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implemented asynchronous call for StereoBeliefPropagation_GPU

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This commit is contained in:
Vladislav Vinogradov
2010-07-29 07:20:35 +00:00
parent 70a2c8f50a
commit 84f51332dd
3 changed files with 138 additions and 49 deletions
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79
modules/gpu/src/cuda/beliefpropagation.cu
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@@ -108,7 +108,7 @@ namespace cv { namespace gpu { namespace impl {
cudaSafeCall( cudaMemcpyToSymbol(beliefpropagation_gpu::clambda, &lambda, sizeof(lambda)) );
}
extern "C" void comp_data_caller(const DevMem2D& l, const DevMem2D& r, DevMem2D_<float> mdata)
extern "C" void comp_data_caller(const DevMem2D& l, const DevMem2D& r, DevMem2D_<float> mdata, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@@ -116,8 +116,15 @@ namespace cv { namespace gpu { namespace impl {
grid.x = divUp(l.cols, threads.x);
grid.y = divUp(l.rows, threads.y);
beliefpropagation_gpu::comp_data_kernel<<<grid, threads>>>(l.ptr, r.ptr, l.step, mdata.ptr, mdata.step/sizeof(float), l.cols, l.rows);
cudaSafeCall( cudaThreadSynchronize() );
if (stream == 0)
{
beliefpropagation_gpu::comp_data_kernel<<<grid, threads>>>(l.ptr, r.ptr, l.step, mdata.ptr, mdata.step/sizeof(float), l.cols, l.rows);
//cudaSafeCall( cudaThreadSynchronize() );
}
else
{
beliefpropagation_gpu::comp_data_kernel<<<grid, threads, 0, stream>>>(l.ptr, r.ptr, l.step, mdata.ptr, mdata.step/sizeof(float), l.cols, l.rows);
}
}
}}}
@@ -151,7 +158,7 @@ namespace beliefpropagation_gpu
}
namespace cv { namespace gpu { namespace impl {
extern "C" void data_down_kernel_caller(int dst_cols, int dst_rows, int src_rows, const DevMem2D_<float>& src, DevMem2D_<float> dst)
extern "C" void data_down_kernel_caller(int dst_cols, int dst_rows, int src_rows, const DevMem2D_<float>& src, DevMem2D_<float> dst, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@@ -159,8 +166,15 @@ namespace cv { namespace gpu { namespace impl {
grid.x = divUp(dst_cols, threads.x);
grid.y = divUp(dst_rows, threads.y);
beliefpropagation_gpu::data_down_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, src.ptr, src.step/sizeof(float), dst.ptr, dst.step/sizeof(float));
cudaSafeCall( cudaThreadSynchronize() );
if (stream == 0)
{
beliefpropagation_gpu::data_down_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, src.ptr, src.step/sizeof(float), dst.ptr, dst.step/sizeof(float));
//cudaSafeCall( cudaThreadSynchronize() );
}
else
{
beliefpropagation_gpu::data_down_kernel<<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, src.ptr, src.step/sizeof(float), dst.ptr, dst.step/sizeof(float));
}
}
}}}
@@ -191,7 +205,7 @@ namespace beliefpropagation_gpu
}
namespace cv { namespace gpu { namespace impl {
extern "C" void level_up(int dst_idx, int dst_cols, int dst_rows, int src_rows, DevMem2D_<float>* mu, DevMem2D_<float>* md, DevMem2D_<float>* ml, DevMem2D_<float>* mr)
extern "C" void level_up(int dst_idx, int dst_cols, int dst_rows, int src_rows, DevMem2D_<float>* mu, DevMem2D_<float>* md, DevMem2D_<float>* ml, DevMem2D_<float>* mr, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@@ -201,12 +215,21 @@ namespace cv { namespace gpu { namespace impl {
int src_idx = (dst_idx + 1) & 1;
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, mu[src_idx].ptr, mu[src_idx].step/sizeof(float), mu[dst_idx].ptr, mu[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, md[src_idx].ptr, md[src_idx].step/sizeof(float), md[dst_idx].ptr, md[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, ml[src_idx].ptr, ml[src_idx].step/sizeof(float), ml[dst_idx].ptr, ml[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, mr[src_idx].ptr, mr[src_idx].step/sizeof(float), mr[dst_idx].ptr, mr[dst_idx].step/sizeof(float));
cudaSafeCall( cudaThreadSynchronize() );
if (stream == 0)
{
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, mu[src_idx].ptr, mu[src_idx].step/sizeof(float), mu[dst_idx].ptr, mu[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, md[src_idx].ptr, md[src_idx].step/sizeof(float), md[dst_idx].ptr, md[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, ml[src_idx].ptr, ml[src_idx].step/sizeof(float), ml[dst_idx].ptr, ml[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads>>>(dst_cols, dst_rows, src_rows, mr[src_idx].ptr, mr[src_idx].step/sizeof(float), mr[dst_idx].ptr, mr[dst_idx].step/sizeof(float));
//cudaSafeCall( cudaThreadSynchronize() );
}
else
{
beliefpropagation_gpu::level_up_kernel<<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, mu[src_idx].ptr, mu[src_idx].step/sizeof(float), mu[dst_idx].ptr, mu[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, md[src_idx].ptr, md[src_idx].step/sizeof(float), md[dst_idx].ptr, md[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, ml[src_idx].ptr, ml[src_idx].step/sizeof(float), ml[dst_idx].ptr, ml[dst_idx].step/sizeof(float));
beliefpropagation_gpu::level_up_kernel<<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, mr[src_idx].ptr, mr[src_idx].step/sizeof(float), mr[dst_idx].ptr, mr[dst_idx].step/sizeof(float));
}
}
}}}
@@ -301,7 +324,7 @@ namespace beliefpropagation_gpu
}
namespace cv { namespace gpu { namespace impl {
extern "C" void call_all_iterations(int cols, int rows, int iters, DevMem2D_<float>& u, DevMem2D_<float>& d, DevMem2D_<float>& l, DevMem2D_<float>& r, const DevMem2D_<float>& data)
extern "C" void call_all_iterations(int cols, int rows, int iters, DevMem2D_<float>& u, DevMem2D_<float>& d, DevMem2D_<float>& l, DevMem2D_<float>& r, const DevMem2D_<float>& data, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@@ -309,10 +332,17 @@ namespace cv { namespace gpu { namespace impl {
grid.x = divUp(cols, threads.x << 1);
grid.y = divUp(rows, threads.y);
for(int t = 0; t < iters; ++t)
beliefpropagation_gpu::one_iteration<<<grid, threads>>>(t, u.ptr, d.ptr, l.ptr, r.ptr, u.step/sizeof(float), data.ptr, data.step/sizeof(float), cols, rows);
cudaSafeCall( cudaThreadSynchronize() );
if (stream == 0)
{
for(int t = 0; t < iters; ++t)
beliefpropagation_gpu::one_iteration<<<grid, threads>>>(t, u.ptr, d.ptr, l.ptr, r.ptr, u.step/sizeof(float), data.ptr, data.step/sizeof(float), cols, rows);
//cudaSafeCall( cudaThreadSynchronize() );
}
else
{
for(int t = 0; t < iters; ++t)
beliefpropagation_gpu::one_iteration<<<grid, threads, 0, stream>>>(t, u.ptr, d.ptr, l.ptr, r.ptr, u.step/sizeof(float), data.ptr, data.step/sizeof(float), cols, rows);
}
}
}}}
@@ -358,7 +388,7 @@ namespace beliefpropagation_gpu
}
namespace cv { namespace gpu { namespace impl {
extern "C" void output_caller(const DevMem2D_<float>& u, const DevMem2D_<float>& d, const DevMem2D_<float>& l, const DevMem2D_<float>& r, const DevMem2D_<float>& data, DevMem2D disp)
extern "C" void output_caller(const DevMem2D_<float>& u, const DevMem2D_<float>& d, const DevMem2D_<float>& l, const DevMem2D_<float>& r, const DevMem2D_<float>& data, DevMem2D disp, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@@ -366,7 +396,14 @@ namespace cv { namespace gpu { namespace impl {
grid.x = divUp(disp.cols, threads.x);
grid.y = divUp(disp.rows, threads.y);
beliefpropagation_gpu::output<<<grid, threads>>>(disp.cols, disp.rows, u.ptr, d.ptr, l.ptr, r.ptr, data.ptr, u.step/sizeof(float), disp.ptr, disp.step);
cudaSafeCall( cudaThreadSynchronize() );
if (stream == 0)
{
beliefpropagation_gpu::output<<<grid, threads>>>(disp.cols, disp.rows, u.ptr, d.ptr, l.ptr, r.ptr, data.ptr, u.step/sizeof(float), disp.ptr, disp.step);
cudaSafeCall( cudaThreadSynchronize() );
}
else
{
beliefpropagation_gpu::output<<<grid, threads, 0, stream>>>(disp.cols, disp.rows, u.ptr, d.ptr, l.ptr, r.ptr, data.ptr, u.step/sizeof(float), disp.ptr, disp.step);
}
}
}}}