89 lines
3.0 KiB
C++
89 lines
3.0 KiB
C++
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// =================================================================================================
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// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
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// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
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// width of 100 characters per line.
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//
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// Author(s):
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// Cedric Nugteren <www.cedricnugteren.nl>
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//
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// This file demonstrates the use of the DAXPY routine with the C++ CUDA API of CLBlast.
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//
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// Note that this example is meant for illustration purposes only. CLBlast provides other programs
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// for performance benchmarking ('client_xxxxx') and for correctness testing ('test_xxxxx').
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//
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// =================================================================================================
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#include <cstdio>
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#include <chrono>
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#include <vector>
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// Includes the CUDA driver API
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#include <cuda.h>
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// Includes the CLBlast library
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#include <clblast_cuda.h>
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// =================================================================================================
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// Example use of the double-precision Xaxpy routine DAXPY
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int main() {
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// CUDA device selection
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const auto device_id = 0;
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// Example DAXPY arguments
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const size_t n = 8192;
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const double alpha = 0.7;
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// Initializes the OpenCL device
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cuInit(0);
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CUdevice device;
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cuDeviceGet(&device, device_id);
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// Creates the OpenCL context and stream
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CUcontext context;
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cuCtxCreate(&context, 0, device);
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CUstream stream;
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cuStreamCreate(&stream, CU_STREAM_NON_BLOCKING);
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// Populate host matrices with some example data
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auto host_a = std::vector<double>(n);
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auto host_b = std::vector<double>(n);
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for (auto &item: host_a) { item = 12.193; }
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for (auto &item: host_b) { item = -8.199; }
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// Copy the matrices to the device
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CUdeviceptr device_a;
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CUdeviceptr device_b;
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cuMemAlloc(&device_a, host_a.size()*sizeof(double));
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cuMemAlloc(&device_b, host_b.size()*sizeof(double));
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cuMemcpyHtoDAsync(device_a, host_a.data(), host_a.size()*sizeof(double), stream);
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cuMemcpyHtoDAsync(device_b, host_b.data(), host_b.size()*sizeof(double), stream);
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// Start the timer
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auto start_time = std::chrono::steady_clock::now();
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// Call the DAXPY routine. Note that the type of alpha (double) determines the precision.
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const auto status = clblast::Axpy(n, alpha,
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device_a, 0, 1,
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device_b, 0, 1,
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context, device);
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cuStreamSynchronize(stream);
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// Record the execution time
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auto elapsed_time = std::chrono::steady_clock::now() - start_time;
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auto time_ms = std::chrono::duration<double,std::milli>(elapsed_time).count();
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// Example completed. See "clblast_cuda.h" for status codes (0 -> success).
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printf("Completed DAXPY in %.3lf ms with status %d\n", time_ms, static_cast<int>(status));
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// Clean-up
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cuMemFree(device_a);
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cuMemFree(device_b);
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cuStreamDestroy(stream);
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return 0;
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}
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// =================================================================================================
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