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More efficient access pattern in the GEMV kernel

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This commit is contained in:
Philippe Tillet
2015-02-10 23:01:16 -05:00
parent 85b7eb8b5e
commit e453031094
7 changed files with 124 additions and 106 deletions
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76
bench/blas.cpp
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@@ -236,44 +236,44 @@ cl::CommandQueue & queue = ad::cl_ext::queues[ad::cl_ext::default_context()][0];
// }
// std::cout << "\n\n" << std::flush;
// /*---------*/
// /*--BLAS2--*/
// /*---------*/
// //T-layout
// std::cout << "#GEMV-T" << std::endl;
// for(int_t i = 0 ; i < BLAS2_N.size() ; ++i)
// for(int_t j = 0 ; j < BLAS2_M.size() ; ++j)
// {
// int_t N = BLAS2_N[i];
// int_t M = BLAS2_M[j];
// std::cout << M << "," << N;
// /* ATIDLAS */
// ad::array A(N, M, dtype), y(M, dtype), x(N, dtype);
// y = dot(trans(A),x); queue.finish();
// BENCHMARK_ATIDLAS(y = ad::control(dot(trans(A),x), ad::execution_options_type(0, &events), ad::dispatcher_options_type(true)),(M*N + M + N)*dtsize/t);
// #ifdef BENCH_CLAMDBLAS
// BENCHMARK_CLAMDBLAS(clAmdBlasSgemv(clAmdBlasColumnMajor, clAmdBlasTrans, N, M, 1, A.data()(), A.ld(), x.data()(), 0, 1, 0, y.data()(), 0, 1, 1, &queue(),0, NULL, &event()), (M*N + M + N)*dtsize/t)
// #endif
// #ifdef BENCH_CBLAS
// std::vector<float> cA(N*M), cx(N), cy(M);
// ad::copy(x, cx);
// ad::copy(y, cy);
// ad::copy(A, cA);
// BENCHMARK_HOST(cblas_sgemv(CblasColMajor, CblasTrans, N, M, 1, cA.data(), N, cx.data(), 1, 0, cy.data(), 1), (M*N + M + N)*dtsize/t);
// #endif
// #ifdef BENCH_CUBLAS
// T *cuA, *cux, *cuy;
// cudaMalloc((void**) &cuA, N * M * sizeof(T));
// cudaMalloc((void**) &cux, N * sizeof(T));
// cudaMalloc((void**) &cuy, M * sizeof(T));
// BENCHMARK_CUDA(cublasSgemv(cublasTrans, N, M, 1, cuA, N, cux, 1, 0, cuy, 1), (M*N + M + N)*dtsize/t)
// cudaFree(cuA);
// cudaFree(cux);
// cudaFree(cuy);
// #endif
// std::cout << std::endl;
// }
// std::cout << "\n\n" << std::flush;
/*---------*/
/*--BLAS2--*/
/*---------*/
//T-layout
std::cout << "#GEMV-T" << std::endl;
for(int_t i = 0 ; i < BLAS2_N.size() ; ++i)
for(int_t j = 0 ; j < BLAS2_M.size() ; ++j)
{
int_t N = BLAS2_N[i];
int_t M = BLAS2_M[j];
std::cout << M << "," << N;
/* ATIDLAS */
ad::array A(N, M, dtype), y(M, dtype), x(N, dtype);
y = dot(trans(A),x); queue.finish();
BENCHMARK_ATIDLAS(y = ad::control(dot(trans(A),x), ad::execution_options_type(0, &events), ad::dispatcher_options_type(true)),(M*N + M + N)*dtsize/t);
#ifdef BENCH_CLAMDBLAS
BENCHMARK_CLAMDBLAS(clAmdBlasSgemv(clAmdBlasColumnMajor, clAmdBlasTrans, N, M, 1, A.data()(), A.ld(), x.data()(), 0, 1, 0, y.data()(), 0, 1, 1, &queue(),0, NULL, &event()), (M*N + M + N)*dtsize/t)
#endif
#ifdef BENCH_CBLAS
std::vector<float> cA(N*M), cx(N), cy(M);
ad::copy(x, cx);
ad::copy(y, cy);
ad::copy(A, cA);
BENCHMARK_HOST(cblas_sgemv(CblasColMajor, CblasTrans, N, M, 1, cA.data(), N, cx.data(), 1, 0, cy.data(), 1), (M*N + M + N)*dtsize/t);
#endif
#ifdef BENCH_CUBLAS
T *cuA, *cux, *cuy;
cudaMalloc((void**) &cuA, N * M * sizeof(T));
cudaMalloc((void**) &cux, N * sizeof(T));
cudaMalloc((void**) &cuy, M * sizeof(T));
BENCHMARK_CUDA(cublasSgemv(cublasTrans, N, M, 1, cuA, N, cux, 1, 0, cuy, 1), (M*N + M + N)*dtsize/t)
cudaFree(cuA);
cudaFree(cux);
cudaFree(cuy);
#endif
std::cout << std::endl;
}
std::cout << "\n\n" << std::flush;
/*---------*/
/*--BLAS3--*/