/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2017, Intel Corporation, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #define CONCAT(A,B) A##_##B #define TEMPLATE(name,type) CONCAT(name,type) #define Dtype float __kernel void TEMPLATE(matvec_mul4,Dtype)( __global const float * A, int offA, unsigned int A_col_size, unsigned int trail_item, __global const float * v, int offv, float alpha, float beta, __global float4 * result, int offr, __local float4 * work) { unsigned int row_gid = get_group_id(0); unsigned int lid = get_local_id(0); const __global float *src0_read = A + row_gid * 4 * A_col_size + offA; const __global float *src1_read = v + offv; result = (__global float4*)((__global float*)result + offr); float4 dot0 = (float4)(0.f); float4 dot1 = (float4)(0.f); float4 dot2 = (float4)(0.f); float4 dot3 = (float4)(0.f); unsigned int i = lid; while( i < A_col_size / 4) { const float4 a0 = vload4(i, src0_read); const float4 a1 = vload4(i, src0_read + A_col_size); const float4 a2 = vload4(i, src0_read + 2 * A_col_size); const float4 a3 = vload4(i, src0_read + 3 * A_col_size); const float4 b0 = vload4(i, src1_read); dot0 += a0 * b0; dot1 += a1 * b0; dot2 += a2 * b0; dot3 += a3 * b0; i += get_local_size(0); } work[lid].s0 = dot0.x + dot0.y + dot0.z + dot0.w; work[lid].s1 = dot1.x + dot1.y + dot1.z + dot1.w; work[lid].s2 = dot2.x + dot2.y + dot2.z + dot2.w; work[lid].s3 = dot3.x + dot3.y + dot3.z + dot3.w; if(i == A_col_size / 4) { if(trail_item != 0) { const __global float *src0_trail = src0_read + i * 4; const __global float *src1_trail = src1_read + i * 4; for(unsigned int i = 0; i < trail_item; ++i) { const float at0 = src0_trail[i]; const float at1 = src0_trail[i + A_col_size]; const float at2 = src0_trail[i + 2 * A_col_size]; const float at3 = src0_trail[i + 3 * A_col_size]; const float bt = src1_trail[i]; work[lid].s0 += at0 * bt; work[lid].s1 += at1 * bt; work[lid].s2 += at2 * bt; work[lid].s3 += at3 * bt; } } } for(unsigned int stride=get_local_size(0)/2 ; stride>0 ; stride>>=1) { barrier(CLK_LOCAL_MEM_FENCE); if(lid < stride) work[lid] += work[lid+stride]; } if(lid == 0) { if(beta == (Dtype)0) result[row_gid] = alpha * work[0]; else result[row_gid] = alpha * work[0] + beta * result[row_gid]; } } /* This kernel used for the trailing rows when row_of_A %4 !=0 */ __kernel void TEMPLATE(matvec_mul1,Dtype)( __global const float * A, int offA, unsigned int A_col_size, unsigned int row_offset, unsigned int trail_item, __global const float * v, int offv, float alpha, float beta, __global float * result, int offr, __local float * work) { unsigned int row_gid = get_group_id(0); unsigned int lid = get_local_id(0); const __global float *src0_read = A + (row_offset + row_gid) * A_col_size + offA; const __global float *src1_read = v + + offv; result = result + offr; float4 dot0 = (float4)(0.f); unsigned int i = lid; while( i < A_col_size / 4) { const float4 a0 = vload4(i, src0_read); const float4 b0 = vload4(i, src1_read); dot0 += a0 * b0; i += get_local_size(0); } work[lid] = dot0.x + dot0.y + dot0.z + dot0.w; if(i == A_col_size / 4) { if(trail_item != 0) { const __global float *src0_trail = src0_read + i * 4; const __global float *src1_trail = src1_read + i * 4; for(unsigned int i = 0; i < trail_item; ++i) { const float at0 = src0_trail[i]; const float bt = src1_trail[i]; work[lid] += at0 * bt; } } } for(unsigned int stride=get_local_size(0)/2 ; stride>0 ; stride>>=1) { barrier(CLK_LOCAL_MEM_FENCE); if(lid < stride) work[lid] += work[lid+stride]; } if(lid == 0) { if(beta == (Dtype)0) { result[row_gid+row_offset] = alpha * work[0]; } else { result[row_gid+row_offset] *= beta; result[row_gid+row_offset] += alpha * work[0]; } } }