From 73cdaac61d3121d4d6556846de259dd734afdccf Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Mon, 10 Aug 2020 21:44:14 +0100 Subject: COMPMID-3335: Remove x/y-axis padding from CLGEMMReshapeLHSMatrixKernel - Remove padding requirement for the input tensor of CLGEMMReshapeLHSMatrixKernel - Add utility function to load a boundary aware 2d tensor from buffer - Extend validation for validating the zero padding requirement Change-Id: I0ac6b1b517d75fd56998f406e0cce97b40918ce1 Signed-off-by: Gian Marco Iodice Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3701 Comments-Addressed: Arm Jenkins Reviewed-by: SiCong Li Tested-by: Arm Jenkins --- src/core/CL/cl_kernels/gemm_helpers.h | 260 +++++++++++++++++++++++++++++++++- 1 file changed, 259 insertions(+), 1 deletion(-) (limited to 'src/core/CL/cl_kernels/gemm_helpers.h') diff --git a/src/core/CL/cl_kernels/gemm_helpers.h b/src/core/CL/cl_kernels/gemm_helpers.h index 5b6ad17ce0..fada0302ff 100644 --- a/src/core/CL/cl_kernels/gemm_helpers.h +++ b/src/core/CL/cl_kernels/gemm_helpers.h @@ -24,10 +24,268 @@ #include "activation_float_helpers.h" #include "helpers.h" +/** Utility macro to access a vector with the scalar positions + * + * Supported cases are: Offset can only be of the same size of the OpenCL vector (2,3,4,8,16) + * + * @param[in] offset The offset within the vector. Offset can only be of the same size of the OpenCL vector (2,3,4,8,16) + * @param[in] n0 The number of consecutive columns to access. n0 + offset must be <= 16 + * @param[in] x Vector to access + * @{ + */ +#define SCALAR_ACCESS_STR(offset, n0, x) scalar_access_##offset##_##n0(x) +#define SCALAR_ACCESS(offset, n0, x) SCALAR_ACCESS_STR(offset, n0, x) + +// offset == 0 +#define scalar_access_0_1(x) ((x).s0) +#define scalar_access_0_2(x) ((x).s01) +#define scalar_access_0_3(x) ((x).s012) +#define scalar_access_0_4(x) ((x).s0123) +#define scalar_access_0_8(x) ((x).s01234567) +#define scalar_access_0_16(x) ((x).s0123456789ABCDEF) + +// offset == 1 +#define scalar_access_1_1(x) ((x).s1) +#define scalar_access_1_2(x) ((x).s12) +#define scalar_access_1_3(x) ((x).s123) +#define scalar_access_1_4(x) ((x).s1234) +#define scalar_access_1_8(x) ((x).s12345678) + +// offset == 2 +#define scalar_access_2_1(x) ((x).s2) +#define scalar_access_2_2(x) ((x).s23) +#define scalar_access_2_3(x) ((x).s234) +#define scalar_access_2_4(x) ((x).s2345) +#define scalar_access_2_8(x) ((x).s23456789) + +// offset == 3 +#define scalar_access_3_1(x) ((x).s3) +#define scalar_access_3_2(x) ((x).s34) +#define scalar_access_3_3(x) ((x).s345) +#define scalar_access_3_4(x) ((x).s3456) +#define scalar_access_3_8(x) ((x).s3456789A) + +// offset == 4 +#define scalar_access_4_1(x) ((x).s4) +#define scalar_access_4_2(x) ((x).s45) +#define scalar_access_4_3(x) ((x).s456) +#define scalar_access_4_4(x) ((x).s4567) +#define scalar_access_4_8(x) ((x).s456789AB) + +// offset == 8 +#define scalar_access_8_1(x) ((x).s8) +#define scalar_access_8_2(x) ((x).s89) +#define scalar_access_8_3(x) ((x).s89A) +#define scalar_access_8_4(x) ((x).s89AB) +#define scalar_access_8_8(x) ((x).s89ABCDEF) + +// offset == 12 +#define scalar_access_12_1(x) ((x).sC) +#define scalar_access_12_2(x) ((x).sCD) +#define scalar_access_12_3(x) ((x).sCDE) +#define scalar_access_12_4(x) ((x).sCDEF) + +// offset == 16 +#define scalar_access_16_1(x) ((x).sF) + +/** Loads the rows from 0 to n-1 in the given variables (BASENAME0 to BASENAMEn-1) without allocating variables. + * @name LOAD_TENSOR_ROW_n + * + * @param[in] N0 The number of columns to load + * @param[in] DATA_TYPE The data type of variables + * @param[in] BASENAME The basename of the destination variables for the loaded rows + * @param[in] PTR The base pointer + * @param[in] COL_OFFSET The column vector offset. COL_OFFSET + N0 must be <= 16 + * @param[in] STRIDE_Y The stride value in y-axis direction + * @param[in] Z The z-axis offset vector + * @{ + */ +#define LOAD_TENSOR_ROW_0(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + ({}) + +#define LOAD_TENSOR_ROW_1(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##0) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 0 * STRIDE_Y + Z##0)); + +#define LOAD_TENSOR_ROW_2(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_1(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##1) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 1 * STRIDE_Y + Z##1)); + +#define LOAD_TENSOR_ROW_3(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_2(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##2) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 2 * STRIDE_Y + Z##2)); + +#define LOAD_TENSOR_ROW_4(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_3(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##3) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 3 * STRIDE_Y + Z##3)); + +#define LOAD_TENSOR_ROW_5(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_4(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##4) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 4 * STRIDE_Y + Z##4)); + +#define LOAD_TENSOR_ROW_6(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_5(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##5) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 5 * STRIDE_Y + Z##5)); + +#define LOAD_TENSOR_ROW_7(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_6(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##6) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 6 * STRIDE_Y + Z##6)); + +#define LOAD_TENSOR_ROW_8(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_7(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##7) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 7 * STRIDE_Y + Z##7)); + +#define LOAD_TENSOR_ROW_9(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_8(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##8) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 8 * STRIDE_Y + Z##8)); + +#define LOAD_TENSOR_ROW_10(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_9(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##9) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 9 * STRIDE_Y + Z##9)); + +#define LOAD_TENSOR_ROW_11(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_10(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##A) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 10 * STRIDE_Y + Z##A)); + +#define LOAD_TENSOR_ROW_12(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_11(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##B) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 11 * STRIDE_Y + Z##B)); + +#define LOAD_TENSOR_ROW_13(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_12(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##C) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 12 * STRIDE_Y + Z##C)); + +#define LOAD_TENSOR_ROW_14(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_13(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##D) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 13 * STRIDE_Y + Z##D)); + +#define LOAD_TENSOR_ROW_15(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_14(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##E) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 14 * STRIDE_Y + Z##E)); + +#define LOAD_TENSOR_ROW_16(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + LOAD_TENSOR_ROW_15(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) \ + SCALAR_ACCESS(COL_OFFSET, N0, BASENAME##F) = VLOAD(N0)(0, (__global DATA_TYPE *)(PTR + 15 * STRIDE_Y + Z##F)); +/** @}*/ // end of group LOAD_TENSOR_ROW_n + +/** Load tensor (consecutive rows and columns) with Z offset. + * @name LOAD_TENSOR + * + * Supported cases are M0=1,2,3,...,16 and N0=1,2,3,4,8,16 + * The data to load is expected to have consecutive names for each row. + * E.g., for M0=3, and BASENAME=c, the expected data is c0, c1 and c2. + * The Z offset is expected to have consecutive names. + * E.g., for M0=3, and Z=zin, the expected Z offsets are zin0, zin1 and zin2. + * + * @param[in] M0 The number of consecutive rows + * @param[in] N0 The number of consecutive columns + * @param[in] DATA_TYPE The data type of the target + * @param[in] BASENAME The basename of the result variables + * @param[in] PTR The base pointer for the data + * @param[in] COL_OFFSET The column vector offset. COL_OFFSET + N0 must be <= 16 + * @param[in] STRIDE_Y The stride in y-axis direction + * @param[in] Z The z-axis offset vector + * @{ + */ +#define LOAD_TENSOR_STR(M0, N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) LOAD_TENSOR_ROW_##M0(N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) +#define LOAD_TENSOR(M0, N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) LOAD_TENSOR_STR(M0, N0, DATA_TYPE, BASENAME, PTR, COL_OFFSET, STRIDE_Y, Z) +/** @} */ // end of group LOAD_TENSOR + +/** Load 2D tensor (consecutive rows and columns) with Z offset. + * @name LOAD_TENSOR_M0Xn + * + * @param[in] M0 The number of rows to load [0-16] + * @param[in] N0 The number of columns to load [0-16] + * @param[in] DATA_TYPE The data type of variables + * @param[in] BASENAME The basename of the destination variables for the loaded rows + * @param[in] PTR The base pointer + * @param[in] STRIDE_Y The stride value in y-axis direction + * @param[in] Z The z-axis offset vector + * @{ + */ +#define LOAD_TENSOR_M0X0(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + ({}) + +#define LOAD_TENSOR_M0X1(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, N0, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); + +#define LOAD_TENSOR_M0X2(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, N0, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); + +#define LOAD_TENSOR_M0X3(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, N0, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); + +#define LOAD_TENSOR_M0X4(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, N0, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); + +#define LOAD_TENSOR_M0X5(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 4, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 1, DATA_TYPE, a, input_ptr + 4 * sizeof(DATA_TYPE), 4, src_stride_y, zin); + +#define LOAD_TENSOR_M0X6(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 4, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 2, DATA_TYPE, a, input_ptr + 4 * sizeof(DATA_TYPE), 4, src_stride_y, zin); + +#define LOAD_TENSOR_M0X7(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 4, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 3, DATA_TYPE, a, input_ptr + 4 * sizeof(DATA_TYPE), 4, src_stride_y, zin); + +#define LOAD_TENSOR_M0X8(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, N0, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); + +#define LOAD_TENSOR_M0X9(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 8, DATA_TYPE, a, input_ptr 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 1, DATA_TYPE, a, input_ptr + 8 * sizeof(DATA_TYPE), 8, src_stride_y, zin); + +#define LOAD_TENSOR_M0X10(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 8, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 2, DATA_TYPE, a, input_ptr + 8 * sizeof(DATA_TYPE), 8, src_stride_y, zin); + +#define LOAD_TENSOR_M0X11(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 8, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 3, DATA_TYPE, a, input_ptr + 8 * sizeof(DATA_TYPE), 8, src_stride_y, zin); + +#define LOAD_TENSOR_M0X12(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 8, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 4, DATA_TYPE, a, input_ptr + 8 * sizeof(DATA_TYPE), 8, src_stride_y, zin); + +#define LOAD_TENSOR_M0X13(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 8, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 4, DATA_TYPE, a, input_ptr + 8 * sizeof(DATA_TYPE), 8, src_stride_y, zin); \ + LOAD_TENSOR(M0, 1, DATA_TYPE, a, input_ptr + 12 * sizeof(DATA_TYPE), 12, src_stride_y, zin); + +#define LOAD_TENSOR_M0X14(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 8, DATA_TYPE, a, input_ptr 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 4, DATA_TYPE, a, input_ptr + 8 * sizeof(DATA_TYPE), 8, src_stride_y, zin); \ + LOAD_TENSOR(M0, 2, DATA_TYPE, a, input_ptr + 12 * sizeof(DATA_TYPE), 12, src_stride_y, zin); + +#define LOAD_TENSOR_M0X15(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, 8, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); \ + LOAD_TENSOR(M0, 4, DATA_TYPE, a, input_ptr + 8 * sizeof(DATA_TYPE), 8, src_stride_y, zin); \ + LOAD_TENSOR(M0, 3, DATA_TYPE, a, input_ptr + 12 * sizeof(DATA_TYPE), 12, src_stride_y, zin); + +#define LOAD_TENSOR_M0X16(M0, N0, DATA_TYPE, a, input_ptr, src_stride_y, zin) \ + LOAD_TENSOR(M0, N0, DATA_TYPE, a, input_ptr, 0, src_stride_y, zin); +/** @}*/ // end of group LOAD_TENSOR_M0Xn + +/** Load 2D tensor (consecutive rows and columns) with Z offset. + * @name LOAD_TENSOR_M0XN0 + * + * @param[in] M0 The number of consecutive rows [0-16] + * @param[in] N0 The number of consecutive columns [0-16] + * @param[in] DATA_TYPE The data type of the target + * @param[in] BASENAME The basename of the result variables + * @param[in] PTR The base pointer for the data + * @param[in] STRIDE_Y The stride in y-axis direction + * @param[in] Z The z-axis offset vector + * @{ + */ +#define LOAD_TENSOR_M0XN0_STR(M0, N0, DATA_TYPE, BASENAME, PTR, STRIDE_Y, Z) LOAD_TENSOR_M0X##N0(M0, N0, DATA_TYPE, BASENAME, PTR, STRIDE_Y, Z) +#define LOAD_TENSOR_M0XN0(M0, N0, DATA_TYPE, BASENAME, PTR, STRIDE_Y, Z) LOAD_TENSOR_M0XN0_STR(M0, N0, DATA_TYPE, BASENAME, PTR, STRIDE_Y, Z) + /** Loads the rows from 0 to n-1 in the given variables (BASENAME0 to BASENAMEn-1). * @name LOAD_ROW_n * - * @param[in] N0 The number of rows to load + * @param[in] N0 The number of columns to load * @param[in] DATA_TYPE The data type of variables * @param[in] BASENAME The basename of the destination variables for the loaded rows * @param[in] PTR The base pointer -- cgit v1.2.1