diff options
author | giuros01 <giuseppe.rossini@arm.com> | 2019-04-01 13:50:22 +0100 |
---|---|---|
committer | Giuseppe Rossini <giuseppe.rossini@arm.com> | 2019-05-17 12:12:11 +0000 |
commit | b3204e76712b8f66218affdd4ad44ec221c6dcb6 (patch) | |
tree | dfcc2ceed5e557305489967aa4fdbea557b7d19c /src/core/CL | |
parent | 3113a27930b8661e869bc59deff6edcf43cf2cd3 (diff) | |
download | ComputeLibrary-b3204e76712b8f66218affdd4ad44ec221c6dcb6.tar.gz |
COMPMID-2093: Implement CLGEMMNative
Change-Id: I347130f6b5ae8d08b7c5c101b523b158565874a1
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1114
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/CL')
-rw-r--r-- | src/core/CL/CLKernelLibrary.cpp | 1 | ||||
-rw-r--r-- | src/core/CL/cl_kernels/gemm.cl | 319 | ||||
-rw-r--r-- | src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp | 321 |
3 files changed, 640 insertions, 1 deletions
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index e102f44b88..dfcbfa7cc5 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -314,6 +314,7 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map = { "gemm_mm_floating_point_f16_bifrost_acc32", "gemm.cl" }, { "gemm_mm_floating_point_f32_bifrost", "gemm.cl" }, { "gemm_mm_floating_point_f32_bifrost_1000", "gemm.cl" }, + { "gemm_mm_native", "gemm.cl" }, { "gemm_mm_reshaped_lhs_nt_rhs_t", "gemm.cl" }, { "gemm_mm_reshaped_only_rhs_nt", "gemm.cl" }, { "gemm_mm_reshaped_only_rhs_t", "gemm.cl" }, diff --git a/src/core/CL/cl_kernels/gemm.cl b/src/core/CL/cl_kernels/gemm.cl index c3107a20f2..da45d0fc18 100644 --- a/src/core/CL/cl_kernels/gemm.cl +++ b/src/core/CL/cl_kernels/gemm.cl @@ -1535,7 +1535,7 @@ __kernel void gemm_mm_reshaped_only_rhs_nt(IMAGE_DECLARATION(lhs), #endif // M0 > 6 #if M0 > 7 VEC_DATA_TYPE(DATA_TYPE, 2) - a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zin)); + a7 = *((__global DATA_TYPE *)(lhs_ptr + lhs_offset + 7 * lhs_stride_y + zin7)); #endif // M0 > 7 LD_RHS_VFMA_M0xN0(0, a, c); @@ -1886,8 +1886,325 @@ __kernel void gemm_mm_reshaped_lhs_nt_rhs_t(IMAGE_DECLARATION(lhs), #undef RHS_OFFSET_X #undef RHS_STEP_X } + #endif // defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(K) && defined(DATA_TYPE) +#if defined(M0) && defined(N0) && defined(K0) && defined(K) && 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 + +/** This OpenCL kernel computes the matrix multiplication between 2 matrices. + * The LHS matrix is NOT reshaped + * The RHS matrix is NOT reshaped + * + * @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 and -DK (i.e. -DM=52, -DN=30 and -DK=90) + * @note The number of columns of LHS matrix must be passed at compile time using -DK (i.e. -DK=64) + * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2) + * @note The number of K0 partial accumulations must be passed at compile time using -DK0 (i.e., -DK0=2) + * @note The number of N0 columns to process must be passed at compile time using -DN0 (i.e. -DN0=2) + * @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 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 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[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] 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) + */ +__kernel void gemm_mm_native(IMAGE_DECLARATION(lhs), + IMAGE_DECLARATION(rhs), + IMAGE_DECLARATION(dst), + uint lhs_stride_z, + uint rhs_stride_z, + 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 + ) +{ + // 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 + y * 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(8, uint, zlhs, 0); //uint zlhs0=0,zlhs1=0,zlhs2=0,... zlhs7=0; + REPEAT_VAR_INIT_TO_CONST(16, uint, zrhs, 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, y, 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, zlhs); + + // Load values from RHS matrix + LOAD_BLOCK(K0, N0, DATA_TYPE, b, rhs_ptr, rhs_offset, rhs_stride_y, zrhs); + + 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, b10, c); + RHS_VFMA_M0xN0(B, a, b11, c); + RHS_VFMA_M0xN0(C, a, b12, c); + RHS_VFMA_M0xN0(D, a, b13, c); + RHS_VFMA_M0xN0(E, a, b14, c); + RHS_VFMA_M0xN0(F, a, b15, c); +#endif // K0 > 8 + + lhs_offset += K0 * sizeof(DATA_TYPE); + rhs_offset += K0 * rhs_stride_y; + } + + // 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)) + (y * (uint)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, y, 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 + // 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) + + // Store output block + STORE_BLOCK(M0, N0, DATA_TYPE, c, dst_addr, dst_stride_y, zout); + +#undef RHS_BLOCK_SIZE +#undef RHS_OFFSET_X +#undef RHS_STEP_X +} +#endif // defined(M0) && defined(N0) && defined(K0) && defined(K) && defined(DATA_TYPE) + #if defined(TRANSPOSE_W) && defined(MULT_TRANSPOSE1XW_WIDTH) #if ELEMENT_SIZE == 1 diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp new file mode 100644 index 0000000000..85d882c865 --- /dev/null +++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp @@ -0,0 +1,321 @@ +/* + * Copyright (c) 2019 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 "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "support/ToolchainSupport.h" + +#include <cstddef> +#include <cstdint> +#include <tuple> + +using namespace arm_compute::misc::shape_calculator; + +namespace arm_compute +{ +namespace +{ +using ElementsProcessed = Steps; + +Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, + const GEMMReshapeInfo &gemm_info) +{ + ARM_COMPUTE_UNUSED(alpha); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input0, input1, output); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F32, DataType::F16); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input0->num_dimensions() > 4, "The number of dimensions for the LHS matrix must be <= 4"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the RHS matrix must be <= 3"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(((rhs_info.k0 & (rhs_info.k0 - 1)) && rhs_info.k0 != 3), "Only 2,3,4,8,16 are supported for k0"); + ARM_COMPUTE_RETURN_ERROR_ON(rhs_info.k0 > 16); + ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.m0 < 1 || lhs_info.m0 > 8); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(((rhs_info.n0 & (rhs_info.n0 - 1)) && rhs_info.n0 != 3), "Only 2,3,4,8,16 are supported for n0"); + + const int m = gemm_info.m(); + const int n = gemm_info.n(); + const int k = gemm_info.k(); + + ARM_COMPUTE_UNUSED(m); + ARM_COMPUTE_UNUSED(n); + ARM_COMPUTE_UNUSED(k); + + ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != static_cast<unsigned int>(k)); + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) != static_cast<unsigned int>(n)); + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(1) != static_cast<unsigned int>(k)); + if(gemm_info.reinterpret_input_as_3d()) + { + ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) * input0->dimension(2) != static_cast<unsigned int>(m)); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) != static_cast<unsigned int>(m)); + } + + if(output->total_size() != 0) + { + const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output); + } + + return Status{}; +} + +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, + const GEMMReshapeInfo &gemm_info, ElementsProcessed &num_elements_processed) +{ + unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0]; + unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1]; + bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d(); + bool reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 0); + + Window win{}; + Window win_out{}; + bool window_changed = false; + + // In case both input and output have to be reinterpreted as 3D tensors, + // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false. + if(reinterpret_input_as_3d == reinterpret_output_as_3d) + { + reinterpret_output_as_3d = false; + } + + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info))); + + TensorInfo tmp_info(*output); + + if(reinterpret_output_as_3d) + { + // Since the output tensor has to be reinterpreted as 3D and the execute window is based on a 2D GEMM, + // the window needs to be constructed on the 2D collapsed version of the tensor + TensorShape tmp_shape(output->tensor_shape()); + tmp_shape.collapse(2U, 1U); + tmp_info.set_tensor_shape(tmp_shape); + } + + // Configure kernel window + num_elems_processed_per_iteration_x = rhs_info.n0; + num_elems_processed_per_iteration_y = lhs_info.m0; + + // Note: bottom paddings are calculated manually as the output can be reinterpreted as 3D tensor + // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic + const int m = gemm_info.m(); + const int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y; + + win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + + AccessWindowStatic input0_access(input0, 0, 0, + input0->dimension(0), + input0->dimension(1) + bottom_pad); + AccessWindowStatic input1_access(input1, 0, 0, + ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), + input1->dimension(1)); + AccessWindowStatic output_access(output, 0, 0, + ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x), + output->dimension(1) + bottom_pad); + + window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop + update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor + + output_access.set_valid_region(win_out, ValidRegion(Coordinates(), output->tensor_shape())); + + // Collapse along the Z direction + // This collapse needs to be here in order to tune the Z dimension of LWS + Window collapsed = win; + const unsigned int dimension_to_collapse = std::min(static_cast<unsigned int>(output->num_dimensions()), 2u); + collapsed = win.collapse(win, dimension_to_collapse); + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, collapsed); +} +} // namespace + +CLGEMMMatrixMultiplyNativeKernel::CLGEMMMatrixMultiplyNativeKernel() + : _input0(nullptr), _input1(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_input_as_3d(false), _reinterpret_output_as_3d(false), _use_dummy_work_items(false) +{ +} + +void CLGEMMMatrixMultiplyNativeKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, const GEMMLHSMatrixInfo &lhs_info, + const GEMMRHSMatrixInfo &rhs_info, const GEMMReshapeInfo &gemm_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output); + + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), alpha, lhs_info, rhs_info, gemm_info)); + + _input0 = input0; + _input1 = input1; + _output = output; + _reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d(); + _reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 0); + _use_dummy_work_items = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device()); + + // In case both input and output have to be reinterpreted as 3D tensors, + // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false. + if(_reinterpret_input_as_3d == _reinterpret_output_as_3d) + { + _reinterpret_input_as_3d = false; + _reinterpret_output_as_3d = false; + } + + // Check if we need to slide the matrix B + const unsigned int num_dimensions_input0 = _input0->info()->num_dimensions(); + _slide_matrix_b = (_input1->info()->num_dimensions() >= num_dimensions_input0); + + ElementsProcessed num_elements_processed{}; + + // Configure kernel window + auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info(), lhs_info, rhs_info, gemm_info, num_elements_processed); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure_internal(win_config.second); + + // Create build options + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type())); + build_opts.add_option_if(std::abs(1.0f - alpha) > 0.00001f, "-DALPHA=" + float_to_string_with_full_precision(alpha)); + build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D"); + build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D"); + build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1))); + build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(2))); + build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2))); + build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS"); + build_opts.add_option("-DM=" + support::cpp11::to_string(input0->info()->dimension(1))); + build_opts.add_option("-DN=" + support::cpp11::to_string(gemm_info.n())); + build_opts.add_option("-DK=" + support::cpp11::to_string(gemm_info.k())); + build_opts.add_option("-DM0=" + support::cpp11::to_string(lhs_info.m0)); + build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0)); + build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0)); + + std::string kernel_name("gemm_mm_native"); + + // Create kernel + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); + + // Set config_id for enabling LWS tuning + _config_id = kernel_name; + _config_id += "_"; + _config_id += (_reinterpret_input_as_3d ? "3di_" : ""); + _config_id += (_reinterpret_output_as_3d ? "3do_" : ""); + _config_id += lower_string(string_from_data_type(input0->info()->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(output->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(output->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(gemm_info.k()); + _config_id += "_"; + _config_id += support::cpp11::to_string(output->info()->dimension(2)); + _config_id += "_"; + _config_id += support::cpp11::to_string(lhs_info.m0); + _config_id += "_"; + _config_id += support::cpp11::to_string(rhs_info.n0); + _config_id += "_"; + _config_id += support::cpp11::to_string(rhs_info.k0); +} + +Status CLGEMMMatrixMultiplyNativeKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, const GEMMLHSMatrixInfo &lhs_info, + const GEMMRHSMatrixInfo &rhs_info, const GEMMReshapeInfo &gemm_info) +{ + ElementsProcessed num_elements_processed{}; + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, alpha, lhs_info, rhs_info, gemm_info)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(), + input1->clone().get(), + output->clone().get(), + lhs_info, + rhs_info, + gemm_info, + num_elements_processed) + .first); + + return Status{}; +} + +void CLGEMMMatrixMultiplyNativeKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + if(_input1->info()->num_dimensions() < 3) + { + // The stride_z for matrix B must be zero if we do not slice + ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0); + } + + Window slice = window.first_slice_window_3D(); + Window slice_matrix_b = slice; + + slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1)); + slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1)); + + if(_reinterpret_input_as_3d) + { + // Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor + const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3; + const unsigned int total_cross_plane_pad = _input0->info()->padding().top + _input0->info()->padding().bottom; + _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad)); + } + + if(_reinterpret_output_as_3d) + { + // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor + const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3 + (_reinterpret_input_as_3d ? 1 : 0); + const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom; + _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad)); + } + + do + { + Window slice_b = slice; + // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2 + // This scenario can happen when the matrix multiplication is used to perform a convolution operation + if(!_slide_matrix_b) + { + slice_b = slice_matrix_b; + } + + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input0, slice); + add_2D_tensor_argument(idx, _input1, slice_b); + add_2D_tensor_argument(idx, _output, slice); + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2])); + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2])); + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2])); + enqueue(queue, *this, slice, lws_hint(), _use_dummy_work_items); + } + while(window.slide_window_slice_3D(slice)); +} +} // namespace arm_compute |