[/ Copyright Oliver Kowalke 2017. Distributed under the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt ] [#cuda] [section:cuda CUDA] [@http://developer.nvidia.com/cuda-zone/ CUDA (Compute Unified Device Architecture)] is a platform for parallel computing on NVIDIA GPUs. The application programming interface of CUDA gives access to GPU's instruction set and computation resources (Execution of compute kernels). [heading Synchronization with CUDA streams] CUDA operation such as compute kernels or memory transfer (between host and device) can be grouped/queued by CUDA streams. are executed on the GPUs. Boost.Fiber enables a fiber to sleep (suspend) till a CUDA stream has completed its operations. This enables applications to run other fibers on the CPU without the need to spawn an additional OS-threads. And resume the fiber when the CUDA streams has finished. __global__ void kernel( int size, int * a, int * b, int * c) { int idx = threadIdx.x + blockIdx.x * blockDim.x; if ( idx < size) { int idx1 = (idx + 1) % 256; int idx2 = (idx + 2) % 256; float as = (a[idx] + a[idx1] + a[idx2]) / 3.0f; float bs = (b[idx] + b[idx1] + b[idx2]) / 3.0f; c[idx] = (as + bs) / 2; } } boost::fibers::fiber f([&done]{ cudaStream_t stream; cudaStreamCreate( & stream); int size = 1024 * 1024; int full_size = 20 * size; int * host_a, * host_b, * host_c; cudaHostAlloc( & host_a, full_size * sizeof( int), cudaHostAllocDefault); cudaHostAlloc( & host_b, full_size * sizeof( int), cudaHostAllocDefault); cudaHostAlloc( & host_c, full_size * sizeof( int), cudaHostAllocDefault); int * dev_a, * dev_b, * dev_c; cudaMalloc( & dev_a, size * sizeof( int) ); cudaMalloc( & dev_b, size * sizeof( int) ); cudaMalloc( & dev_c, size * sizeof( int) ); std::minstd_rand generator; std::uniform_int_distribution<> distribution(1, 6); for ( int i = 0; i < full_size; ++i) { host_a[i] = distribution( generator); host_b[i] = distribution( generator); } for ( int i = 0; i < full_size; i += size) { cudaMemcpyAsync( dev_a, host_a + i, size * sizeof( int), cudaMemcpyHostToDevice, stream); cudaMemcpyAsync( dev_b, host_b + i, size * sizeof( int), cudaMemcpyHostToDevice, stream); kernel<<< size / 256, 256, 0, stream >>>( size, dev_a, dev_b, dev_c); cudaMemcpyAsync( host_c + i, dev_c, size * sizeof( int), cudaMemcpyDeviceToHost, stream); } auto result = boost::fibers::cuda::waitfor_all( stream); // suspend fiber till CUDA stream has finished BOOST_ASSERT( stream == std::get< 0 >( result) ); BOOST_ASSERT( cudaSuccess == std::get< 1 >( result) ); std::cout << "f1: GPU computation finished" << std::endl; cudaFreeHost( host_a); cudaFreeHost( host_b); cudaFreeHost( host_c); cudaFree( dev_a); cudaFree( dev_b); cudaFree( dev_c); cudaStreamDestroy( stream); }); f.join(); [heading Synopsis] #include namespace boost { namespace fibers { namespace cuda { std::tuple< cudaStream_t, cudaError_t > waitfor_all( cudaStream_t st); std::vector< std::tuple< cudaStream_t, cudaError_t > > waitfor_all( cudaStream_t ... st); }}} [ns_function_heading cuda..waitfor] #include namespace boost { namespace fibers { namespace cuda { std::tuple< cudaStream_t, cudaError_t > waitfor_all( cudaStream_t st); std::vector< std::tuple< cudaStream_t, cudaError_t > > waitfor_all( cudaStream_t ... st); }}} [variablelist [[Effects:] [Suspends active fiber till CUDA stream has finished its operations.]] [[Returns:] [tuple of stream reference and the CUDA stream status]] ] [endsect]