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ec11d8cdc4
This adds third-party performance tests to use in comparing Boost.Compute with other parallel/GPGPU frameworks like Intel's TBB and NVIDIA's Thrust along with the C++ STL. Also refactors the timing and profiling infrastructure and adds a simple perf.py driver script for running performance tests.
53 lines
1.4 KiB
C++
53 lines
1.4 KiB
C++
//---------------------------------------------------------------------------//
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// Copyright (c) 2013-2014 Kyle Lutz <kyle.r.lutz@gmail.com>
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//
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// Distributed under the Boost Software License, Version 1.0
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// See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt
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//
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// See http://kylelutz.github.com/compute for more information.
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//---------------------------------------------------------------------------//
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#include <algorithm>
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#include <iostream>
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#include <vector>
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#include "perf.hpp"
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float rand_float()
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{
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return (float(rand()) / float(RAND_MAX)) * 1000.f;
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}
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// y <- alpha * x + y
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void serial_saxpy(size_t n, float alpha, const float *x, float *y)
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{
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for(size_t i = 0; i < n; i++){
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y[i] = alpha * x[i] + y[i];
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}
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}
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int main(int argc, char *argv[])
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{
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perf_parse_args(argc, argv);
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std::cout << "size: " << PERF_N << std::endl;
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float alpha = 2.5f;
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std::vector<float> host_x(PERF_N);
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std::vector<float> host_y(PERF_N);
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std::generate(host_x.begin(), host_x.end(), rand_float);
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std::generate(host_y.begin(), host_y.end(), rand_float);
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perf_timer t;
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for(size_t trial = 0; trial < PERF_TRIALS; trial++){
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t.start();
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serial_saxpy(PERF_N, alpha, &host_x[0], &host_y[0]);
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t.stop();
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}
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std::cout << "time: " << t.min_time() / 1e6 << " ms" << std::endl;
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return 0;
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}
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