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src/cudamatrix/cu-rand-speed-test.cc
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// cudamatrix/cu-rand-speed-test.cc
// Copyright 2016 Brno University of Technology (author: Karel Vesely)
// See ../../COPYING for clarification regarding multiple authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
// MERCHANTABLITY OR NON-INFRINGEMENT.
// See the Apache 2 License for the specific language governing permissions and
// limitations under the License.
#include <iostream>
#include <vector>
#include <cstdlib>
#include "base/kaldi-common.h"
#include "util/common-utils.h"
#include "cudamatrix/cu-matrix.h"
#include "cudamatrix/cu-vector.h"
#include "cudamatrix/cu-rand.h"
using namespace kaldi;
namespace kaldi {
template<typename Real>
std::string NameOf() {
return (sizeof(Real) == 8 ? "<double>" : "<float>");
}
template <typename T>
std::string ToString(const T& t) {
std::ostringstream os;
os << t;
return os.str();
}
template<typename Real>
std::string MeanVariance(const CuMatrixBase<Real>& m) {
std::ostringstream os;
Real mean = m.Sum() / (m.NumRows()*m.NumCols());
CuMatrix<Real> tmp(m);
tmp.Add(-mean);
tmp.ApplyPow(2.0);
Real var = tmp.Sum() / (tmp.NumRows()*tmp.NumCols());
return std::string("mean ") + ToString(mean) + ", std-dev " + ToString(std::sqrt(var));
}
template<typename Real>
std::string MeanVariance(const CuVectorBase<Real>& v) {
std::ostringstream os;
Real mean = v.Sum() / v.Dim();
CuVector<Real> tmp(v);
tmp.Add(-mean);
tmp.ApplyPow(2.0);
Real var = tmp.Sum() / tmp.Dim();
return std::string("mean ") + ToString(mean) + ", std-dev " + ToString(std::sqrt(var));
}
template <typename Real>
void CuRandUniformMatrixSpeedTest(const int32 iter) {
Timer t;
CuRand<Real> rand;
CuMatrix<Real> m(249,1001, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandUniform(&m);
}
CuMatrix<Real> m2(256,1024, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandUniform(&m2);
}
// flops = number of generated random numbers per second,
Real flops = iter * (m.NumRows() * m.NumCols() + m2.NumRows() * m2.NumCols()) / t.Elapsed();
KALDI_LOG << __func__ << NameOf<Real>()
<< " Speed was " << flops << " rand_elems/s. "
<< "(debug " << MeanVariance(m) << ")";
}
template <typename Real>
void CuRandUniformMatrixBaseSpeedTest(const int32 iter) {
Timer t;
CuRand<Real> rand;
CuMatrix<Real> m(249,1001, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandUniform(dynamic_cast<CuMatrixBase<Real>*>(&m));
}
CuMatrix<Real> m2(256,1024, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandUniform(dynamic_cast<CuMatrixBase<Real>*>(&m2));
}
// flops = number of generated random numbers per second,
Real flops = iter * (m.NumRows() * m.NumCols() + m2.NumRows() * m2.NumCols()) / t.Elapsed();
KALDI_LOG << __func__ << NameOf<Real>()
<< " Speed was " << flops << " rand_elems/s. "
<< "(debug " << MeanVariance(m) << ")";
}
template <typename Real>
void CuRandGaussianMatrixSpeedTest(const int32 iter) {
Timer t;
CuRand<Real> rand;
CuMatrix<Real> m(249,1001, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandGaussian(&m);
}
CuMatrix<Real> m2(256,1024, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandGaussian(&m2);
}
// flops = number of generated random numbers per second,
Real flops = iter * (m.NumRows() * m.NumCols() + m2.NumRows() * m2.NumCols()) / t.Elapsed();
KALDI_LOG << __func__ << NameOf<Real>()
<< " Speed was " << flops << " rand_elems/s. "
<< "(debug " << MeanVariance(m) << ")";
}
template <typename Real>
void CuRandGaussianMatrixBaseSpeedTest(const int32 iter) {
Timer t;
CuRand<Real> rand;
CuMatrix<Real> m(249,1001, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandGaussian(dynamic_cast<CuMatrixBase<Real>*>(&m));
}
CuMatrix<Real> m2(256,1024, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandGaussian(dynamic_cast<CuMatrixBase<Real>*>(&m2));
}
// flops = number of generated random numbers per second,
Real flops = iter * (m.NumRows() * m.NumCols() + m2.NumRows() * m2.NumCols()) / t.Elapsed();
KALDI_LOG << __func__ << NameOf<Real>()
<< " Speed was " << flops << " rand_elems/s. "
<< "(debug " << MeanVariance(m) << ")";
}
template <typename Real>
void CuRandUniformVectorSpeedTest(const int32 iter) {
Timer t;
CuRand<Real> rand;
CuVector<Real> v(2011, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandUniform(&v);
}
CuVector<Real> v2(2048, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandUniform(&v2);
}
// flops = number of generated random numbers per second,
Real flops = iter * (v.Dim() + v2.Dim()) / t.Elapsed();
KALDI_LOG << __func__ << NameOf<Real>()
<< " Speed was " << flops << " rand_elems/s. "
<< "(debug " << MeanVariance(v) << ")";
}
template <typename Real>
void CuRandGaussianVectorSpeedTest(const int32 iter) {
Timer t;
CuRand<Real> rand;
CuVector<Real> v(2011, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandGaussian(&v);
}
CuVector<Real> v2(2048, kUndefined);
for (int32 i = 0; i < iter; i++) {
rand.RandGaussian(&v2);
}
// flops = number of generated random numbers per second,
Real flops = iter * (v.Dim() + v2.Dim()) / t.Elapsed();
KALDI_LOG << __func__ << NameOf<Real>()
<< " Speed was " << flops << " rand_elems/s. "
<< "(debug " << MeanVariance(v) << ")";
}
} // namespace kaldi
int main() {
int32 iter = 10; // Be quick on CPU,
#if HAVE_CUDA == 1
for (int32 loop = 0; loop < 2; loop++) { // NO for loop if 'HAVE_CUDA != 1',
CuDevice::Instantiate().SetDebugStrideMode(true);
if ( loop == 0)
CuDevice::Instantiate().SelectGpuId("no");
else {
CuDevice::Instantiate().SelectGpuId("yes");
iter = 400; // GPUs are faster,
}
#endif
Timer t;
kaldi::CuRandUniformMatrixSpeedTest<float>(iter);
kaldi::CuRandUniformMatrixBaseSpeedTest<float>(iter);
kaldi::CuRandUniformVectorSpeedTest<float>(iter);
kaldi::CuRandGaussianMatrixSpeedTest<float>(iter);
kaldi::CuRandGaussianMatrixBaseSpeedTest<float>(iter);
kaldi::CuRandGaussianVectorSpeedTest<float>(iter);
fprintf(stderr, "---
");
kaldi::CuRandUniformMatrixSpeedTest<double>(iter);
kaldi::CuRandUniformMatrixBaseSpeedTest<double>(iter);
kaldi::CuRandUniformVectorSpeedTest<double>(iter);
kaldi::CuRandGaussianMatrixSpeedTest<double>(iter);
kaldi::CuRandGaussianMatrixBaseSpeedTest<double>(iter);
kaldi::CuRandGaussianVectorSpeedTest<double>(iter);
fprintf(stderr, "--- ELAPSED %fs.
", t.Elapsed());
#if HAVE_CUDA == 1
} // No for loop if 'HAVE_CUDA != 1',
CuDevice::Instantiate().PrintProfile();
#endif
KALDI_LOG << "Tests succeeded.";
}
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