #if M0 == 1 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ }) #elif M0 == 2 // M0 == 2 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ }) #elif M0 == 3 // M0 == 3 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ }) #elif M0 == 4 // M0 == 4 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ }) #elif M0 == 5 // M0 == 5 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ }) #elif M0 == 6 // M0 == 6 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ }) #elif M0 == 7 // M0 == 7 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \ }) #elif M0 == 8 // M0 == 8 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##7).s##i), b, (c##7)); \ }) #else // M0 not supported #error "M0 not supported" #endif // M0 not supported #if defined(GEMM_MM_NATIVE) /** This OpenCL kernel computes the matrix multiplication between 2 matrices. * The LHS matrix is NOT reshaped * The RHS matrix is NOT reshaped * @note This kernel is duplicated in /experimental/gemm_fused_post_ops/act_eltwise_op_act/gemm_mm_native.cl * * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. * @note The GEMM's dimensions (M,N and K) must be passed at runtime as kernel parameters. * @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2) * @note The number of K0 partial accumulations must be passed at compile time using -DK0 (e.g., -DK0=2) * @note The number of N0 columns to process must be passed at compile time using -DN0 (e.g. -DN0=2) * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1) * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 * - N0 = 2, 3, 4, 8, 16 * - K0 = 2, 3, 4, 8, 16 * * @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 * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix * * @param[in] lhs_ptr Pointer to the LHS matrix. Supported data type: F16/F32 * @param[in] lhs_stride_x Stride of the LHS matrix in X dimension (in bytes) * @param[in] lhs_step_x lhs_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] lhs_stride_y Stride of the LHS matrix in Y dimension (in bytes) * @param[in] lhs_step_y lhs_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS matrix * @param[in] rhs_ptr Pointer to the RHS matrix. Supported data type: same as @p lhs_ptr * @param[in] rhs_stride_x Stride of the RHS matrix in X dimension (in bytes) * @param[in] rhs_step_x rhs_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] rhs_stride_y Stride of the RHS matrix in Y dimension (in bytes) * @param[in] rhs_step_y rhs_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS matrix * @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr * @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes) * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes) * @param[in] bias_step_y (Optional) bias_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] lhs_stride_z Stride of the LHS matrix in Z dimension (in bytes) * @param[in] rhs_stride_z Stride of the RHS matrix in Z dimension (in bytes) * @param[in] bias_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @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. * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) */ __kernel void gemm_mm_native(IMAGE_DECLARATION(lhs), IMAGE_DECLARATION(rhs), #if defined(BETA) IMAGE_DECLARATION(bias), #endif // defined(BETA) IMAGE_DECLARATION(dst), uint lhs_stride_z, uint rhs_stride_z, #if defined(BETA) uint bias_stride_z, #endif //defined(BETA) uint dst_stride_z, const int M, const int N, const int K #if defined(REINTERPRET_INPUT_AS_3D) , uint lhs_cross_plane_pad #endif // REINTERPRET_INPUT_AS_3D #if defined(REINTERPRET_OUTPUT_AS_3D) , uint dst_cross_plane_pad #endif // REINTERPRET_OUTPUT_AS_3D ) { // Block size #define RHS_BLOCK_SIZE ((K0) * (N0)) // RHS offset and step X #define RHS_OFFSET_X (RHS_BLOCK_SIZE) uint x = get_global_id(0); uint y = get_global_id(1); uint z = get_global_id(2); #if defined(DUMMY_WORK_ITEMS) if((x * N0 >= N) || (y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; // Compute RHS matrix address uint rhs_offset = rhs_offset_first_element_in_bytes + x * N0 * sizeof(DATA_TYPE); #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z; #else // defined(MATRIX_B_DEPTH) rhs_offset += z * rhs_stride_z; #endif // defined(MATRIX_B_DEPTH) REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0); REPEAT_VAR_INIT_TO_CONST(16, uint, zero, 0); #if defined(REINTERPRET_INPUT_AS_3D) // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply lhs_stride_z by DEPTH_GEMM3D lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_INPUT_AS_3D) // Add offset for batched GEMM lhs_offset += z * lhs_stride_z; #endif // defined(REINTERPRET_INPUT_AS_3D) // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(M0-1)=0; int i = 0; #if K0 > 1 for(; i <= (K - K0); i += K0) { // Supported cases (M0, K0): // 1,2 - 1,3 - 1,4 - 1,8 - 1,16 // 2,2 - 2,3 - 2,4 - 2,8 - 2,16 // 3,2 - 3,3 - 3,4 - 3,8 - 3,16 // 4,2 - 4,3 - 4,4 - 4,8 - 4,16 // 5,2 - 5,3 - 5,4 - 5,8 - 5,16 // 6,2 - 6,3 - 6,4 - 6,8 - 6,16 // 7,2 - 7,3 - 7,4 - 7,8 - 7,16 // 8,2 - 8,3 - 8,4 - 8,8 - 8,16 // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); // Load values from RHS matrix LOAD_BLOCK(K0, N0, DATA_TYPE, b, rhs_ptr, rhs_offset, rhs_stride_y, zero); RHS_VFMA_M0xN0(0, a, b0, c); RHS_VFMA_M0xN0(1, a, b1, c); #if K0 > 2 RHS_VFMA_M0xN0(2, a, b2, c); #endif // K0 > 2 #if K0 > 3 RHS_VFMA_M0xN0(3, a, b3, c); #endif // K0 > 3 #if K0 > 4 RHS_VFMA_M0xN0(4, a, b4, c); RHS_VFMA_M0xN0(5, a, b5, c); RHS_VFMA_M0xN0(6, a, b6, c); RHS_VFMA_M0xN0(7, a, b7, c); #endif // K0 > 4 #if K0 > 8 RHS_VFMA_M0xN0(8, a, b8, c); RHS_VFMA_M0xN0(9, a, b9, c); RHS_VFMA_M0xN0(A, a, bA, c); RHS_VFMA_M0xN0(B, a, bB, c); RHS_VFMA_M0xN0(C, a, bC, c); RHS_VFMA_M0xN0(D, a, bD, c); RHS_VFMA_M0xN0(E, a, bE, c); RHS_VFMA_M0xN0(F, a, bF, c); #endif // K0 > 8 lhs_offset += K0 * sizeof(DATA_TYPE); rhs_offset += K0 * rhs_stride_y; } #endif // K0 > 1 // Left-over accumulations for(; i < K; ++i) { // Load values from LHS matrix VEC_DATA_TYPE(DATA_TYPE, 2) a0 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 0 * lhs_stride_y + zlhs0)); #if M0 > 1 VEC_DATA_TYPE(DATA_TYPE, 2) a1 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 1 * lhs_stride_y + zlhs1)); #endif // M0 > 1 #if M0 > 2 VEC_DATA_TYPE(DATA_TYPE, 2) a2 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 2 * lhs_stride_y + zlhs2)); #endif // M0 > 2 #if M0 > 3 VEC_DATA_TYPE(DATA_TYPE, 2) a3 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 3 * lhs_stride_y + zlhs3)); #endif // M0 > 3 #if M0 > 4 VEC_DATA_TYPE(DATA_TYPE, 2) a4 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 4 * lhs_stride_y + zlhs4)); #endif // M0 > 4 #if M0 > 5 VEC_DATA_TYPE(DATA_TYPE, 2) a5 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 5 * lhs_stride_y + zlhs5)); #endif // M0 > 5 #if M0 > 6 VEC_DATA_TYPE(DATA_TYPE, 2) a6 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 6 * lhs_stride_y + zlhs6)); #endif // M0 > 6 #if M0 > 7 VEC_DATA_TYPE(DATA_TYPE, 2) a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zlhs7)); #endif // M0 > 7 VEC_DATA_TYPE(DATA_TYPE, N0) b = VLOAD(N0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset + 0 * rhs_stride_y)); RHS_VFMA_M0xN0(0, a, b, c); lhs_offset += sizeof(DATA_TYPE); rhs_offset += rhs_stride_y; } __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); #if defined(REINTERPRET_OUTPUT_AS_3D) // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply dst_stride_z by DEPTH_GEMM3D dst_addr += z * dst_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_OUTPUT_AS_3D) // Add offset for batched GEMM dst_addr += z * dst_stride_z; #endif // defined(REINTERPRET_OUTPUT_AS_3D) // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, c, ALPHA); #endif // defined(ALPHA) // Add beta*bias #if defined(BETA) #if defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK(1, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] ADD_BLOCK_BROADCAST(M0, c, bias0); #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = bias_ptr + bias_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * bias_stride_y) + z * bias_stride_z; LOAD_BLOCK(M0, N0, DATA_TYPE, bias, bias_addr, 0, bias_stride_y, zero); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias ADD_BLOCK(M0, c, bias); #endif // defined(BROADCAST_BIAS) #endif // defined(BETA) #if defined(ACTIVATION_TYPE) ACTIVATION_BLOCK(M0, ACTIVATION_TYPE, DATA_TYPE, N0, c, A_VAL, B_VAL); #endif // defined(ACTIVATION_TYPE) const bool cond_y = y == 0; const bool cond_x = ((x + 1) * N0 >= N); // Store output block STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); } #endif // defined(GEMM_MM_NATIVE) #endif // defined(M0) && defined(N0) && defined(K0) && defined(DATA_TYPE) #if defined(BETA) /** This OpenCL kernel performs the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta: * * @note The beta's value need to be passed at compile time using -DBETA * * @param[in] src_ptr Pointer to the source matrix. Supported data types: F32 * @param[in] src_stride_x Stride of the source matrix in X dimension (in bytes) * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] src_stride_y Stride of the source matrix in Y dimension (in bytes) * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] src_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] src_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_ma_f32(TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst)) { // Compute source and destination addresses Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); // Load values from A x B float4 alpha_ab = vload4(0, (__global float *)dst.ptr); // Load values from Matrix C float4 c = vload4(0, (__global float *)src.ptr); // Computes alpha * axb + beta * c float4 out = alpha_ab + (float4)BETA * c; // Store final result in axb matrix vstore4(out, 0, (__global float *)dst.ptr); } #if defined(ARM_COMPUTE_OPENCL_FP16_ENABLED) /** This OpenCL kernel performs the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta: * * @note The beta's value need to be passed at compile time using -DBETA * * @param[in] src_ptr Pointer to the source matrix. Supported data types: F16 * @param[in] src_stride_x Stride of the source matrix in X dimension (in bytes) * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] src_stride_y Stride of the source matrix in Y dimension (in bytes) * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] src_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] src_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source matrix * @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src_ptr * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) * @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_ma_f16(TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst)) { // Compute source and destination addresses Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); // Load values from A x B half8 alpha_ab = vload8(0, (__global half *)dst.ptr); // Load values from Matrix C half8 c = vload8(0, (__global half *)src.ptr); // Computes alpha * axb + beta * c half8 out = alpha_ab + (half8)BETA * c; // Store final result in axb matrix vstore8(out, 0, (__global half *)dst.ptr); } #endif // defined(ARM_COMPUTE_OPENCL_FP16_ENABLED) #endif // defined(BETA)