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C++: Added clBLAS sGEMM ABI (still buggy)

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This commit is contained in:
Philippe Tillet
2015-06-24 07:51:27 -07:00
parent c61eaceb21
commit 9f7e34ba5d
10 changed files with 9928 additions and 140 deletions
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240
bench/blas.cpp
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@@ -2,7 +2,7 @@
#include "isaac/symbolic/execute.h"
#include "isaac/tools/timer.hpp"
#ifdef BENCH_CLBLAS
#include "clBLAS.h"
#include "isaac/wrap/clBLAS.h"
#endif
#ifdef BENCH_CBLAS
#include "cblas.h"
@@ -166,127 +166,127 @@ void bench(ad::numeric_type dtype, std::string operation)
// /*--BLAS1--*/
// /*---------*/
if(operation=="axpy")
{
for(int_t N: create_log_range(1e3, 2e7, 50, 64))
{
std::cout << N;
ad::array x(N, dtype), y(N, dtype);
/* ISAAC */
std::list<ad::driver::Event> events;\
BENCHMARK_ISAAC(y = ad::control(x + y, ad::execution_options_type(0, &events), ad::dispatcher_options_type(false)), 3*N*dtsize/t)
BENCHMARK_ISAAC(y = ad::control(x + y, ad::execution_options_type(0, &events), ad::dispatcher_options_type(true)), 3*N*dtsize/t)
/* clblas */
#ifdef BENCH_CLBLAS
BENCHMARK_CLBLAS(clblasSaxpy(N, 1, CL_HANDLE(x.data()), 0, 1, CL_HANDLE(y.data()), 0, 1, 1, &CL_HANDLE(queue), 0, NULL, &event()), 3*N*dtsize/t)
#endif
/* BLAS */
#ifdef BENCH_CBLAS
std::vector<float> cx(N), cy(N);
ad::copy(x, cx);
ad::copy(y, cy);
BENCHMARK_HOST(cblas_saxpy(N, 1, cx.data(), 1, cy.data(), 1), 3*N*dtsize/t);
#endif
/* CuBLAS */
#ifdef BENCH_CUBLAS
T *cux, *cuy;
cudaMalloc((void**) &cux, N * sizeof(T));
cudaMalloc((void**) &cuy, N * sizeof(T));
BENCHMARK_CUDA(cublasSaxpy(N, 2, cux, 1, cuy, 1), 3*N*dtsize/t)
cudaFree(cux);
cudaFree(cuy);
#endif
std::cout << std::endl;
}
}
// if(operation=="axpy")
// {
// for(int_t N: create_log_range(1e3, 2e7, 50, 64))
// {
// std::cout << N;
// ad::array x(N, dtype), y(N, dtype);
// /* ISAAC */
// std::list<ad::driver::Event> events;\
// BENCHMARK_ISAAC(y = ad::control(x + y, ad::execution_options_type(0, &events), ad::dispatcher_options_type(false)), 3*N*dtsize/t)
// BENCHMARK_ISAAC(y = ad::control(x + y, ad::execution_options_type(0, &events), ad::dispatcher_options_type(true)), 3*N*dtsize/t)
// /* clblas */
// #ifdef BENCH_CLBLAS
// BENCHMARK_CLBLAS(clblasSaxpy(N, 1, CL_HANDLE(x.data()), 0, 1, CL_HANDLE(y.data()), 0, 1, 1, &CL_HANDLE(queue), 0, NULL, &event()), 3*N*dtsize/t)
// #endif
// /* BLAS */
// #ifdef BENCH_CBLAS
// std::vector<float> cx(N), cy(N);
// ad::copy(x, cx);
// ad::copy(y, cy);
// BENCHMARK_HOST(cblas_saxpy(N, 1, cx.data(), 1, cy.data(), 1), 3*N*dtsize/t);
// #endif
// /* CuBLAS */
// #ifdef BENCH_CUBLAS
// T *cux, *cuy;
// cudaMalloc((void**) &cux, N * sizeof(T));
// cudaMalloc((void**) &cuy, N * sizeof(T));
// BENCHMARK_CUDA(cublasSaxpy(N, 2, cux, 1, cuy, 1), 3*N*dtsize/t)
// cudaFree(cux);
// cudaFree(cuy);
// #endif
// std::cout << std::endl;
// }
// }
if(operation=="dot")
{
for(int_t N: create_log_range(1e3, 2e7, 50, 64))
{
std::cout << N;
/* ISAAC */
ad::array x(N, dtype), y(N, dtype);
ad::array scratch(N, dtype);
ad::scalar s(dtype);
s = dot(x,y); queue.synchronize();
BENCHMARK_ISAAC(s = ad::control(dot(x,y), ad::execution_options_type(0, &events), ad::dispatcher_options_type(true)), 2*N*dtsize/t)
/* clblas */
#ifdef BENCH_CLBLAS
BENCHMARK_CLBLAS(clblasSdot(N, CL_HANDLE(s.data()), 0, CL_HANDLE(x.data()), 0, 1, CL_HANDLE(y.data()), 0, 1, CL_HANDLE(scratch.data()), 1, &CL_HANDLE(queue), 0, NULL, &event()), 2*N*dtsize/t)
#endif
/* BLAS */
#ifdef BENCH_CBLAS
std::vector<float> cx(N), cy(N);
ad::copy(x, cx);
ad::copy(y, cy);
BENCHMARK_HOST(cblas_sdot(N, cx.data(), 1, cy.data(), 1), 2*N*dtsize/t);
#endif
#ifdef BENCH_CUBLAS
T *cux, *cuy;
T result;
cudaMalloc((void**) &cux, N * sizeof(T));
cudaMalloc((void**) &cuy, N * sizeof(T));
BENCHMARK_CUDA(cublasSdot(N, cux, 1, cuy, 1), 2*N*dtsize/t)
cudaFree(cux);
cudaFree(cuy);
#endif
std::cout << std::endl;
}
std::cout << "\n\n" << std::flush;
}
// if(operation=="dot")
// {
// for(int_t N: create_log_range(1e3, 2e7, 50, 64))
// {
// std::cout << N;
// /* ISAAC */
// ad::array x(N, dtype), y(N, dtype);
// ad::array scratch(N, dtype);
// ad::scalar s(dtype);
// s = dot(x,y); queue.synchronize();
// BENCHMARK_ISAAC(s = ad::control(dot(x,y), ad::execution_options_type(0, &events), ad::dispatcher_options_type(true)), 2*N*dtsize/t)
// /* clblas */
// #ifdef BENCH_CLBLAS
// BENCHMARK_CLBLAS(clblasSdot(N, CL_HANDLE(s.data()), 0, CL_HANDLE(x.data()), 0, 1, CL_HANDLE(y.data()), 0, 1, CL_HANDLE(scratch.data()), 1, &CL_HANDLE(queue), 0, NULL, &event()), 2*N*dtsize/t)
// #endif
// /* BLAS */
// #ifdef BENCH_CBLAS
// std::vector<float> cx(N), cy(N);
// ad::copy(x, cx);
// ad::copy(y, cy);
// BENCHMARK_HOST(cblas_sdot(N, cx.data(), 1, cy.data(), 1), 2*N*dtsize/t);
// #endif
// #ifdef BENCH_CUBLAS
// T *cux, *cuy;
// T result;
// cudaMalloc((void**) &cux, N * sizeof(T));
// cudaMalloc((void**) &cuy, N * sizeof(T));
// BENCHMARK_CUDA(cublasSdot(N, cux, 1, cuy, 1), 2*N*dtsize/t)
// cudaFree(cux);
// cudaFree(cuy);
// #endif
// std::cout << std::endl;
// }
// std::cout << "\n\n" << std::flush;
// }
if(operation.substr(0, 4)=="gemv")
{
std::vector<std::tuple<int_t, int_t> > MNs;
MNs.push_back(std::make_tuple(896,896));
MNs.push_back(std::make_tuple(3072,3072));
MNs.push_back(std::make_tuple(64,32000));
MNs.push_back(std::make_tuple(896,32000));
MNs.push_back(std::make_tuple(32000, 64));
MNs.push_back(std::make_tuple(32000, 896));
// if(operation.substr(0, 4)=="gemv")
// {
// std::vector<std::tuple<int_t, int_t> > MNs;
// MNs.push_back(std::make_tuple(896,896));
// MNs.push_back(std::make_tuple(3072,3072));
// MNs.push_back(std::make_tuple(64,32000));
// MNs.push_back(std::make_tuple(896,32000));
// MNs.push_back(std::make_tuple(32000, 64));
// MNs.push_back(std::make_tuple(32000, 896));
/*---------*/
/*--BLAS2--*/
/*---------*/
//T-layout
for(std::tuple<int_t, int_t> MN: MNs)
{
int_t M = std::get<0>(MN);
int_t N = std::get<1>(MN);
std::cout << M << "," << N;
/* ISAAC */
ad::array A(N, M, dtype), y(M, dtype), x(N, dtype);
#if HAS_A_BLAS
int_t lda = A.ld();
#endif
y = dot(trans(A),x); queue.synchronize();
BENCHMARK_ISAAC(y = ad::control(dot(trans(A),x), ad::execution_options_type(0, &events), ad::dispatcher_options_type(false)),(M*N + M + N)*dtsize/t);
BENCHMARK_ISAAC(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_CLBLAS
BENCHMARK_CLBLAS(clblasSgemv(clblasColumnMajor, clblasTrans, N, M, 1, CL_HANDLE(A.data()), 0, lda, CL_HANDLE(x.data()), 0, 1, 0, CL_HANDLE(y.data()), 0, 1, 1, &CL_HANDLE(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(), lda, 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('t', N, M, 1, cuA, lda, 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
// for(std::tuple<int_t, int_t> MN: MNs)
// {
// int_t M = std::get<0>(MN);
// int_t N = std::get<1>(MN);
// std::cout << M << "," << N;
// /* ISAAC */
// ad::array A(N, M, dtype), y(M, dtype), x(N, dtype);
// #if HAS_A_BLAS
// int_t lda = A.ld();
// #endif
// y = dot(trans(A),x); queue.synchronize();
// BENCHMARK_ISAAC(y = ad::control(dot(trans(A),x), ad::execution_options_type(0, &events), ad::dispatcher_options_type(false)),(M*N + M + N)*dtsize/t);
// BENCHMARK_ISAAC(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_CLBLAS
// BENCHMARK_CLBLAS(clblasSgemv(clblasColumnMajor, clblasTrans, N, M, 1, CL_HANDLE(A.data()), 0, lda, CL_HANDLE(x.data()), 0, 1, 0, CL_HANDLE(y.data()), 0, 1, 1, &CL_HANDLE(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(), lda, 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('t', N, M, 1, cuA, lda, 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;
// }
if(operation.substr(0,4)=="gemm")
{
@@ -312,7 +312,7 @@ void bench(ad::numeric_type dtype, std::string operation)
#if HAS_A_BLAS
int_t lda = A.ld(), ldb = B.ld(), ldc = C.ld();
#endif
BENCHMARK_ISAAC(C = ad::control(dot(A,trans(B)), ad::execution_options_type(0, &events), ad::dispatcher_options_type(false)), (double)2*M*N*K/t);
// BENCHMARK_ISAAC(C = ad::control(dot(A,trans(B)), ad::execution_options_type(0, &events), ad::dispatcher_options_type(false)), (double)2*M*N*K/t);
//BENCHMARK_ISAAC(C = ad::control(dot(A,trans(B)), ad::execution_options_type(0, &events), ad::dispatcher_options_type(true)), (double)2*M*N*K/t);
/* clblas */
#ifdef BENCH_CLBLAS