void copy(const compressed_matrix<SCALARTYPE, ALIGNMENT> & gpu_matrix, CPU_MATRIX & cpu_matrix ) { if ( gpu_matrix.size1() > 0 && gpu_matrix.size2() > 0 ) { cpu_matrix.resize(gpu_matrix.size1(), gpu_matrix.size2()); //get raw data from memory: std::vector<unsigned int> row_buffer(gpu_matrix.size1() + 1); std::vector<unsigned int> col_buffer(gpu_matrix.nnz()); std::vector<SCALARTYPE> elements(gpu_matrix.nnz()); //std::cout << "GPU->CPU, nonzeros: " << gpu_matrix.nnz() << std::endl; cl_int err; err = clEnqueueReadBuffer(viennacl::ocl::device().queue().get(), gpu_matrix.handle1().get(), CL_TRUE, 0, sizeof(unsigned int)*(gpu_matrix.size1() + 1), &(row_buffer[0]), 0, NULL, NULL); CL_ERR_CHECK(err); err = clEnqueueReadBuffer(viennacl::ocl::device().queue().get(), gpu_matrix.handle2().get(), CL_TRUE, 0, sizeof(unsigned int)*gpu_matrix.nnz(), &(col_buffer[0]), 0, NULL, NULL); CL_ERR_CHECK(err); err = clEnqueueReadBuffer(viennacl::ocl::device().queue().get(), gpu_matrix.handle().get(), CL_TRUE, 0, sizeof(SCALARTYPE)*gpu_matrix.nnz(), &(elements[0]), 0, NULL, NULL); CL_ERR_CHECK(err); viennacl::ocl::finish(); //fill the cpu_matrix: unsigned int data_index = 0; for (unsigned int row = 1; row <= gpu_matrix.size1(); ++row) { while (data_index < row_buffer[row]) { if (col_buffer[data_index] >= gpu_matrix.size1()) { std::cerr << "ViennaCL encountered invalid data at colbuffer[" << data_index << "]: " << col_buffer[data_index] << std::endl; return; } if (elements[data_index] != static_cast<SCALARTYPE>(0.0)) cpu_matrix(row-1, col_buffer[data_index]) = elements[data_index]; ++data_index; } } } }
void inplace_solve(compressed_matrix<SCALARTYPE, MAT_ALIGNMENT> const & L, vector<SCALARTYPE, VEC_ALIGNMENT> & vec, viennacl::linalg::unit_lower_tag) { viennacl::ocl::kernel & k = viennacl::ocl::get_kernel(viennacl::linalg::kernels::compressed_matrix<SCALARTYPE, MAT_ALIGNMENT>::program_name(), "lu_forward"); unsigned int threads = k.local_work_size(); k.global_work_size(k.local_work_size()); viennacl::ocl::enqueue(k(L.handle1(), L.handle2(), L, viennacl::ocl::local_mem(sizeof(int) * (threads+1)), viennacl::ocl::local_mem(sizeof(SCALARTYPE) * threads), vec, L.size1())); }