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Commit 31a78143 authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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used new device layer for cv::gpu::countNonZero

parent 020624c4
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Showing with 35 additions and 159 deletions
modules/cudaarithm/src/cuda/countnonzero.cu
View file @ 31a78143
......@@ -40,137 +40,57 @@
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/opencv_modules.hpp"
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/reduce.hpp"
#include "opencv2/core/cuda/emulation.hpp"
#ifndef HAVE_OPENCV_CUDEV
using namespace cv::cuda;
using namespace cv::cuda::device;
#error "opencv_cudev is required"
namespace countNonZero
{
__device__ unsigned int blocks_finished = 0;
template <int BLOCK_SIZE, typename T>
__global__ void kernel(const PtrStepSz<T> src, unsigned int* count, const int twidth, const int theight)
{
__shared__ unsigned int scount[BLOCK_SIZE];
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
unsigned int mycount = 0;
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
{
const T* ptr = src.ptr(y);
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
{
const T srcVal = ptr[x];
mycount += (srcVal != 0);
}
}
device::reduce<BLOCK_SIZE>(scount, mycount, tid, plus<unsigned int>());
#if __CUDA_ARCH__ >= 200
if (tid == 0)
::atomicAdd(count, mycount);
#else
__shared__ bool is_last;
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
if (tid == 0)
{
count[bid] = mycount;
__threadfence();
unsigned int ticket = ::atomicInc(&blocks_finished, gridDim.x * gridDim.y);
is_last = (ticket == gridDim.x * gridDim.y - 1);
}
__syncthreads();
if (is_last)
{
mycount = tid < gridDim.x * gridDim.y ? count[tid] : 0;
#else
device::reduce<BLOCK_SIZE>(scount, mycount, tid, plus<unsigned int>());
#include "opencv2/cudaarithm.hpp"
#include "opencv2/cudev.hpp"
if (tid == 0)
{
count[0] = mycount;
using namespace cv::cudev;
blocks_finished = 0;
}
}
#endif
}
const int threads_x = 32;
const int threads_y = 8;
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
namespace
{
template <typename T>
int countNonZeroImpl(const GpuMat& _src, GpuMat& _buf)
{
block = dim3(threads_x, threads_y);
grid = dim3(divUp(cols, block.x * block.y),
divUp(rows, block.y * block.x));
const GpuMat_<T>& src = (const GpuMat_<T>&) _src;
GpuMat_<int>& buf = (GpuMat_<int>&) _buf;
grid.x = ::min(grid.x, block.x);
grid.y = ::min(grid.y, block.y);
}
gridCountNonZero(src, buf);
void getBufSize(int cols, int rows, int& bufcols, int& bufrows)
{
dim3 block, grid;
getLaunchCfg(cols, rows, block, grid);
int data;
buf.download(cv::Mat(1, 1, buf.type(), &data));
bufcols = grid.x * grid.y * sizeof(int);
bufrows = 1;
return data;
}
}
template <typename T>
int run(const PtrStepSzb src, PtrStep<unsigned int> buf)
int cv::cuda::countNonZero(InputArray _src, GpuMat& buf)
{
typedef int (*func_t)(const GpuMat& _src, GpuMat& _buf);
static const func_t funcs[] =
{
dim3 block, grid;
getLaunchCfg(src.cols, src.rows, block, grid);
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
const int theight = divUp(divUp(src.rows, grid.y), block.y);
countNonZeroImpl<uchar>,
countNonZeroImpl<schar>,
countNonZeroImpl<ushort>,
countNonZeroImpl<short>,
countNonZeroImpl<int>,
countNonZeroImpl<float>,
countNonZeroImpl<double>
};
unsigned int* count_buf = buf.ptr(0);
GpuMat src = _src.getGpuMat();
cudaSafeCall( cudaMemset(count_buf, 0, sizeof(unsigned int)) );
CV_Assert( src.channels() == 1 );
kernel<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, count_buf, twidth, theight);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
unsigned int count;
cudaSafeCall(cudaMemcpy(&count, count_buf, sizeof(unsigned int), cudaMemcpyDeviceToHost));
return count;
}
const func_t func = funcs[src.depth()];
template int run<uchar >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<schar >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<ushort>(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<short >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<int >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<float >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<double>(const PtrStepSzb src, PtrStep<unsigned int> buf);
return func(src, buf);
}
#endif // CUDA_DISABLER
#endif
modules/cudaarithm/src/reductions.cpp
View file @ 31a78143
......@@ -186,50 +186,6 @@ double cv::cuda::norm(InputArray _src1, InputArray _src2, GpuMat& buf, int normT
return retVal;
}
//////////////////////////////////////////////////////////////////////////////
// countNonZero
namespace countNonZero
{
void getBufSize(int cols, int rows, int& bufcols, int& bufrows);
template <typename T>
int run(const PtrStepSzb src, PtrStep<unsigned int> buf);
}
int cv::cuda::countNonZero(InputArray _src, GpuMat& buf)
{
GpuMat src = _src.getGpuMat();
typedef int (*func_t)(const PtrStepSzb src, PtrStep<unsigned int> buf);
static const func_t funcs[] =
{
::countNonZero::run<uchar>,
::countNonZero::run<schar>,
::countNonZero::run<ushort>,
::countNonZero::run<short>,
::countNonZero::run<int>,
::countNonZero::run<float>,
::countNonZero::run<double>
};
CV_Assert(src.channels() == 1);
if (src.depth() == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
Size buf_size;
::countNonZero::getBufSize(src.cols, src.rows, buf_size.width, buf_size.height);
ensureSizeIsEnough(buf_size, CV_8U, buf);
const func_t func = funcs[src.depth()];
return func(src, buf);
}
//////////////////////////////////////////////////////////////////////////////
// reduce
......
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