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/* ************************************************************************
* Copyright (C) 2016-2024 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell cop-
* ies of the Software, and to permit persons to whom the Software is furnished
* to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IM-
* PLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNE-
* CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
* ************************************************************************ */
#include "client_utility.hpp"
#include <hip/hip_runtime.h>
#include <rocblas/rocblas.h>
const int NUM_ITER = 1000;
double maxRelativeError(std::vector<double>& A, std::vector<double>& reference)
{
double maxRelativeError = double(std::numeric_limits<double>::min());
size_t n = A.size();
for(size_t i = 0; i < n; ++i)
{
double gold = double(reference[i]);
double relativeError = gold != 0 ? (gold - double(A[i])) / (gold) : double(A[i]);
relativeError = relativeError > 0 ? relativeError : -relativeError;
maxRelativeError = relativeError < maxRelativeError ? maxRelativeError : relativeError;
}
return maxRelativeError;
}
int main()
{
rocblas_status rstatus = rocblas_status_success;
rocblas_int M = 8192;
rocblas_int N = 3;
rocblas_int incx = 1;
rocblas_int incy = 1;
typedef double dataType;
dataType h_alpha = 1.0;
dataType h_beta = 0.0;
const rocblas_operation trans_A = rocblas_operation_transpose;
size_t size_x, dim_x, abs_incx;
size_t size_y, dim_y, abs_incy;
if(trans_A == rocblas_operation_none)
{
dim_x = N;
dim_y = M;
}
else // transpose
{
dim_x = M;
dim_y = N;
}
rocblas_int lda = M;
size_t size_A = lda * size_t(dim_x);
abs_incx = incx >= 0 ? incx : -incx;
abs_incy = incy >= 0 ? incy : -incy;
size_x = dim_x * abs_incx;
size_y = dim_y * abs_incy;
std::vector<dataType> hA(size_A);
std::vector<dataType> hx(size_x);
std::vector<dataType> hy(size_y, 0);
// initial data on host
srand(1);
for(int i = 0; i < size_A; ++i)
{
hA[i] = rand() % 17;
}
for(int i = 0; i < size_x; ++i)
{
hx[i] = rand() % 17;
}
std::vector<dataType> hy_gold = hy;
// using rocblas API
rocblas_handle handle;
CHECK_ROCBLAS_ERROR(rocblas_create_handle(&handle));
hipStream_t stream_1, stream_2;
CHECK_HIP_ERROR(hipStreamCreate(&stream_1));
CHECK_HIP_ERROR(hipStreamCreate(&stream_2));
bool graph_captured = false;
hipGraph_t graph;
hipGraphExec_t graph_exec;
// allocate memory on device
dataType *dA, *dX, *dY;
CHECK_HIP_ERROR(hipMalloc(&dA, size_A * sizeof(dataType)));
CHECK_HIP_ERROR(hipMalloc(&dX, size_x * sizeof(dataType)));
CHECK_HIP_ERROR(hipMalloc(&dY, size_y * sizeof(dataType)));
// copy data from CPU to device
CHECK_HIP_ERROR(hipMemcpy(dA, hA.data(), sizeof(dataType) * size_A, hipMemcpyHostToDevice));
CHECK_HIP_ERROR(hipMemcpy(dX, hx.data(), sizeof(dataType) * size_x, hipMemcpyHostToDevice));
CHECK_HIP_ERROR(hipMemcpy(dY, hy.data(), sizeof(dataType) * size_y, hipMemcpyHostToDevice));
// enable passing alpha and beta parameters from pointer to host memory
CHECK_ROCBLAS_ERROR(rocblas_set_pointer_mode(handle, rocblas_pointer_mode_host));
CHECK_ROCBLAS_ERROR(rocblas_set_stream(handle, stream_1));
for(auto i = 0; i < NUM_ITER; i++)
{
if(!graph_captured)
{
CHECK_HIP_ERROR(hipStreamBeginCapture(stream_1, hipStreamCaptureModeGlobal));
// asynchronous calculation on device, returns before finished calculations
CHECK_ROCBLAS_ERROR(rocblas_dgemv(
handle, trans_A, M, N, &h_alpha, dA, lda, dX, incx, &h_beta, dY, incy));
CHECK_HIP_ERROR(hipStreamEndCapture(stream_1, &graph));
CHECK_HIP_ERROR(hipGraphInstantiate(&graph_exec, graph, NULL, NULL, 0));
CHECK_HIP_ERROR(hipGraphDestroy(graph));
graph_captured = true;
}
CHECK_HIP_ERROR(
hipGraphLaunch(graph_exec, stream_2)); //Launching the graph in a different stream.
}
// fetch device memory results, automatically blocked until results ready
CHECK_HIP_ERROR(hipMemcpy(hy.data(), dY, sizeof(dataType) * size_y, hipMemcpyDeviceToHost));
rocblas_cout << "M, N, lda = " << M << ", " << N << ", " << lda << std::endl;
// calculate expected result using CPU
for(size_t j = 0; j < size_y; j++)
{
for(size_t i = j * M, k = 0; k < M; k++, i++)
{
hy_gold[j] += h_alpha * hA[i] * hx[k] + h_beta * hy_gold[j];
}
}
auto maxRelativeErr = maxRelativeError(hy, hy_gold);
dataType eps = std::numeric_limits<dataType>::epsilon();
dataType tolerance = 10;
if(maxRelativeErr > eps * tolerance)
{
std::cout << "FAIL";
}
else
{
std::cout << "PASS";
}
std::cout << ": max. relative err. = " << maxRelativeErr << std::endl;
CHECK_HIP_ERROR(hipGraphExecDestroy(graph_exec));
/* CAUTION: Do not destroy streams before destroying the rocblas_handle.
rocblas_handle requires stream parameter to free allocated device memory.*/
CHECK_ROCBLAS_ERROR(rocblas_destroy_handle(handle));
CHECK_HIP_ERROR(hipStreamDestroy(stream_1));
CHECK_HIP_ERROR(hipStreamDestroy(stream_2));
CHECK_HIP_ERROR(hipFree(dA));
CHECK_HIP_ERROR(hipFree(dX));
CHECK_HIP_ERROR(hipFree(dY));
return EXIT_SUCCESS;
}
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