/* * Copyright (c) 2017 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 "helpers.h" #ifdef FIXED_POINT_POSITION #include "fixed_point.h" #endif // FIXED_POINT_POSITION /** This OpenCL kernel computes the "vector" 1x4 transposition of input matrix * * @param[in] src_ptr Pointer to the source matrix. Supported data types: U32/S32/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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_transpose1x4(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { uint x = get_global_id(0); uint y = get_global_id(1); // Compute address for Matrix B - source Image src = CONVERT_TO_IMAGE_STRUCT(src); // Compute address for Matrix B transposed - destination. X and Y are swapped uint dst_addr_in_bytes = y * 16 + ((x * dst_stride_y + dst_offset_first_element_in_bytes)); uint4 b0 = vload4(0, (__global uint *)src.ptr); vstore4(b0, 0, (__global uint *)(dst_ptr + dst_addr_in_bytes)); } /** This OpenCL kernel computes the "vector" 1x8 transposition of input matrix * * @param[in] src_ptr Pointer to the source matrix. Supported data types: U16/S16/QS16/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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_transpose1x8(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { uint x = get_global_id(0); uint y = get_global_id(1); // Compute address for Matrix B - source Image src = CONVERT_TO_IMAGE_STRUCT(src); // Compute address for Matrix B transposed - destination. X and Y are swapped uint dst_addr_in_bytes = y * 16 + ((x * dst_stride_y + dst_offset_first_element_in_bytes)); ushort8 b0 = vload8(0, (__global ushort *)src.ptr); vstore8(b0, 0, (__global ushort *)(dst_ptr + dst_addr_in_bytes)); } /** This OpenCL kernel computes the "vector" 1x16 transposition of input matrix * * @param[in] src_ptr Pointer to the source matrix. Supported data types: U8/S8/QS8 * @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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_transpose1x16(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { uint x = get_global_id(0); uint y = get_global_id(1); // Compute address for Matrix B - source Image src = CONVERT_TO_IMAGE_STRUCT(src); // Compute address for Matrix B transposed - destination. X and Y are swapped uint dst_addr_in_bytes = y * 16 + ((x * dst_stride_y + dst_offset_first_element_in_bytes)); uchar16 b0 = vload16(0, (__global uchar *)src.ptr); vstore16(b0, 0, (__global uchar *)(dst_ptr + dst_addr_in_bytes)); } /** This OpenCL kernel reshapes the input matrix transposing each 4x4 block and interleaving the values * * @param[in] src_ptr Pointer to the source matrix. Supported data types: U32/S32/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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_interleave4x4_32bit(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { // Compute source and destination addresses Image src = CONVERT_TO_IMAGE_STRUCT(src); Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Load values from Matrix A uint4 a0 = vload4(0, (__global uint *)(offset(&src, 0, 0))); uint4 a1 = vload4(0, (__global uint *)(offset(&src, 0, 1))); uint4 a2 = vload4(0, (__global uint *)(offset(&src, 0, 2))); uint4 a3 = vload4(0, (__global uint *)(offset(&src, 0, 3))); uint4 val0 = (uint4)(a0.s0, a1.s0, a2.s0, a3.s0); vstore4(val0, 0, ((__global uint *)dst.ptr) + 0); val0 = (uint4)(a0.s1, a1.s1, a2.s1, a3.s1); vstore4(val0, 0, ((__global uint *)dst.ptr) + 4); val0 = (uint4)(a0.s2, a1.s2, a2.s2, a3.s2); vstore4(val0, 0, ((__global uint *)dst.ptr) + 8); val0 = (uint4)(a0.s3, a1.s3, a2.s3, a3.s3); vstore4(val0, 0, ((__global uint *)dst.ptr) + 12); } /** This OpenCL kernel reshapes the input matrix transposing each 4x4 block and interleaving the values * * @param[in] src_ptr Pointer to the source matrix. Supported data types: U16/S16/QS16/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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_interleave4x4_16bit(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { // Compute source and destination addresses Image src = CONVERT_TO_IMAGE_STRUCT(src); Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Load values from Matrix A ushort8 a0 = vload8(0, (__global ushort *)(offset(&src, 0, 0))); ushort8 a1 = vload8(0, (__global ushort *)(offset(&src, 0, 1))); ushort8 a2 = vload8(0, (__global ushort *)(offset(&src, 0, 2))); ushort8 a3 = vload8(0, (__global ushort *)(offset(&src, 0, 3))); ushort8 val0 = (ushort8)((ushort4)(a0.s0, a1.s0, a2.s0, a3.s0), (ushort4)(a0.s1, a1.s1, a2.s1, a3.s1)); vstore8(val0, 0, ((__global ushort *)dst.ptr) + 0); val0 = (ushort8)((ushort4)(a0.s2, a1.s2, a2.s2, a3.s2), (ushort4)(a0.s3, a1.s3, a2.s3, a3.s3)); vstore8(val0, 0, ((__global ushort *)dst.ptr) + 8); val0 = (ushort8)((ushort4)(a0.s4, a1.s4, a2.s4, a3.s4), (ushort4)(a0.s5, a1.s5, a2.s5, a3.s5)); vstore8(val0, 0, ((__global ushort *)dst.ptr) + 16); val0 = (ushort8)((ushort4)(a0.s6, a1.s6, a2.s6, a3.s6), (ushort4)(a0.s7, a1.s7, a2.s7, a3.s7)); vstore8(val0, 0, ((__global ushort *)dst.ptr) + 24); } /** This OpenCL kernel reshapes the input matrix transposing each 4x4 block and interleaving the values * * @param[in] src_ptr Pointer to the source matrix. Supported data types: U8/S8/QS8 * @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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_interleave4x4_8bit(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { // Compute source and destination addresses Image src = CONVERT_TO_IMAGE_STRUCT(src); Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Load values from Matrix A uchar16 a0 = vload16(0, (__global uchar *)(offset(&src, 0, 0))); uchar16 a1 = vload16(0, (__global uchar *)(offset(&src, 0, 1))); uchar16 a2 = vload16(0, (__global uchar *)(offset(&src, 0, 2))); uchar16 a3 = vload16(0, (__global uchar *)(offset(&src, 0, 3))); uchar16 val0 = (uchar16)((uchar4)(a0.s0, a1.s0, a2.s0, a3.s0), (uchar4)(a0.s1, a1.s1, a2.s1, a3.s1), (uchar4)(a0.s2, a1.s2, a2.s2, a3.s2), (uchar4)(a0.s3, a1.s3, a2.s3, a3.s3)); vstore16(val0, 0, ((__global uchar *)dst.ptr) + 0); val0 = (uchar16)((uchar4)(a0.s4, a1.s4, a2.s4, a3.s4), (uchar4)(a0.s5, a1.s5, a2.s5, a3.s5), (uchar4)(a0.s6, a1.s6, a2.s6, a3.s6), (uchar4)(a0.s7, a1.s7, a2.s7, a3.s7)); vstore16(val0, 0, ((__global uchar *)dst.ptr) + 16); val0 = (uchar16)((uchar4)(a0.s8, a1.s8, a2.s8, a3.s8), (uchar4)(a0.s9, a1.s9, a2.s9, a3.s9), (uchar4)(a0.sA, a1.sA, a2.sA, a3.sA), (uchar4)(a0.sB, a1.sB, a2.sB, a3.sB)); vstore16(val0, 0, ((__global uchar *)dst.ptr) + 32); val0 = (uchar16)((uchar4)(a0.sC, a1.sC, a2.sC, a3.sC), (uchar4)(a0.sD, a1.sD, a2.sD, a3.sD), (uchar4)(a0.sE, a1.sE, a2.sE, a3.sE), (uchar4)(a0.sF, a1.sF, a2.sF, a3.sF)); vstore16(val0, 0, ((__global uchar *)dst.ptr) + 48); } #if defined(COLS_B) /** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_8bit and @ref gemm_transpose1x16 before running the matrix multiplication * * @attention The number of matrix B columns needs to be passed at compile time using -DCOLS_B * * @param[in] src0_ptr Pointer to the source matrix. Supported formats: U8 * @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 formats: 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 formats: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix * @param[in] a_offset Offset to be added to each element of the matrix A * @param[in] b_offset Offset to be added to each element of the matrix B. * @param[in] c_offset Offset to be added to each element of the matrix C. * @param[in] c_mult_int Multiplied with each element of the matrix C. * @param[in] shift Number of bits to shift right the result. */ __kernel void gemm_mm_interleaved_transposed_u8(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst), int a_offset, int b_offset, int c_offset, int c_mult_int, int shift) { // src_addr.s0 = address of matrix A // src_addr.s1 = address of matrix B // Compute address for matrix A and B int2 src_addr = (int2)(get_global_id(1), get_global_id(0)) * (int2)((src0_stride_y), (src1_stride_y)); // Add offset_first_element_in_bytes src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); // Compute end row address for matrix B int end_row_mtx_b = src_addr.s1 + COLS_B; // Reset accumulators int16 c00 = 0.0f; int16 c10 = 0.0f; int16 c20 = 0.0f; int16 c30 = 0.0f; for(; src_addr.s1 <= (end_row_mtx_b - 8); src_addr += (int2)(8, 32)) { // Load values from matrix A (interleaved) and matrix B (transposed) int8 a0 = (int8)a_offset + convert_int8(vload8(0, ((__global uchar *)src0_ptr) + src_addr.s0)); int16 b0 = (int16)b_offset + convert_int16(vload16(0, ((__global uchar *)src1_ptr) + src_addr.s1)); c00 += (int16)a0.s0 * b0; c10 += (int16)a0.s1 * b0; c20 += (int16)a0.s2 * b0; c30 += (int16)a0.s3 * b0; int16 b1 = (int16)b_offset + convert_int16(vload16(0, ((__global uchar *)src1_ptr) + src_addr.s1 + 16)); c00 += (int16)a0.s4 * b1; c10 += (int16)a0.s5 * b1; c20 += (int16)a0.s6 * b1; c30 += (int16)a0.s7 * b1; } for(; src_addr.s1 < end_row_mtx_b; src_addr += (int2)(4, 16)) { // Load values from matrix A (interleaved) and matrix B (transposed) int4 a0 = (int4)a_offset + convert_int4(vload4(0, ((__global uchar *)src0_ptr) + src_addr.s0)); int16 b0 = (int16)b_offset + convert_int16(vload16(0, ((__global uchar *)src1_ptr) + src_addr.s1)); c00 += (int16)a0.s0 * b0; c10 += (int16)a0.s1 * b0; c20 += (int16)a0.s2 * b0; c30 += (int16)a0.s3 * b0; } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix product c00 = (((int16)c_offset + c00) * (int16)c_mult_int) >> shift; c10 = (((int16)c_offset + c10) * (int16)c_mult_int) >> shift; c20 = (((int16)c_offset + c20) * (int16)c_mult_int) >> shift; c30 = (((int16)c_offset + c30) * (int16)c_mult_int) >> shift; // Store 4x16 block vstore16(convert_uchar16_sat(c00), 0, (__global uchar *)(offset(&dst, 0, 0))); vstore16(convert_uchar16_sat(c10), 0, (__global uchar *)(offset(&dst, 0, 1))); vstore16(convert_uchar16_sat(c20), 0, (__global uchar *)(offset(&dst, 0, 2))); vstore16(convert_uchar16_sat(c30), 0, (__global uchar *)(offset(&dst, 0, 3))); } /** This OpenCL kernel is optimised for Midgard. It computes the matrix multiplication between matrix A (src0) and matrix B (src1) * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_32bit and @ref gemm_transpose1x4 before running the matrix multiplication * * @attention The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_interleaved_transposed_f32_midgard(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { // src_addr.s0 = address of matrix A // src_addr.s1 = address of matrix B // Compute address for matrix A and B int2 src_addr = (int2)(get_global_id(1), get_global_id(0)) * (int2)((src0_stride_y), (src1_stride_y)); // Add offset_first_element_in_bytes src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); // Divide by 4 in order to get the src_addr in unit of float src_addr = src_addr >> 2; // Compute end row address for matrix B int end_row_mtx_b = src_addr.s1 + COLS_B; // Reset accumulators float4 c00 = 0.0f; float4 c10 = 0.0f; float4 c20 = 0.0f; float4 c30 = 0.0f; for(; src_addr.s1 <= (end_row_mtx_b - 8); src_addr += (int2)(8, 8)) { // Load values from matrix A (interleaved) and matrix B (transposed) float4 a0 = vload4(0, ((__global float *)src0_ptr) + src_addr.s0); float4 b0 = vload4(0, ((__global float *)src1_ptr) + src_addr.s1); c00 += (float4)a0.s0 * b0; c10 += (float4)a0.s1 * b0; c20 += (float4)a0.s2 * b0; c30 += (float4)a0.s3 * b0; // Load values from matrix A (interleaved) and matrix B (transposed) a0 = vload4(0, ((__global float *)src0_ptr) + src_addr.s0 + 4); b0 = vload4(0, ((__global float *)src1_ptr) + src_addr.s1 + 4); c00 += (float4)a0.s0 * b0; c10 += (float4)a0.s1 * b0; c20 += (float4)a0.s2 * b0; c30 += (float4)a0.s3 * b0; } for(; src_addr.s1 < end_row_mtx_b; src_addr += (int2)(4, 4)) { // Load values from matrix A (interleaved) and matrix B (transposed) float4 a0 = vload4(0, ((__global float *)src0_ptr) + src_addr.s0); float4 b0 = vload4(0, ((__global float *)src1_ptr) + src_addr.s1); c00 += (float4)a0.s0 * b0; c10 += (float4)a0.s1 * b0; c20 += (float4)a0.s2 * b0; c30 += (float4)a0.s3 * b0; } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); #if defined(ALPHA) // Multiply by the weight of matrix product c00 = c00 * (float4)ALPHA; c10 = c10 * (float4)ALPHA; c20 = c20 * (float4)ALPHA; c30 = c30 * (float4)ALPHA; #endif // defined(ALPHA) // Store 4x4 block vstore4(c00, 0, (__global float *)(offset(&dst, 0, 0))); vstore4(c10, 0, (__global float *)(offset(&dst, 0, 1))); vstore4(c20, 0, (__global float *)(offset(&dst, 0, 2))); vstore4(c30, 0, (__global float *)(offset(&dst, 0, 3))); } /** This OpenCL kernel is optimized for Bifrost. It computes the matrix multiplication between matrix A (src0) and matrix B (src1) * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_32bit and @ref gemm_transpose1x4 before running the matrix multiplication * * @attention The number of matrix B columns and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { // src_addr_a = address of matrix A // src_addr_b = address of matrix B __global float *src_addr_a = (__global float *)(src0_ptr + get_global_id(1) * src0_stride_y + src0_offset_first_element_in_bytes); __global float *src_addr_b = (__global float *)(src1_ptr + get_global_id(0) * src1_stride_y + src1_offset_first_element_in_bytes); // Compute end row address for matrix B __global float *src_end_addr_b = src_addr_b + COLS_B; // Reset accumulators float c00 = 0.0f; float c01 = 0.0f; float c02 = 0.0f; float c03 = 0.0f; float c10 = 0.0f; float c11 = 0.0f; float c12 = 0.0f; float c13 = 0.0f; float c20 = 0.0f; float c21 = 0.0f; float c22 = 0.0f; float c23 = 0.0f; float c30 = 0.0f; float c31 = 0.0f; float c32 = 0.0f; float c33 = 0.0f; for(; src_addr_b <= (src_end_addr_b - 16); src_addr_a += 16, src_addr_b += 16) { // Load values from matrix A (interleaved) and matrix B (transposed) float4 a0 = vload4(0, src_addr_a); float4 b0 = vload4(0, src_addr_b); c00 = fma(a0.s0, b0.s0, c00); c01 = fma(a0.s0, b0.s1, c01); c02 = fma(a0.s0, b0.s2, c02); c03 = fma(a0.s0, b0.s3, c03); c10 = fma(a0.s1, b0.s0, c10); c11 = fma(a0.s1, b0.s1, c11); c12 = fma(a0.s1, b0.s2, c12); c13 = fma(a0.s1, b0.s3, c13); c20 = fma(a0.s2, b0.s0, c20); c21 = fma(a0.s2, b0.s1, c21); c22 = fma(a0.s2, b0.s2, c22); c23 = fma(a0.s2, b0.s3, c23); c30 = fma(a0.s3, b0.s0, c30); c31 = fma(a0.s3, b0.s1, c31); c32 = fma(a0.s3, b0.s2, c32); c33 = fma(a0.s3, b0.s3, c33); // Load values from matrix A (interleaved) and matrix B (transposed) a0 = vload4(0, src_addr_a + 4); b0 = vload4(0, src_addr_b + 4); c00 = fma(a0.s0, b0.s0, c00); c01 = fma(a0.s0, b0.s1, c01); c02 = fma(a0.s0, b0.s2, c02); c03 = fma(a0.s0, b0.s3, c03); c10 = fma(a0.s1, b0.s0, c10); c11 = fma(a0.s1, b0.s1, c11); c12 = fma(a0.s1, b0.s2, c12); c13 = fma(a0.s1, b0.s3, c13); c20 = fma(a0.s2, b0.s0, c20); c21 = fma(a0.s2, b0.s1, c21); c22 = fma(a0.s2, b0.s2, c22); c23 = fma(a0.s2, b0.s3, c23); c30 = fma(a0.s3, b0.s0, c30); c31 = fma(a0.s3, b0.s1, c31); c32 = fma(a0.s3, b0.s2, c32); c33 = fma(a0.s3, b0.s3, c33); // Load values from matrix A (interleaved) and matrix B (transposed) a0 = vload4(0, src_addr_a + 8); b0 = vload4(0, src_addr_b + 8); c00 = fma(a0.s0, b0.s0, c00); c01 = fma(a0.s0, b0.s1, c01); c02 = fma(a0.s0, b0.s2, c02); c03 = fma(a0.s0, b0.s3, c03); c10 = fma(a0.s1, b0.s0, c10); c11 = fma(a0.s1, b0.s1, c11); c12 = fma(a0.s1, b0.s2, c12); c13 = fma(a0.s1, b0.s3, c13); c20 = fma(a0.s2, b0.s0, c20); c21 = fma(a0.s2, b0.s1, c21); c22 = fma(a0.s2, b0.s2, c22); c23 = fma(a0.s2, b0.s3, c23); c30 = fma(a0.s3, b0.s0, c30); c31 = fma(a0.s3, b0.s1, c31); c32 = fma(a0.s3, b0.s2, c32); c33 = fma(a0.s3, b0.s3, c33); // Load values from matrix A (interleaved) and matrix B (transposed) a0 = vload4(0, src_addr_a + 12); b0 = vload4(0, src_addr_b + 12); c00 = fma(a0.s0, b0.s0, c00); c01 = fma(a0.s0, b0.s1, c01); c02 = fma(a0.s0, b0.s2, c02); c03 = fma(a0.s0, b0.s3, c03); c10 = fma(a0.s1, b0.s0, c10); c11 = fma(a0.s1, b0.s1, c11); c12 = fma(a0.s1, b0.s2, c12); c13 = fma(a0.s1, b0.s3, c13); c20 = fma(a0.s2, b0.s0, c20); c21 = fma(a0.s2, b0.s1, c21); c22 = fma(a0.s2, b0.s2, c22); c23 = fma(a0.s2, b0.s3, c23); c30 = fma(a0.s3, b0.s0, c30); c31 = fma(a0.s3, b0.s1, c31); c32 = fma(a0.s3, b0.s2, c32); c33 = fma(a0.s3, b0.s3, c33); } for(; src_addr_b < src_end_addr_b; src_addr_a += 4, src_addr_b += 4) { // Load values from matrix A (interleaved) and matrix B (transposed) float4 a0 = vload4(0, src_addr_a); float4 b0 = vload4(0, src_addr_b); c00 = fma(a0.s0, b0.s0, c00); c01 = fma(a0.s0, b0.s1, c01); c02 = fma(a0.s0, b0.s2, c02); c03 = fma(a0.s0, b0.s3, c03); c10 = fma(a0.s1, b0.s0, c10); c11 = fma(a0.s1, b0.s1, c11); c12 = fma(a0.s1, b0.s2, c12); c13 = fma(a0.s1, b0.s3, c13); c20 = fma(a0.s2, b0.s0, c20); c21 = fma(a0.s2, b0.s1, c21); c22 = fma(a0.s2, b0.s2, c22); c23 = fma(a0.s2, b0.s3, c23); c30 = fma(a0.s3, b0.s0, c30); c31 = fma(a0.s3, b0.s1, c31); c32 = fma(a0.s3, b0.s2, c32); c33 = fma(a0.s3, b0.s3, c33); } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); #if defined(ALPHA) // Multiply by the weight of matrix product c00 = c00 * ALPHA; c01 = c01 * ALPHA; c02 = c02 * ALPHA; c03 = c03 * ALPHA; c10 = c10 * ALPHA; c11 = c11 * ALPHA; c12 = c12 * ALPHA; c13 = c13 * ALPHA; c20 = c20 * ALPHA; c21 = c21 * ALPHA; c22 = c22 * ALPHA; c23 = c23 * ALPHA; c30 = c30 * ALPHA; c31 = c31 * ALPHA; c32 = c32 * ALPHA; c33 = c33 * ALPHA; #endif // defined(ALPHA) barrier(CLK_GLOBAL_MEM_FENCE); // Store 4x4 block vstore4((float4)(c00, c01, c02, c03), 0, (__global float *)(offset(&dst, 0, 0))); vstore4((float4)(c10, c11, c12, c13), 0, (__global float *)(offset(&dst, 0, 1))); vstore4((float4)(c20, c21, c22, c23), 0, (__global float *)(offset(&dst, 0, 2))); vstore4((float4)(c30, c31, c32, c33), 0, (__global float *)(offset(&dst, 0, 3))); } #if defined(ARM_COMPUTE_OPENCL_FP16_ENABLED) /** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_16bit and @ref gemm_transpose1x8 before running the matrix multiplication * * @attention The number of matrix B columns and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { // src_addr.s0 = address of matrix A // src_addr.s1 = address of matrix B // Compute address for matrix A and B int2 src_addr = (int2)(get_global_id(1), get_global_id(0)) * (int2)((src0_stride_y), (src1_stride_y)); // Add offset_first_element_in_bytes src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); // Divide by 2 in order to get the src_addr in unit of half src_addr = src_addr >> 1; // Compute end row address for matrix B int end_row_mtx_b = src_addr.s1 + COLS_B; // Reset accumulators half8 c00 = 0.0f; half8 c10 = 0.0f; half8 c20 = 0.0f; half8 c30 = 0.0f; for(; src_addr.s1 <= (end_row_mtx_b - 16); src_addr += (int2)(8, 16)) { // Load values from matrix A (interleaved) and matrix B (transposed) half4 a0 = vload4(0, ((__global half *)src0_ptr) + src_addr.s0); half8 b0 = vload8(0, ((__global half *)src1_ptr) + src_addr.s1); c00 += (half8)a0.s0 * b0; c10 += (half8)a0.s1 * b0; c20 += (half8)a0.s2 * b0; c30 += (half8)a0.s3 * b0; // Load values from matrix A (interleaved) and matrix B (transposed) a0 = vload4(0, ((__global half *)src0_ptr) + src_addr.s0 + 4); b0 = vload8(0, ((__global half *)src1_ptr) + src_addr.s1 + 8); c00 += (half8)a0.s0 * b0; c10 += (half8)a0.s1 * b0; c20 += (half8)a0.s2 * b0; c30 += (half8)a0.s3 * b0; } for(; src_addr.s1 < end_row_mtx_b; src_addr += (int2)(4, 8)) { // Load values from matrix A (interleaved) and matrix B (transposed) half4 a0 = vload4(0, ((__global half *)src0_ptr) + src_addr.s0); half8 b0 = vload8(0, ((__global half *)src1_ptr) + src_addr.s1); c00 += (half8)a0.s0 * b0; c10 += (half8)a0.s1 * b0; c20 += (half8)a0.s2 * b0; c30 += (half8)a0.s3 * b0; } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); #if defined(ALPHA) // Multiply by the weight of matrix product c00 = c00 * (half8)ALPHA; c10 = c10 * (half8)ALPHA; c20 = c20 * (half8)ALPHA; c30 = c30 * (half8)ALPHA; #endif // defined(ALPHA) // Store 4x8 block vstore8(c00, 0, (__global half *)(offset(&dst, 0, 0))); vstore8(c10, 0, (__global half *)(offset(&dst, 0, 1))); vstore8(c20, 0, (__global half *)(offset(&dst, 0, 2))); vstore8(c30, 0, (__global half *)(offset(&dst, 0, 3))); } #endif // defined(ARM_COMPUTE_OPENCL_FP16_ENABLED) #if defined(FIXED_POINT_POSITION) /** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) in 8 bit fixed point precision * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_8bit and @ref gemm_transpose1x16 before running the matrix multiplication * * @attention The number of matrix B columns, the optional alpha's value and fixed point position need to be passed at compile time using -DCOLS_B -DALPHA and -DFIXED_POINT_POSITION * * @note: ALPHA must be passed in 8 bit fixed point format * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_interleaved_transposed_qs8(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { // src_addr.s0 = address of matrix A // src_addr.s1 = address of matrix B // Compute address for matrix A and B int2 src_addr = (int2)(get_global_id(1), get_global_id(0)) * (int2)((src0_stride_y), (src1_stride_y)); // Add offset_first_element_in_bytes src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); // Compute end row address for matrix B int end_row_mtx_b = src_addr.s1 + COLS_B; // Reset accumulators short8 c00 = 0.0f; short8 c10 = 0.0f; short8 c20 = 0.0f; short8 c30 = 0.0f; short8 c01 = 0.0f; short8 c11 = 0.0f; short8 c21 = 0.0f; short8 c31 = 0.0f; // This for loop performs 1 accumulation for each iteration for(; src_addr.s1 <= (end_row_mtx_b - 16); src_addr += (int2)(4, 16)) { // Load values from matrix A (interleaved) and matrix B (transposed) char4 a0 = vload4(0, ((__global char *)src0_ptr) + src_addr.s0); char16 b0 = vload16(0, ((__global char *)src1_ptr) + src_addr.s1); c00 = mlal_sat_qs8x8(c00, (char8)a0.s0, b0.s01234567, FIXED_POINT_POSITION); c10 = mlal_sat_qs8x8(c10, (char8)a0.s1, b0.s01234567, FIXED_POINT_POSITION); c20 = mlal_sat_qs8x8(c20, (char8)a0.s2, b0.s01234567, FIXED_POINT_POSITION); c30 = mlal_sat_qs8x8(c30, (char8)a0.s3, b0.s01234567, FIXED_POINT_POSITION); c01 = mlal_sat_qs8x8(c01, (char8)a0.s0, b0.s89ABCDEF, FIXED_POINT_POSITION); c11 = mlal_sat_qs8x8(c11, (char8)a0.s1, b0.s89ABCDEF, FIXED_POINT_POSITION); c21 = mlal_sat_qs8x8(c21, (char8)a0.s2, b0.s89ABCDEF, FIXED_POINT_POSITION); c31 = mlal_sat_qs8x8(c31, (char8)a0.s3, b0.s89ABCDEF, FIXED_POINT_POSITION); } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix product char16 c00_qs8 = convert_char16_sat((short16)(c00, c01)); char16 c10_qs8 = convert_char16_sat((short16)(c10, c11)); char16 c20_qs8 = convert_char16_sat((short16)(c20, c21)); char16 c30_qs8 = convert_char16_sat((short16)(c30, c31)); #if defined(ALPHA) c00_qs8 = mul_sat_qs8x16(c00_qs8, (char16)ALPHA, FIXED_POINT_POSITION); c10_qs8 = mul_sat_qs8x16(c10_qs8, (char16)ALPHA, FIXED_POINT_POSITION); c20_qs8 = mul_sat_qs8x16(c20_qs8, (char16)ALPHA, FIXED_POINT_POSITION); c30_qs8 = mul_sat_qs8x16(c30_qs8, (char16)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) // Store 16x4 block vstore16(c00_qs8, 0, (__global char *)(offset(&dst, 0, 0))); vstore16(c10_qs8, 0, (__global char *)(offset(&dst, 0, 1))); vstore16(c20_qs8, 0, (__global char *)(offset(&dst, 0, 2))); vstore16(c30_qs8, 0, (__global char *)(offset(&dst, 0, 3))); } /** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) in 16 bit fixed point precision * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_16bit and @ref gemm_transpose1x8 before running the matrix multiplication * * @attention The number of matrix B columns, the optional alpha's value and fixed point position need to be passed at compile time using -DCOLS_B -DALPHA and -DFIXED_POINT_POSITION * * @note: ALPHA must be passed in 16 bit fixed point format * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS16 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_interleaved_transposed_qs16(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { // src_addr.s0 = address of matrix A // src_addr.s1 = address of matrix B // Compute address for matrix A and B int2 src_addr = (int2)(get_global_id(1), get_global_id(0)) * (int2)((src0_stride_y), (src1_stride_y)); // Add offset_first_element_in_bytes src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); // Divide by 2 in order to get the src_addr in unit of short src_addr = src_addr >> 1; // Compute end row address for matrix B int end_row_mtx_b = src_addr.s1 + COLS_B; // Reset accumulators int8 c00 = 0.0f; int8 c10 = 0.0f; int8 c20 = 0.0f; int8 c30 = 0.0f; // This for loop performs 1 accumulation for each iteration for(; src_addr.s1 <= (end_row_mtx_b - 8); src_addr += (int2)(4, 8)) { /* Load values from matrix A (interleaved) and matrix B (transposed) */ short4 a0 = vload4(0, ((__global short *)src0_ptr) + src_addr.s0); short8 b0 = vload8(0, ((__global short *)src1_ptr) + src_addr.s1); c00 = mlal_sat_qs16x8(c00, (short8)a0.s0, b0, FIXED_POINT_POSITION); c10 = mlal_sat_qs16x8(c10, (short8)a0.s1, b0, FIXED_POINT_POSITION); c20 = mlal_sat_qs16x8(c20, (short8)a0.s2, b0, FIXED_POINT_POSITION); c30 = mlal_sat_qs16x8(c30, (short8)a0.s3, b0, FIXED_POINT_POSITION); } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix product short8 c00_qs16 = convert_short8_sat(c00); short8 c10_qs16 = convert_short8_sat(c10); short8 c20_qs16 = convert_short8_sat(c20); short8 c30_qs16 = convert_short8_sat(c30); #if defined(ALPHA) c00_qs16 = mul_sat_qs16x8(c00_qs16, (short8)ALPHA, FIXED_POINT_POSITION); c10_qs16 = mul_sat_qs16x8(c10_qs16, (short8)ALPHA, FIXED_POINT_POSITION); c20_qs16 = mul_sat_qs16x8(c20_qs16, (short8)ALPHA, FIXED_POINT_POSITION); c30_qs16 = mul_sat_qs16x8(c30_qs16, (short8)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) // Store 8x4 block vstore8(c00_qs16, 0, (__global short *)(offset(&dst, 0, 0))); vstore8(c10_qs16, 0, (__global short *)(offset(&dst, 0, 1))); vstore8(c20_qs16, 0, (__global short *)(offset(&dst, 0, 2))); vstore8(c30_qs16, 0, (__global short *)(offset(&dst, 0, 3))); } #endif // defined(FIXED_POINT_POSITION) #endif // defined(COLS_B) #if defined(COLS_A) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && (NUM_ELEMS_PROCESSED_PER_THREAD_Y) #if defined(DATA_TYPE) #define VECTOR_TYPE VEC_DATA_TYPE(DATA_TYPE, NUM_ELEMS_PROCESSED_PER_THREAD_X) /** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped * * @note This OpenCL kernel works with floating point data types (F16/F32) * @note The floating point data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float) * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y * @note The number of matrix A columns and the optional alpha's value need to be passed at compile time using -DCOLS_A and -DALPHA * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { 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 * sizeof(DATA_TYPE); int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(DATA_TYPE)); VECTOR_TYPE acc0 = 0.0f; #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 VECTOR_TYPE acc1 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 VECTOR_TYPE acc2 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 VECTOR_TYPE acc3 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 for(; src_addr.s0 <= (end_row_vec_a - 2 * (int)sizeof(DATA_TYPE)); src_addr += (int2)(2 * sizeof(DATA_TYPE), 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 // 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 += b0 * (VECTOR_TYPE)a0.s0; acc0 += b1 * (VECTOR_TYPE)a0.s1; #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc1 += b0 * (VECTOR_TYPE)a1.s0; acc1 += b1 * (VECTOR_TYPE)a1.s1; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc2 += b0 * (VECTOR_TYPE)a2.s0; acc2 += b1 * (VECTOR_TYPE)a2.s1; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc3 += b0 * (VECTOR_TYPE)a3.s0; acc3 += b1 * (VECTOR_TYPE)a3.s1; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(DATA_TYPE), 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 // 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 += b0 * (VECTOR_TYPE)a0; #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc1 += b0 * (VECTOR_TYPE)a1; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc2 += b0 * (VECTOR_TYPE)a2; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc3 += b0 * (VECTOR_TYPE)a3; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) acc0 = acc0 * (VECTOR_TYPE)ALPHA; #endif // defined(ALPHA) VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) (acc0, 0, (__global DATA_TYPE *)(offset(&dst, 0, 0))); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if defined(ALPHA) acc1 = acc1 * (VECTOR_TYPE)ALPHA; #endif // defined(ALPHA) VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) (acc1, 0, (__global DATA_TYPE *)(offset(&dst, 0, 1))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if defined(ALPHA) acc2 = acc2 * (VECTOR_TYPE)ALPHA; #endif // defined(ALPHA) VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) (acc2, 0, (__global DATA_TYPE *)(offset(&dst, 0, 2))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 #if defined(ALPHA) acc3 = acc3 * (VECTOR_TYPE)ALPHA; #endif // defined(ALPHA) VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) (acc3, 0, (__global DATA_TYPE *)(offset(&dst, 0, 3))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } #endif // defined(DATA_TYPE) /** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped * * @note This OpenCL kernel works with the 32-bit floating point data type (float) and uses the fma units. * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y. * This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=4. * @note The number of matrix A columns must be passed at compile time using -DCOLS_A. * @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { 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 matrix A src_addr.s0 += get_global_id(1) * src0_stride_y * NUM_ELEMS_PROCESSED_PER_THREAD_Y; // Update address for matrix B src_addr.s1 += idx * sizeof(float); // Address boundary for matrix A int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(float)); // Initialize accumulators float acc00 = 0.0f; float acc01 = 0.0f; float acc02 = 0.0f; float acc03 = 0.0f; #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 float acc10 = 0.0f; float acc11 = 0.0f; float acc12 = 0.0f; float acc13 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 float acc20 = 0.0f; float acc21 = 0.0f; float acc22 = 0.0f; float acc23 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 float acc30 = 0.0f; float acc31 = 0.0f; float acc32 = 0.0f; float acc33 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 // A and B src indices get incremented at the same time. for(; src_addr.s0 <= (end_row_vec_a - 2 * (int)sizeof(float)); src_addr += (int2)(2 * sizeof(float), 2 * src1_stride_y)) { // Load values from matrix A float2 a0 = vload2(0, (__global float *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 float2 a1 = vload2(0, (__global float *)(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 float2 a2 = vload2(0, (__global float *)(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 float2 a3 = vload2(0, (__global float *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 // Load values from matrix B float4 b0 = vload4(0, (__global float *)(src1_ptr + src_addr.s1 + 0 * src1_stride_y)); float4 b1 = vload4(0, (__global float *)(src1_ptr + src_addr.s1 + 1 * src1_stride_y)); // Multiply and accumulate acc00 = fma(a0.s0, b0.s0, acc00); acc00 = fma(a0.s1, b1.s0, acc00); acc01 = fma(a0.s0, b0.s1, acc01); acc01 = fma(a0.s1, b1.s1, acc01); acc02 = fma(a0.s0, b0.s2, acc02); acc02 = fma(a0.s1, b1.s2, acc02); acc03 = fma(a0.s1, b1.s3, acc03); acc03 = fma(a0.s0, b0.s3, acc03); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc10 = fma(a1.s0, b0.s0, acc10); acc11 = fma(a1.s0, b0.s1, acc11); acc12 = fma(a1.s0, b0.s2, acc12); acc13 = fma(a1.s0, b0.s3, acc13); acc10 = fma(a1.s1, b1.s0, acc10); acc11 = fma(a1.s1, b1.s1, acc11); acc12 = fma(a1.s1, b1.s2, acc12); acc13 = fma(a1.s1, b1.s3, acc13); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc20 = fma(a2.s0, b0.s0, acc20); acc21 = fma(a2.s0, b0.s1, acc21); acc22 = fma(a2.s0, b0.s2, acc22); acc23 = fma(a2.s0, b0.s3, acc23); acc20 = fma(a2.s1, b1.s0, acc20); acc21 = fma(a2.s1, b1.s1, acc21); acc22 = fma(a2.s1, b1.s2, acc22); acc23 = fma(a2.s1, b1.s3, acc23); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc30 = fma(a3.s0, b0.s0, acc30); acc31 = fma(a3.s0, b0.s1, acc31); acc32 = fma(a3.s0, b0.s2, acc32); acc33 = fma(a3.s0, b0.s3, acc33); acc30 = fma(a3.s1, b1.s0, acc30); acc31 = fma(a3.s1, b1.s1, acc31); acc32 = fma(a3.s1, b1.s2, acc32); acc33 = fma(a3.s1, b1.s3, acc33); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(float), src1_stride_y)) { // Load values from matrix A float a0 = *((__global float *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 float a1 = *((__global float *)(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 float a2 = *((__global float *)(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 float a3 = *((__global float *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 // Load values from matrix B float4 b0 = vload4(0, (__global float *)(src1_ptr + src_addr.s1)); // Multiply and accumulate acc00 = fma(a0, b0.s0, acc00); acc01 = fma(a0, b0.s1, acc01); acc02 = fma(a0, b0.s2, acc02); acc03 = fma(a0, b0.s3, acc03); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc10 = fma(a1, b0.s0, acc10); acc11 = fma(a1, b0.s1, acc11); acc12 = fma(a1, b0.s2, acc12); acc13 = fma(a1, b0.s3, acc13); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc20 = fma(a2, b0.s0, acc20); acc21 = fma(a2, b0.s1, acc21); acc22 = fma(a2, b0.s2, acc22); acc23 = fma(a2, b0.s3, acc23); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc30 = fma(a3, b0.s0, acc30); acc31 = fma(a3, b0.s1, acc31); acc32 = fma(a3, b0.s2, acc32); acc33 = fma(a3, b0.s3, acc33); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) acc00 = acc00 * ALPHA; acc01 = acc01 * ALPHA; acc02 = acc02 * ALPHA; acc03 = acc03 * ALPHA; #endif // defined(ALPHA) float4 acc0 = ((float4)(acc00, acc01, acc02, acc03)); vstore4(acc0, 0, (__global float *)(offset(&dst, 0, 0))); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if defined(ALPHA) acc10 = acc10 * ALPHA; acc11 = acc11 * ALPHA; acc12 = acc12 * ALPHA; acc13 = acc13 * ALPHA; #endif // defined(ALPHA) float4 acc1 = ((float4)(acc10, acc11, acc12, acc13)); vstore4(acc1, 0, (__global float *)(offset(&dst, 0, 1))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if defined(ALPHA) acc20 = acc20 * ALPHA; acc21 = acc21 * ALPHA; acc22 = acc22 * ALPHA; acc23 = acc23 * ALPHA; #endif // defined(ALPHA) float4 acc2 = ((float4)(acc20, acc21, acc22, acc23)); vstore4(acc2, 0, (__global float *)(offset(&dst, 0, 2))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 #if defined(ALPHA) acc30 = acc30 * ALPHA; acc31 = acc31 * ALPHA; acc32 = acc32 * ALPHA; acc33 = acc33 * ALPHA; #endif // defined(ALPHA) float4 acc3 = ((float4)(acc30, acc31, acc32, acc33)); vstore4(acc3, 0, (__global float *)(offset(&dst, 0, 3))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } /** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not been reshaped * * @note This OpenCL kernel works with the 32-bit floating point data type (float) and uses the fma units. * This OpenCL kernel is optimized for Bifrost when the number of matrix B columns is less or equal to 1000. * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y. * This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=2. * @note The number of matrix A columns must be passed at compile time using -DCOLS_A. * @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha if alpha!=1.0f. * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { // Requires 2 NUM_ELEMS_PROCESSED_PER_THREAD_X, C vect2, A vect4, B (2 vload2) // to fix for NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 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 * sizeof(float); // Address boundary for the matrix A int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(float)); // Initialize accumulators float acc00 = 0.0f; float acc01 = 0.0f; #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 float acc10 = 0.0f; float acc11 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 float acc20 = 0.0f; float acc21 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 float acc30 = 0.0f; float acc31 = 0.0f; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 // A and B src indices get incremented at the same time. for(; src_addr.s0 <= (end_row_vec_a - 4 * (int)sizeof(float)); src_addr += (int2)(4 * sizeof(float), 4 * src1_stride_y)) { // Load values from matrix A float4 a0 = vload4(0, (__global float *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); // Load values from matrix B float2 b0 = vload2(0, (__global float *)(src1_ptr + src_addr.s1 + 0 * src1_stride_y)); float2 b1 = vload2(0, (__global float *)(src1_ptr + src_addr.s1 + 1 * src1_stride_y)); float2 b2 = vload2(0, (__global float *)(src1_ptr + src_addr.s1 + 2 * src1_stride_y)); float2 b3 = vload2(0, (__global float *)(src1_ptr + src_addr.s1 + 3 * src1_stride_y)); // Multiply and accumulate acc00 = fma(a0.s0, b0.s0, acc00); acc00 = fma(a0.s1, b1.s0, acc00); acc00 = fma(a0.s2, b2.s0, acc00); acc00 = fma(a0.s3, b3.s0, acc00); acc01 = fma(a0.s0, b0.s1, acc01); acc01 = fma(a0.s1, b1.s1, acc01); acc01 = fma(a0.s2, b2.s1, acc01); acc01 = fma(a0.s3, b3.s1, acc01); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 a0 = vload4(0, (__global float *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y)); acc10 = fma(a0.s0, b0.s0, acc10); acc10 = fma(a0.s1, b1.s0, acc10); acc10 = fma(a0.s2, b2.s0, acc10); acc10 = fma(a0.s3, b3.s0, acc10); acc11 = fma(a0.s0, b0.s1, acc11); acc11 = fma(a0.s1, b1.s1, acc11); acc11 = fma(a0.s2, b2.s1, acc11); acc11 = fma(a0.s3, b3.s1, acc11); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 a0 = vload4(0, (__global float *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y)); acc20 = fma(a0.s0, b0.s0, acc20); acc20 = fma(a0.s1, b1.s0, acc20); acc20 = fma(a0.s2, b2.s0, acc20); acc20 = fma(a0.s3, b3.s0, acc20); acc21 = fma(a0.s0, b0.s1, acc21); acc21 = fma(a0.s1, b1.s1, acc21); acc21 = fma(a0.s2, b2.s1, acc21); acc21 = fma(a0.s3, b3.s1, acc21); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 a0 = vload4(0, (__global float *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); acc30 = fma(a0.s0, b0.s0, acc30); acc30 = fma(a0.s1, b1.s0, acc30); acc30 = fma(a0.s2, b2.s0, acc30); acc30 = fma(a0.s3, b3.s0, acc30); acc31 = fma(a0.s0, b0.s1, acc31); acc31 = fma(a0.s1, b1.s1, acc31); acc31 = fma(a0.s2, b2.s1, acc31); acc31 = fma(a0.s3, b3.s1, acc31); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // float size increment for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(4, src1_stride_y)) { // Load values from matrix A float a0 = *((__global float *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 float a1 = *((__global float *)(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 float a2 = *((__global float *)(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 float a3 = *((__global float *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 // Load values from matrix B float2 b0 = vload2(0, (__global float *)(src1_ptr + src_addr.s1)); // Multiply and accumulate acc00 = fma(a0, b0.s0, acc00); acc01 = fma(a0, b0.s1, acc01); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc10 = fma(a1, b0.s0, acc10); acc11 = fma(a1, b0.s1, acc11); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc20 = fma(a2, b0.s0, acc20); acc21 = fma(a2, b0.s1, acc21); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc30 = fma(a3, b0.s0, acc30); acc31 = fma(a3, b0.s1, acc31); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) acc00 = acc00 * ALPHA; acc01 = acc01 * ALPHA; #endif // defined(ALPHA) float2 acc0 = ((float2)(acc00, acc01)); vstore2(acc0, 0, (__global float *)(offset(&dst, 0, 0))); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if defined(ALPHA) acc10 = acc10 * ALPHA; acc11 = acc11 * ALPHA; #endif // defined(ALPHA) float2 acc1 = ((float2)(acc10, acc11)); vstore2(acc1, 0, (__global float *)(offset(&dst, 0, 1))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if defined(ALPHA) acc20 = acc20 * ALPHA; acc21 = acc21 * ALPHA; #endif // defined(ALPHA) float2 acc2 = ((float2)(acc20, acc21)); vstore2(acc2, 0, (__global float *)(offset(&dst, 0, 2))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 #if defined(ALPHA) acc30 = acc30 * ALPHA; acc31 = acc31 * ALPHA; #endif // defined(ALPHA) float2 acc3 = (float2)(acc30, acc31); vstore2(acc3, 0, (__global float *)(offset(&dst, 0, 3))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } #if defined(FIXED_POINT_POSITION) /** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped * * @note This OpenCL kernel works with fixed point data types QS8 * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y * @note The number matrix A columns, the number of elements processed per thread along the Y direction and the alpha's value need to be passed at compile time using -DCOLS_A, -DNUM_ELEMS_PROCESSED_PER_THREAD_Y and -DALPHA * @note The fixed point position need to be passed at compile time using -DFIXED_POINT_POSITION * @note The optional alpha value must be passed in 8 bit fixed point format using -DALPHA * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8/QS16 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_qs8(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { 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 * sizeof(char); int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(char)); short8 acc00 = 0; short8 acc01 = 0; #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 short8 acc10 = 0; short8 acc11 = 0; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 short8 acc20 = 0; short8 acc21 = 0; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 short8 acc30 = 0; short8 acc31 = 0; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 // This for loop performs 4 accumulations per iteration for(; src_addr.s0 <= (end_row_vec_a - 2); src_addr += (int2)(2, 2 * src1_stride_y)) { char2 a0 = vload2(0, (__global char *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 char2 a1 = vload2(0, (__global char *)(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 char2 a2 = vload2(0, (__global char *)(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 char2 a3 = vload2(0, (__global char *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 char16 b0 = vload16(0, (__global char *)(src1_ptr + src_addr.s1 + 0 * src1_stride_y)); char16 b1 = vload16(0, (__global char *)(src1_ptr + src_addr.s1 + 1 * src1_stride_y)); acc00 = mlal_sat_qs8x8(acc00, (char8)a0.s0, b0.s01234567, FIXED_POINT_POSITION); acc00 = mlal_sat_qs8x8(acc00, (char8)a0.s1, b1.s01234567, FIXED_POINT_POSITION); acc01 = mlal_sat_qs8x8(acc01, (char8)a0.s0, b0.s89ABCDEF, FIXED_POINT_POSITION); acc01 = mlal_sat_qs8x8(acc01, (char8)a0.s1, b1.s89ABCDEF, FIXED_POINT_POSITION); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc10 = mlal_sat_qs8x8(acc10, (char8)a1.s0, b0.s01234567, FIXED_POINT_POSITION); acc10 = mlal_sat_qs8x8(acc10, (char8)a1.s1, b1.s01234567, FIXED_POINT_POSITION); acc11 = mlal_sat_qs8x8(acc11, (char8)a1.s0, b0.s89ABCDEF, FIXED_POINT_POSITION); acc11 = mlal_sat_qs8x8(acc11, (char8)a1.s1, b1.s89ABCDEF, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc20 = mlal_sat_qs8x8(acc20, (char8)a2.s0, b0.s01234567, FIXED_POINT_POSITION); acc20 = mlal_sat_qs8x8(acc20, (char8)a2.s1, b1.s01234567, FIXED_POINT_POSITION); acc21 = mlal_sat_qs8x8(acc21, (char8)a2.s0, b0.s89ABCDEF, FIXED_POINT_POSITION); acc21 = mlal_sat_qs8x8(acc21, (char8)a2.s1, b1.s89ABCDEF, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc30 = mlal_sat_qs8x8(acc30, (char8)a3.s0, b0.s01234567, FIXED_POINT_POSITION); acc30 = mlal_sat_qs8x8(acc30, (char8)a3.s1, b1.s01234567, FIXED_POINT_POSITION); acc31 = mlal_sat_qs8x8(acc31, (char8)a3.s0, b0.s89ABCDEF, FIXED_POINT_POSITION); acc31 = mlal_sat_qs8x8(acc31, (char8)a3.s1, b1.s89ABCDEF, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // Left-over accumulations for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(1, src1_stride_y)) { char a0 = *((__global char *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 char a1 = *((__global char *)(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 char a2 = *((__global char *)(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 char a3 = *((__global char *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 char16 b0 = vload16(0, (__global char *)(src1_ptr + src_addr.s1)); acc00 = mlal_sat_qs8x8(acc00, (char8)a0, b0.s01234567, FIXED_POINT_POSITION); acc01 = mlal_sat_qs8x8(acc01, (char8)a0, b0.s89ABCDEF, FIXED_POINT_POSITION); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc10 = mlal_sat_qs8x8(acc10, (char8)a1, b0.s01234567, FIXED_POINT_POSITION); acc11 = mlal_sat_qs8x8(acc11, (char8)a1, b0.s89ABCDEF, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc20 = mlal_sat_qs8x8(acc20, (char8)a2, b0.s01234567, FIXED_POINT_POSITION); acc21 = mlal_sat_qs8x8(acc21, (char8)a2, b0.s89ABCDEF, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc30 = mlal_sat_qs8x8(acc30, (char8)a3, b0.s01234567, FIXED_POINT_POSITION); acc31 = mlal_sat_qs8x8(acc31, (char8)a3, b0.s89ABCDEF, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix product and store the result char16 acc_qs8; acc_qs8 = convert_char16_sat((short16)(acc00, acc01)); #if defined(ALPHA) acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 0))); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc_qs8 = convert_char16_sat((short16)(acc10, acc11)); #if defined(ALPHA) acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 1))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc_qs8 = convert_char16_sat((short16)(acc20, acc21)); #if defined(ALPHA) acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 2))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc_qs8 = convert_char16_sat((short16)(acc30, acc31)); #if defined(ALPHA) acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 3))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } /** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped * * @note This OpenCL kernel works with fixed point data types QS16 * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y * @note The number of matrix A columns, the number of elements processed per thread along the Y direction and the alpha's value need to be passed at compile time using -DCOLS_A, -DNUM_ELEMS_PROCESSED_PER_THREAD_Y and -DALPHA * @note The fixed point position need to be passed at compile time using -DFIXED_POINT_POSITION * @note The optional alpha value must be passed in 16 bit fixed point format using -DALPHA * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8/QS16 * @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 types: 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_mm_qs16(IMAGE_DECLARATION(src0), IMAGE_DECLARATION(src1), IMAGE_DECLARATION(dst)) { 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 * sizeof(short); int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(short)); int8 acc0 = 0; #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 int8 acc1 = 0; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 int8 acc2 = 0; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 int8 acc3 = 0; #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 // This for loop performs 4 accumulations per iteration for(; src_addr.s0 <= (end_row_vec_a - 2 * (int)sizeof(short)); src_addr += (int2)(2 * sizeof(short), 2 * src1_stride_y)) { short2 a0 = vload2(0, (__global short *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 short2 a1 = vload2(0, (__global short *)(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 short2 a2 = vload2(0, (__global short *)(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 short2 a3 = vload2(0, (__global short *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 short8 b0 = vload8(0, (__global short *)(src1_ptr + src_addr.s1 + 0 * src1_stride_y)); short8 b1 = vload8(0, (__global short *)(src1_ptr + src_addr.s1 + 1 * src1_stride_y)); acc0 = mlal_sat_qs16x8(acc0, (short8)a0.s0, b0, FIXED_POINT_POSITION); acc0 = mlal_sat_qs16x8(acc0, (short8)a0.s1, b1, FIXED_POINT_POSITION); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc1 = mlal_sat_qs16x8(acc1, (short8)a1.s0, b0, FIXED_POINT_POSITION); acc1 = mlal_sat_qs16x8(acc1, (short8)a1.s1, b1, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc2 = mlal_sat_qs16x8(acc2, (short8)a2.s0, b0, FIXED_POINT_POSITION); acc2 = mlal_sat_qs16x8(acc2, (short8)a2.s1, b1, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc3 = mlal_sat_qs16x8(acc3, (short8)a3.s0, b0, FIXED_POINT_POSITION); acc3 = mlal_sat_qs16x8(acc3, (short8)a3.s1, b1, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // Left-over accumulations for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(short), src1_stride_y)) { short a0 = *((__global short *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y)); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 short a1 = *((__global short *)(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 short a2 = *((__global short *)(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 short a3 = *((__global short *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y)); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 short8 b0 = vload8(0, (__global short *)(src1_ptr + src_addr.s1)); acc0 = mlal_sat_qs16x8(acc0, (short8)a0, b0, FIXED_POINT_POSITION); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc1 = mlal_sat_qs16x8(acc1, (short8)a1, b0, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc2 = mlal_sat_qs16x8(acc2, (short8)a2, b0, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc3 = mlal_sat_qs16x8(acc3, (short8)a3, b0, FIXED_POINT_POSITION); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Multiply by the weight of matrix product and store the result short8 acc_qs16; acc_qs16 = convert_short8_sat(acc0); #if defined(ALPHA) acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 0))); #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 acc_qs16 = convert_short8_sat(acc1); #if defined(ALPHA) acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 1))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 acc_qs16 = convert_short8_sat(acc2); #if defined(ALPHA) acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 2))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 acc_qs16 = convert_short8_sat(acc3); #if defined(ALPHA) acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION); #endif // defined(ALPHA) vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 3))); #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 } #endif // defined(FIXED_POINT_POSITION) #endif // defined(COLS_A) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && (NUM_ELEMS_PROCESSED_PER_THREAD_Y) #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: * * @attention 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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_ma_f32(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { // Compute source and destination addresses Image src = CONVERT_TO_IMAGE_STRUCT(src); Image dst = CONVERT_TO_IMAGE_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); } /** 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: * * @attention 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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_ma_f16(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { // Compute source and destination addresses Image src = CONVERT_TO_IMAGE_STRUCT(src); Image dst = CONVERT_TO_IMAGE_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); } #if defined(FIXED_POINT_POSITION) /** This OpenCL kernel performs the in-place matrix addition between 2 matrices in 8 bit fixed point taking into account that the second matrix might be weighted by a scalar value beta: * * @attention The beta's value and the fixed point position need to be passed at compile time using -DBETA and -DFIXED_POINT_POSITION * * @note: BETA must be passed in 8 bit fixed point format * * @param[in] src_ptr Pointer to the source matrix. Supported data types: QS8 * @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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_ma_qs8(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { // Compute source and destination addresses Image src = CONVERT_TO_IMAGE_STRUCT(src); Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Load values from A x B char16 alpha_ab = vload16(0, (__global char *)dst.ptr); // Load values from Matrix C char16 c = vload16(0, (__global char *)src.ptr); // Computes alpha * axb + beta * c char16 out = mla_sat_qs8x16(alpha_ab, (char16)BETA, c, FIXED_POINT_POSITION); // Store final result in axb matrix vstore16(out, 0, (__global char *)dst.ptr); } /** This OpenCL kernel performs the in-place matrix addition between 2 matrices in 16 bit fixed point taking into account that the second matrix might be weighted by a scalar value beta: * * @attention The beta's value and the fixed point position need to be passed at compile time using -DBETA and -DFIXED_POINT_POSITION * * @note: BETA must be passed in 16 bit fixed point format * * @param[in] src_ptr Pointer to the source matrix. Supported data types: QS16 * @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_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_ma_qs16(IMAGE_DECLARATION(src), IMAGE_DECLARATION(dst)) { // Compute source and destination addresses Image src = CONVERT_TO_IMAGE_STRUCT(src); Image dst = CONVERT_TO_IMAGE_STRUCT(dst); // Load values from A x B short8 alpha_ab = vload8(0, (__global short *)dst.ptr); // Load values from Matrix C short8 c = vload8(0, (__global short *)src.ptr); // Computes alpha * axb + beta * c short8 out = mla_sat_qs16x8(alpha_ab, (short8)BETA, c, FIXED_POINT_POSITION); // Store final result in axb matrix vstore8(out, 0, (__global short *)dst.ptr); } #endif // defined(FIXED_POINT_POSITION) #endif // defined(BETA) #if defined(WIDTH_VECTOR_A) /** This OpenCL kernel computes the vector by matrix multiplication between each row of A (src0) and matrix B (src1) used for locally connected layer * * @attention The width of A need to be passed at compile time using -DWIDTH_VECTOR_A * * @attention The input A and matrix B must not be reshaped * * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32 * @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 types: 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_stride_z Stride of the source matrix in Z dimension (in bytes) * @param[in] src1_step_z src_stride_z * number of elements along Z 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 types: same as @p src0_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_offset_first_element_in_bytes The offset of the first element in the destination matrix */ __kernel void gemm_lc_vm_f32(IMAGE_DECLARATION(src0), TENSOR3D_DECLARATION(src1), IMAGE_DECLARATION(dst)) { int idx = get_global_id(0) * 4; int idy = get_global_id(1); // Compute the address for the vector A and matrix B int2 src_addr = ((int2)(src0_offset_first_element_in_bytes + src0_stride_y * idy, src1_offset_first_element_in_bytes + src1_stride_z * idy)); src_addr.s1 += idx * sizeof(float); int end_row_vec_a = src_addr.s0 + (WIDTH_VECTOR_A * sizeof(float)); float4 acc = 0.0f; for(; src_addr.s0 <= (end_row_vec_a - 2 * (int)sizeof(float)); src_addr += (int2)(2 * sizeof(float), 2 * src1_stride_y)) { float2 a0 = vload2(0, (__global float *)(src0_ptr + src_addr.s0)); float4 b0 = vload4(0, (__global float *)(src1_ptr + src_addr.s1)); float4 b1 = vload4(0, (__global float *)(src1_ptr + src_addr.s1 + src1_stride_y)); acc += b0 * (float4)a0.s0; acc += b1 * (float4)a0.s1; } for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(float), src1_stride_y)) { float a0 = *((__global float *)(src0_ptr + src_addr.s0)); float4 b0 = vload4(0, (__global float *)(src1_ptr + src_addr.s1)); acc += b0 * (float4)a0; } // Compute destination address Image dst = CONVERT_TO_IMAGE_STRUCT(dst); vstore4(acc, 0, (__global float *)(offset(&dst, 0, 0))); } #endif // defined(WIDTH_VECTOR_A) /** This kernel accumulates each row with the biases vector. * * @note The data type must be passed at compile time using -DDATA_TYPE e.g. -DDATA_TYPE=short. * @note The vector size must be passed at compile time using -DVECTOR_SIZE e.g. -DVECTOR_SIZE=16. * * @param[in, out] accum_ptr Pointer to the accumulate tensor. Supported data type: U8/S8/QS8/U16/S16/F16/U32/S32/F32 * @param[in] accum_stride_x Stride of the accmulate tensor in X dimension (in bytes) * @param[in] accum_step_x accum_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] accum_stride_y Stride of the accumlulate tensor in Y dimension (in bytes) * @param[in] accum_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] accum_offset_first_element_in_bytes The offset of the first element in the accumulate tensor * @param[in] biases_ptr Pointer to the biases vector. Same as @p accum_ptr * @param[in] biases_stride_x Stride of the destination tensor in X dimension (in bytes) * @param[in] biases_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] biases_offset_first_element_in_bytes The offset of the first element in the destination tensor */ #if defined(DATA_TYPE) && defined(VECTOR_SIZE) __kernel void gemm_accumulate_biases( IMAGE_DECLARATION(accum), VECTOR_DECLARATION(biases)) { Image accum = CONVERT_TO_IMAGE_STRUCT(accum); Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); // Vector size, i.e. number of vector elements. VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) accum_value = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)accum.ptr); VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) biases_value = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)biases.ptr); #ifdef FIXED_POINT_POSITION accum_value = ADD_SAT_OP_EXPAND(biases_value, accum_value, DATA_TYPE, VECTOR_SIZE); #else // FIXED_POINT_POSITION accum_value = biases_value + accum_value; #endif // FIXED_POINT_POSITION // Store result in the accumulate buffer VSTORE(VECTOR_SIZE) (accum_value, 0, (__global DATA_TYPE *)accum.ptr); } #endif // defined(DATA_TYPE) && defined(VECTOR_SIZE)