Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

Merge pull request #3159 from ElenaGvozdeva:ocl_gemm

Browse Source
pull/3373/head
Alexander Alekhin 10 years ago
parent 4a9cfbf806 d88fdd0378
commit efebd83bc8
2 changed files with 197 additions and 2 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 87
      modules/core/src/matmul.cpp
  2. 112
      modules/core/src/opencl/gemm.cl

87
modules/core/src/matmul.cpp
Unescape View File

@ -693,7 +693,7 @@ static void GEMMStore_64fc( const Complexd* c_data, size_t c_step,
#ifdef HAVE_CLAMDBLAS
static bool ocl_gemm( InputArray matA, InputArray matB, double alpha,
static bool ocl_gemm_amdblas( InputArray matA, InputArray matB, double alpha,
InputArray matC, double beta, OutputArray matD, int flags )
{
int type = matA.type(), esz = CV_ELEM_SIZE(type);
@ -775,6 +775,84 @@ static bool ocl_gemm( InputArray matA, InputArray matB, double alpha,
#endif
#ifdef HAVE_OPENCL
static bool ocl_gemm( InputArray matA, InputArray matB, double alpha,
InputArray matC, double beta, OutputArray matD, int flags )
{
int depth = matA.depth(), cn = matA.channels();
int type = CV_MAKETYPE(depth, cn);
CV_Assert( type == matB.type() && (type == CV_32FC1 || type == CV_64FC1 || type == CV_32FC2 || type == CV_64FC2) );
const ocl::Device & dev = ocl::Device::getDefault();
bool doubleSupport = dev.doubleFPConfig() > 0;
if (!doubleSupport && depth == CV_64F)
return false;
bool haveC = matC.kind() != cv::_InputArray::NONE;
Size sizeA = matA.size(), sizeB = matB.size(), sizeC = haveC ? matC.size() : Size(0, 0);
bool atrans = (flags & GEMM_1_T) != 0, btrans = (flags & GEMM_2_T) != 0, ctrans = (flags & GEMM_3_T) != 0;
if (atrans)
sizeA = Size(sizeA.height, sizeA.width);
if (btrans)
sizeB = Size(sizeB.height, sizeB.width);
if (haveC && ctrans)
sizeC = Size(sizeC.height, sizeC.width);
Size sizeD(sizeB.width, sizeA.height);
CV_Assert( !haveC || matC.type() == type );
CV_Assert( sizeA.width == sizeB.height && (!haveC || sizeC == sizeD) );
int max_wg_size = (int)dev.maxWorkGroupSize();
int block_size = (max_wg_size / (32*cn) < 32) ? (max_wg_size / (16*cn) < 16) ? (max_wg_size / (8*cn) < 8) ? 1 : 8 : 16 : 32;
matD.create(sizeD, type);
UMat A = matA.getUMat(), B = matB.getUMat(), D = matD.getUMat();
if (atrans)
A = A.t();
if (btrans)
B = B.t();
if (haveC)
ctrans ? transpose(matC, D) : matC.copyTo(D);
int vectorWidths[] = { 4, 4, 2, 2, 1, 4, cn, -1 };
int kercn = ocl::checkOptimalVectorWidth(vectorWidths, B, D);
String opts = format("-D T=%s -D T1=%s -D WT=%s -D cn=%d -D kercn=%d -D LOCAL_SIZE=%d %s %s %s",
ocl::typeToStr(type), ocl::typeToStr(depth), ocl::typeToStr(CV_MAKETYPE(depth, kercn)),
cn, kercn, block_size,
(sizeA.width % block_size !=0) ? "-D NO_MULT" : "",
haveC ? "-D HAVE_C" : "",
doubleSupport ? " -D DOUBLE_SUPPORT" : "");
ocl::Kernel k("gemm", cv::ocl::core::gemm_oclsrc, opts);
if (k.empty())
return false;
if (depth == CV_64F)
k.args(ocl::KernelArg::ReadOnlyNoSize(A),
ocl::KernelArg::ReadOnlyNoSize(B, cn, kercn),
ocl::KernelArg::ReadWrite(D, cn, kercn),
sizeA.width, alpha, beta);
else
k.args(ocl::KernelArg::ReadOnlyNoSize(A),
ocl::KernelArg::ReadOnlyNoSize(B, cn, kercn),
ocl::KernelArg::ReadWrite(D, cn, kercn),
sizeA.width, (float)alpha, (float)beta);
size_t globalsize[2] = { sizeD.width * cn / kercn, sizeD.height};
size_t localsize[2] = { block_size, block_size};
return k.run(2, globalsize, block_size!=1 ? localsize : NULL, false);
}
#endif
}
void cv::gemm( InputArray matA, InputArray matB, double alpha,
@ -783,7 +861,12 @@ void cv::gemm( InputArray matA, InputArray matB, double alpha,
#ifdef HAVE_CLAMDBLAS
CV_OCL_RUN(ocl::haveAmdBlas() && matA.dims() <= 2 && matB.dims() <= 2 && matC.dims() <= 2 && _matD.isUMat() &&
matA.cols() > 20 && matA.rows() > 20 && matB.cols() > 20, // since it works incorrect for small sizes
ocl_gemm(matA, matB, alpha, matC, beta, _matD, flags))
ocl_gemm_amdblas(matA, matB, alpha, matC, beta, _matD, flags))
#endif
#ifdef HAVE_OPENCL
CV_OCL_RUN(_matD.isUMat() && matA.dims() <= 2 && matB.dims() <= 2 && matC.dims() <= 2,
ocl_gemm(matA, matB, alpha, matC, beta, _matD, flags))
#endif
const int block_lin_size = 128;

112
modules/core/src/opencl/gemm.cl
Unescape View File

@ -0,0 +1,112 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
// Copyright (C) 2014, Itseez, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
#ifdef DOUBLE_SUPPORT
#ifdef cl_amd_fp64
#pragma OPENCL EXTENSION cl_amd_fp64:enable
#elif defined (cl_khr_fp64)
#pragma OPENCL EXTENSION cl_khr_fp64:enable
#endif
#endif
#define TSIZE (int)sizeof(T)
#define WTSIZE (int)sizeof(WT)
#define IND_A mad24(y, A_step, A_offset)
#define IND_B mad24(x, WTSIZE, B_offset)
#define STEP_B B_step / WTSIZE
#define LOCAL_SIZE_ODD (LOCAL_SIZE + 1)
#if cn==2
#if kercn==2
#define MUL(a, b)\
{\
sum.x += fma(a.x, b.x, - a.y * b.y);\
sum.y += fma(a.x, b.y, a.y * b.x);\
}
#else
#define MUL(a, b)\
{\
sum.x += fma(a.x, b.x, - a.y * b.y);\
sum.y += fma(a.x, b.y, a.y * b.x);\
sum.z += fma(a.x, b.z, - a.y * b.w);\
sum.w += fma(a.x, b.w, a.y * b.z);\
}
#endif
#else
#define MUL(a, b) sum = fma(a, b, sum);
#endif
__kernel void gemm(__global const uchar * A_ptr, int A_step, int A_offset,
__global const uchar * B_ptr, int B_step, int B_offset,
__global uchar * D_ptr, int D_step, int D_offset, int D_rows, int D_cols,
int n, T1 alpha, T1 beta)
{
int x = get_global_id(0);
int y = get_global_id(1);
int lidx = get_local_id(0);
int lidy = get_local_id(1);
__global const T* A = (__global const T*)(A_ptr + IND_A);
__global const WT* B = (__global const WT*)(B_ptr + IND_B);
WT sum = (WT)(0);
#if LOCAL_SIZE == 1
if (x < D_cols && y < D_rows)
{
for (int i = 0; i < n; ++i)
MUL(A[i], B[i*STEP_B]);
#else
__local T a_local[LOCAL_SIZE_ODD*LOCAL_SIZE];
__local WT b_local[LOCAL_SIZE_ODD*LOCAL_SIZE];
int reps;
#if NO_MULT
reps = (n + LOCAL_SIZE-1)/LOCAL_SIZE;
#else
reps = n/LOCAL_SIZE;
#endif
for (int p = 0; p < reps; ++p)
{
if (p * LOCAL_SIZE + lidx < n && y < D_rows)
a_local[mad24(lidy, LOCAL_SIZE_ODD, lidx)] = A[mad24(p, LOCAL_SIZE, lidx)];
if (p * LOCAL_SIZE + lidy < n && x < D_cols)
b_local[mad24(lidy, LOCAL_SIZE_ODD, lidx)] = B[mad24(p, LOCAL_SIZE, lidy)*STEP_B];
barrier(CLK_LOCAL_MEM_FENCE);
if (x < D_cols && y < D_rows)
{
#if NO_MULT
int ie = min(LOCAL_SIZE, n - p * LOCAL_SIZE);
for (int i = 0; i < ie; ++i)
#else
for (int i = 0; i < LOCAL_SIZE; ++i)
#endif
MUL(a_local[mad24(lidy, LOCAL_SIZE_ODD, i)], b_local[mad24(i, LOCAL_SIZE_ODD, lidx)]);
}
barrier(CLK_LOCAL_MEM_FENCE);
}
if (x < D_cols && y < D_rows)
{
#endif
__global WT* D = (__global WT*)(D_ptr + mad24(y, D_step, mad24(x, WTSIZE, D_offset)));
#if HAVE_C
D[0] = mad(alpha, sum, D[0]*beta);
#else
D[0] = alpha * sum;
#endif
}
}
Write Preview
Loading…
Cancel
Save