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Commit 85601e03 authored by Aaron Denney's avatar Aaron Denney
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remove constant memory use in compute_data_cost

parent 52516085
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Showing with 20 additions and 23 deletions
modules/cudastereo/src/cuda/stereocsbp.cu
View file @ 85601e03
......@@ -362,7 +362,7 @@ namespace cv { namespace cuda { namespace device
///////////////////////////////////////////////////////////////
template <typename T, int channels>
__global__ void compute_data_cost(const uchar *cleft, const uchar *cright, size_t cimg_step, const T* selected_disp_pyr, T* data_cost_, int h, int w, int level, int nr_plane, float data_weight, float max_data_term, int min_disp)
__global__ void compute_data_cost(const uchar *cleft, const uchar *cright, size_t cimg_step, const T* selected_disp_pyr, T* data_cost_, int h, int w, int level, int nr_plane, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step1, size_t disp_step2)
{
int x = blockIdx.x * blockDim.x + threadIdx.x;
int y = blockIdx.y * blockDim.y + threadIdx.y;
......@@ -375,8 +375,8 @@ namespace cv { namespace cuda { namespace device
int x0 = x << level;
int xt = (x + 1) << level;
const T* selected_disparity = selected_disp_pyr + y/2 * cmsg_step + x/2;
T* data_cost = data_cost_ + y * cmsg_step + x;
const T* selected_disparity = selected_disp_pyr + y/2 * msg_step + x/2;
T* data_cost = data_cost_ + y * msg_step + x;
for(int d = 0; d < nr_plane; d++)
{
......@@ -385,7 +385,7 @@ namespace cv { namespace cuda { namespace device
{
for(int xi = x0; xi < xt; xi++)
{
int sel_disp = selected_disparity[d * cdisp_step2];
int sel_disp = selected_disparity[d * disp_step2];
int xr = xi - sel_disp;
if (xr < 0 || sel_disp < min_disp)
......@@ -399,13 +399,13 @@ namespace cv { namespace cuda { namespace device
}
}
}
data_cost[cdisp_step1 * d] = saturate_cast<T>(val);
data_cost[disp_step1 * d] = saturate_cast<T>(val);
}
}
}
template <typename T, int winsz, int channels>
__global__ void compute_data_cost_reduce(const uchar *cleft, const uchar *cright, size_t cimg_step, const T* selected_disp_pyr, T* data_cost_, int level, int rows, int cols, int h, int nr_plane, float data_weight, float max_data_term, int min_disp)
__global__ void compute_data_cost_reduce(const uchar *cleft, const uchar *cright, size_t cimg_step, const T* selected_disp_pyr, T* data_cost_, int level, int rows, int cols, int h, int nr_plane, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step1, size_t disp_step2)
{
int x_out = blockIdx.x;
int y_out = blockIdx.y % h;
......@@ -413,12 +413,12 @@ namespace cv { namespace cuda { namespace device
int tid = threadIdx.x;
const T* selected_disparity = selected_disp_pyr + y_out/2 * cmsg_step + x_out/2;
T* data_cost = data_cost_ + y_out * cmsg_step + x_out;
const T* selected_disparity = selected_disp_pyr + y_out/2 * msg_step + x_out/2;
T* data_cost = data_cost_ + y_out * msg_step + x_out;
if (d < nr_plane)
{
int sel_disp = selected_disparity[d * cdisp_step2];
int sel_disp = selected_disparity[d * disp_step2];
int x0 = x_out << level;
int y0 = y_out << level;
......@@ -450,13 +450,13 @@ namespace cv { namespace cuda { namespace device
reduce<winsz>(smem + winsz * threadIdx.z, val, tid, plus<float>());
if (tid == 0)
data_cost[cdisp_step1 * d] = saturate_cast<T>(val);
data_cost[disp_step1 * d] = saturate_cast<T>(val);
}
}
template <typename T>
void compute_data_cost_caller_(const uchar *cleft, const uchar *cright, size_t cimg_step, const T* disp_selected_pyr, T* data_cost, int /*rows*/, int /*cols*/,
int h, int w, int level, int nr_plane, int channels, float data_weight, float max_data_term, int min_disp, cudaStream_t stream)
int h, int w, int level, int nr_plane, int channels, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step1, size_t disp_step2, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
......@@ -466,16 +466,16 @@ namespace cv { namespace cuda { namespace device
switch(channels)
{
case 1: compute_data_cost<T, 1><<<grid, threads, 0, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, h, w, level, nr_plane, data_weight, max_data_term, min_disp); break;
case 3: compute_data_cost<T, 3><<<grid, threads, 0, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, h, w, level, nr_plane, data_weight, max_data_term, min_disp); break;
case 4: compute_data_cost<T, 4><<<grid, threads, 0, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, h, w, level, nr_plane, data_weight, max_data_term, min_disp); break;
case 1: compute_data_cost<T, 1><<<grid, threads, 0, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, h, w, level, nr_plane, data_weight, max_data_term, min_disp, msg_step, disp_step1, disp_step2); break;
case 3: compute_data_cost<T, 3><<<grid, threads, 0, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, h, w, level, nr_plane, data_weight, max_data_term, min_disp, msg_step, disp_step1, disp_step2); break;
case 4: compute_data_cost<T, 4><<<grid, threads, 0, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, h, w, level, nr_plane, data_weight, max_data_term, min_disp, msg_step, disp_step1, disp_step2); break;
default: CV_Error(cv::Error::BadNumChannels, "Unsupported channels count");
}
}
template <typename T, int winsz>
void compute_data_cost_reduce_caller_(const uchar *cleft, const uchar *cright, size_t cimg_step, const T* disp_selected_pyr, T* data_cost, int rows, int cols,
int h, int w, int level, int nr_plane, int channels, float data_weight, float max_data_term, int min_disp, cudaStream_t stream)
int h, int w, int level, int nr_plane, int channels, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step1, size_t disp_step2, cudaStream_t stream)
{
const int threadsNum = 256;
const size_t smem_size = threadsNum * sizeof(float);
......@@ -486,9 +486,9 @@ namespace cv { namespace cuda { namespace device
switch (channels)
{
case 1: compute_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane, data_weight, max_data_term, min_disp); break;
case 3: compute_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane, data_weight, max_data_term, min_disp); break;
case 4: compute_data_cost_reduce<T, winsz, 4><<<grid, threads, smem_size, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane, data_weight, max_data_term, min_disp); break;
case 1: compute_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane, data_weight, max_data_term, min_disp, msg_step, disp_step1, disp_step2); break;
case 3: compute_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane, data_weight, max_data_term, min_disp, msg_step, disp_step1, disp_step2); break;
case 4: compute_data_cost_reduce<T, winsz, 4><<<grid, threads, smem_size, stream>>>(cleft, cright, cimg_step, disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane, data_weight, max_data_term, min_disp, msg_step, disp_step1, disp_step2); break;
default: CV_Error(cv::Error::BadNumChannels, "Unsupported channels count");
}
}
......@@ -499,7 +499,7 @@ namespace cv { namespace cuda { namespace device
int min_disp, cudaStream_t stream)
{
typedef void (*ComputeDataCostCaller)(const uchar *cleft, const uchar *cright, size_t cimg_step, const T* disp_selected_pyr, T* data_cost, int rows, int cols,
int h, int w, int level, int nr_plane, int channels, float data_weight, float max_data_term, int min_disp, cudaStream_t stream);
int h, int w, int level, int nr_plane, int channels, float data_weight, float max_data_term, int min_disp, size_t msg_step, size_t disp_step1, size_t disp_step2, cudaStream_t stream);
static const ComputeDataCostCaller callers[] =
{
......@@ -510,11 +510,8 @@ namespace cv { namespace cuda { namespace device
size_t disp_step1 = msg_step * h;
size_t disp_step2 = msg_step * h2;
cudaSafeCall( cudaMemcpyToSymbol(cdisp_step1, &disp_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(cdisp_step2, &disp_step2, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(cmsg_step, &msg_step, sizeof(size_t)) );
callers[level](cleft, cright, cimg_step, disp_selected_pyr, data_cost, rows, cols, h, w, level, nr_plane, channels, data_weight, max_data_term, min_disp, stream);
callers[level](cleft, cright, cimg_step, disp_selected_pyr, data_cost, rows, cols, h, w, level, nr_plane, channels, data_weight, max_data_term, min_disp, msg_step, disp_step1, disp_step2, stream);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
......
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