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src/cudamatrix/cu-compressed-matrix.cc
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// cudamatrix/cu-compressed-matrix.cc
// Copyright 2018 Johns Hopkins University (author: Daniel Povey)
// 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.
#if HAVE_CUDA == 1
#include <cuda_runtime_api.h>
#include <cublas_v2.h>
#endif
#include "base/timer.h"
#include "cudamatrix/cu-common.h"
#include "cudamatrix/cu-vector.h"
#include "cudamatrix/cu-device.h"
#include "cudamatrix/cu-kernels.h"
#include "cudamatrix/cu-array.h"
#include "cudamatrix/cu-compressed-matrix.h"
namespace kaldi {
template <typename I>
CuCompressedMatrix<I>::CuCompressedMatrix(BaseFloat range, bool truncate):
data_(NULL), scale_(range / std::numeric_limits<I>::max()),
truncate_(truncate), num_rows_(0), num_cols_(0), stride_(0) {
#if HAVE_CUDA == 1
KALDI_ASSERT(CuDevice::Instantiate().Enabled());
#else
KALDI_ERR << "You instantiated CuCompressedMatrix while GPU use "
"was not compiled in.";
#endif
}
template <typename I>
void CuCompressedMatrix<I>::Destroy() {
#if HAVE_CUDA == 1
if (data_ != NULL) {
// we don't bother timing this because Free() won't normally have to
// access the GPU at all (due to caching).
CuDevice::Instantiate().Free(data_);
data_ = NULL;
num_rows_ = 0;
num_cols_ = 0;
stride_ = 0;
}
#endif
}
template <typename I>
void CuCompressedMatrix<I>::CopyFromMat(
const CuMatrixBase<BaseFloat> &mat) {
#if HAVE_CUDA == 1
KALDI_ASSERT(CuDevice::Instantiate().Enabled());
if (mat.NumRows() == 0)
return;
if (num_rows_ != mat.NumRows() || num_cols_ != mat.NumCols()) {
Destroy();
num_rows_ = mat.NumRows();
num_cols_ = mat.NumCols();
data_ = static_cast<I*>(
CuDevice::Instantiate().Malloc(sizeof(I) * num_rows_ * num_cols_));
stride_ = num_cols_;
}
{
CuTimer tim;
dim3 dimGrid, dimBlock;
GetBlockSizesForSimpleMatrixOperation(NumRows(), NumCols(),
&dimGrid, &dimBlock);
if (scale_ == 0.0) { // scale == 0 calls a different kernel from the others.
cuda_mat_compress_sign(dimGrid, dimBlock, mat.Data(), mat.Dim(),
data_, stride_);
} else {
cuda_mat_compress(dimGrid, dimBlock, mat.Data(), mat.Dim(),
data_, stride_, float(1.0 / scale_),
truncate_);
}
CU_SAFE_CALL(cudaGetLastError());
CuDevice::Instantiate().AccuProfile(__func__, tim);
}
#endif
}
template <typename I>
void CuCompressedMatrix<I>::CopyToMat(CuMatrixBase<BaseFloat> *mat) const {
#if HAVE_CUDA == 1
KALDI_ASSERT(CuDevice::Instantiate().Enabled());
KALDI_ASSERT(mat->NumRows() == num_rows_ && mat->NumCols() == num_cols_);
{
CuTimer tim;
dim3 dimGrid, dimBlock;
GetBlockSizesForSimpleMatrixOperation(NumRows(), NumCols(),
&dimGrid, &dimBlock);
BaseFloat scale = (scale_ == 0.0 ? 1.0 : scale_);
cuda_mat_uncompress(dimGrid, dimBlock, mat->Data(), mat->Dim(),
data_, stride_, float(scale));
}
#endif
}
CuCompressedMatrixBase *NewCuCompressedMatrix(CuCompressedMatrixType t,
BaseFloat range,
bool truncat) {
if (t == kCompressedMatrixUint8) {
KALDI_ASSERT(range >= 0);
return new CuCompressedMatrix<uint8>(range);
} else if (t == kCompressedMatrixInt8) {
KALDI_ASSERT(range >= 0);
return new CuCompressedMatrix<int8>(range);
} else if (t == kCompressedMatrixUint16) {
KALDI_ASSERT(range > 0);
return new CuCompressedMatrix<uint16>(range);
} else if (t == kCompressedMatrixInt16) {
KALDI_ASSERT(range > 0);
return new CuCompressedMatrix<int16>(range);
} else {
KALDI_ERR << "Unknown compressed-matrix type";
return NULL;
}
}
} // namespace kaldi
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