diff options
Diffstat (limited to 'src/core/CL/cl_kernels/gemmlowp.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/gemmlowp.cl | 285 |
1 files changed, 0 insertions, 285 deletions
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl index 127df063f6..d9625e7117 100644 --- a/src/core/CL/cl_kernels/gemmlowp.cl +++ b/src/core/CL/cl_kernels/gemmlowp.cl @@ -195,291 +195,6 @@ (n0, k0, a, b, c); \ }) -#if defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_Y) && defined(COLS_A) -#define VECTOR_TYPE VEC_DATA_TYPE(DATA_TYPE, NUM_ELEMS_PROCESSED_PER_THREAD_X) -#define VECTOR_ACC_TYPE VEC_DATA_TYPE(ACC_DATA_TYPE, NUM_ELEMS_PROCESSED_PER_THREAD_X) -#define VECTOR_INT VEC_DATA_TYPE(int, NUM_ELEMS_PROCESSED_PER_THREAD_X) -/** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) in case both matrices have not been reshaped - * - * @attention The number of matrix A columns needs to be passed at compile time using -DCOLS_A - * - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The accumulator data type must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @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 matrix A NOT reshaped - * - * @param[in] src0_ptr Pointer to the source matrix. Supported data type: QASYMM8 - * @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes) - * @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes) - * @param[in] src0_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] src0_offset_first_element_in_bytes The offset of the first element in the source matrix - * @param[in] src1_ptr Pointer to the source matrix. Supported data type: same as @p src0_ptr - * @param[in] src1_stride_x Stride of the source matrix in X dimension (in bytes) - * @param[in] src1_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes) - * @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] src1_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 type: S32 - * @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_offset_first_element_in_bytes The offset of the first element in the destination matrix - * @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes) - * @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] src_cross_plane_pad (Optional) Bottom paddings in unit of elements for the input tensor (only if defined REINTERPRET_INPUT_AS_3D) - * @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements for the output tensor (only if defined REINTERPRET_OUTPUT_AS_3D) - */ -__kernel void gemmlowp_mm_midgard(IMAGE_DECLARATION(src0), - IMAGE_DECLARATION(src1), - IMAGE_DECLARATION(dst), - uint src0_stride_z, - uint src1_stride_z, - uint dst_stride_z -#if defined(REINTERPRET_INPUT_AS_3D) - , - uint src_cross_plane_pad -#endif // REINTERPRET_INPUT_AS_3D -#if defined(REINTERPRET_OUTPUT_AS_3D) - , - uint dst_cross_plane_pad -#endif // REINTERPRET_OUTPUT_AS_3D - ) -{ - int idx = get_global_id(0) * NUM_ELEMS_PROCESSED_PER_THREAD_X; - - // Compute starting address for matrix A and Matrix B - int2 src_addr = ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); - - // Update address for the matrix A - src_addr.s0 += get_global_id(1) * src0_stride_y * NUM_ELEMS_PROCESSED_PER_THREAD_Y; - - // Update address for the matrix B - src_addr.s1 += idx; - -#if defined(REINTERPRET_INPUT_AS_3D) - // Since we load a 2D input tile from a 3D tensor, we need to check when the plane changes across the z dimension - // in order to take into account the presence of possible cross plane paddings - // - // | | - // | plane0 | - // | | - // |__________________| - // |******************| - // | cross_plane_pad | - // |******************| - // | | - // | plane1 | - // | | - // |__________________| - - // The plane (zin) is calculated dividing M (get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y) by HEIGHT_GEMM3D - uint4 zin = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D; - zin = min(DEPTH_GEMM3D - 1, zin); - - // Add offset due to the cross plane paddings - zin *= (src_cross_plane_pad * src0_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply src0_stride_z by DEPTH_GEMM3D - src_addr.s0 += get_global_id(2) * src0_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_INPUT_AS_3D) - - // Add offset for batched GEMM - src_addr.s0 += get_global_id(2) * src0_stride_z; - -#endif // defined(REINTERPRET_INPUT_AS_3D) - -#if defined(MATRIX_B_DEPTH) - // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 - src_addr.s1 += (get_global_id(2) % MATRIX_B_DEPTH) * src1_stride_z; -#else // defined(MATRIX_B_DEPTH) - src_addr.s1 += get_global_id(2) * src1_stride_z; -#endif // defined(MATRIX_B_DEPTH) - - int end_row_vec_a = src_addr.s0 + COLS_A; - - VECTOR_ACC_TYPE acc0 = 0; -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 - VECTOR_ACC_TYPE acc1 = 0; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 - VECTOR_ACC_TYPE acc2 = 0; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 - VECTOR_ACC_TYPE acc3 = 0; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - VECTOR_ACC_TYPE acc4 = 0; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - - for(; src_addr.s0 <= (end_row_vec_a - 2); src_addr += (int2)(2, 2 * src1_stride_y)) - { - // Load values from matrix A - VEC_DATA_TYPE(DATA_TYPE, 2) - a0 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 - VEC_DATA_TYPE(DATA_TYPE, 2) - a1 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 - VEC_DATA_TYPE(DATA_TYPE, 2) - a2 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 - VEC_DATA_TYPE(DATA_TYPE, 2) - a3 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - VEC_DATA_TYPE(DATA_TYPE, 2) - a4 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 4 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - // Load values from matrix B - VECTOR_TYPE b0 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, (__global DATA_TYPE *)(src1_ptr + src_addr.s1)); - VECTOR_TYPE b1 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, (__global DATA_TYPE *)(src1_ptr + src_addr.s1 + src1_stride_y)); - - // Accumulate - acc0 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a0.s0; - acc0 += CONVERT(b1, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a0.s1; -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 - acc1 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a1.s0; - acc1 += CONVERT(b1, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a1.s1; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 - acc2 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a2.s0; - acc2 += CONVERT(b1, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a2.s1; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 - acc3 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a3.s0; - acc3 += CONVERT(b1, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a3.s1; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - acc4 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a4.s0; - acc4 += CONVERT(b1, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a4.s1; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - } - - for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(1, src1_stride_y)) - { - // Load values from matrix A - DATA_TYPE a0 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 - DATA_TYPE a1 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 - DATA_TYPE a2 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 - DATA_TYPE a3 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - DATA_TYPE a4 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 4 * src0_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - // Load values from matrix B - VECTOR_TYPE b0 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, (__global DATA_TYPE *)(src1_ptr + src_addr.s1)); - - // Accumulate - acc0 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a0; -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 - acc1 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a1; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 - acc2 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a2; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 - acc3 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a3; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - acc4 += CONVERT(b0, VECTOR_ACC_TYPE) * (VECTOR_ACC_TYPE)a4; -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - } - - const int z = get_global_id(2); - - // Compute destination address - Image dst = CONVERT_TO_IMAGE_STRUCT(dst); - -#if defined(REINTERPRET_OUTPUT_AS_3D) - // Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension - // in order to take into account the presence of possible cross plane paddings - // - // | | - // | plane0 | - // | | - // |__________________| - // |******************| - // | cross_plane_pad | - // |******************| - // | | - // | plane1 | - // | | - // |__________________| - - // The plane (zout) is calculated dividing M (get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y) by HEIGHT_GEMM3D - uint8 zout = ((uint8)(0, 1, 2, 3, 4, 5, 6, 7) + (uint8)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint8)HEIGHT_GEMM3D; - zout = min(DEPTH_GEMM3D - 1, zout); - - // Add offset due to the cross plane paddings - zout *= (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.ptr += z * dst_stride_z * DEPTH_GEMM3D; - - // Store the result - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc0, VECTOR_INT), 0, (__global int *)(dst.ptr + 0 * dst_stride_y + zout.s0)); -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc1, VECTOR_INT), 0, (__global int *)(dst.ptr + 1 * dst_stride_y + zout.s1)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc2, VECTOR_INT), 0, (__global int *)(dst.ptr + 2 * dst_stride_y + zout.s2)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc3, VECTOR_INT), 0, (__global int *)(dst.ptr + 3 * dst_stride_y + zout.s3)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc4, VECTOR_INT), 0, (__global int *)(dst.ptr + 4 * dst_stride_y + zout.s4)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - -#else // defined(REINTERPRET_OUTPUT_AS_3D) - // Add offset for batched GEMM - dst.ptr += z * dst_stride_z; - - // Store the result - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc0, VECTOR_INT), 0, (__global int *)(dst.ptr + 0 * dst_stride_y)); -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc1, VECTOR_INT), 0, (__global int *)(dst.ptr + 1 * dst_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc2, VECTOR_INT), 0, (__global int *)(dst.ptr + 2 * dst_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc3, VECTOR_INT), 0, (__global int *)(dst.ptr + 3 * dst_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 -#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 - VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) - (CONVERT(acc4, VECTOR_INT), 0, (__global int *)(dst.ptr + 4 * dst_stride_y)); -#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 4 -#endif // defined(REINTERPRET_OUTPUT_AS_3D) -} -#endif // defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_Y) && defined(COLS_A) - #if defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(M) && defined(N) /** This OpenCL kernel computes the matrix multiplication between 2 matrices with QASYMM/QASYMM_SIGNED data type. * The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be NOT transposed |