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Grid/Hadrons/A2AMatrix.hpp

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/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: Hadrons/A2AMatrix.hpp
Copyright (C) 2015-2018
Author: Antonin Portelli <antonin.portelli@me.com>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef A2A_Matrix_hpp_
#define A2A_Matrix_hpp_
#include <Hadrons/Global.hpp>
#include <Hadrons/TimerArray.hpp>
#include <Grid/Eigen/unsupported/CXX11/Tensor>
#ifdef USE_MKL
#include "mkl.h"
#include "mkl_cblas.h"
#endif
#ifndef HADRONS_A2AM_NAME
#define HADRONS_A2AM_NAME "a2aMatrix"
#endif
#ifndef HADRONS_A2AM_IO_TYPE
#define HADRONS_A2AM_IO_TYPE ComplexF
#endif
#define HADRONS_A2AM_PARALLEL_IO
BEGIN_HADRONS_NAMESPACE
// general A2A matrix set based on Eigen tensors and Grid-allocated memory
// Dimensions:
// 0 - ext - external field (momentum, EM field, ...)
// 1 - str - spin-color structure
// 2 - t - timeslice
// 3 - i - left A2A mode index
// 4 - j - right A2A mode index
template <typename T>
using A2AMatrixSet = Eigen::TensorMap<Eigen::Tensor<T, 5, Eigen::RowMajor>>;
template <typename T>
using A2AMatrix = Eigen::Matrix<T, -1, -1, Eigen::RowMajor>;
template <typename T>
using A2AMatrixMap = Eigen::Map<A2AMatrix<T>>;
template <typename T>
using A2AMatrixTr = Eigen::Matrix<T, -1, -1, Eigen::ColMajor>;
/******************************************************************************
* Abstract class for A2A kernels *
******************************************************************************/
template <typename T, typename Field>
class A2AKernel
{
public:
A2AKernel(void) = default;
virtual ~A2AKernel(void) = default;
virtual void operator()(A2AMatrixSet<T> &m, const Field *left, const Field *right,
const unsigned int orthogDim, double &time) = 0;
virtual double flops(const unsigned int blockSizei, const unsigned int blockSizej) = 0;
virtual double bytes(const unsigned int blockSizei, const unsigned int blockSizej) = 0;
};
/******************************************************************************
* Class to handle A2A matrix block HDF5 I/O *
******************************************************************************/
template <typename T>
class A2AMatrixIo
{
public:
// constructors
A2AMatrixIo(void) = default;
A2AMatrixIo(std::string filename, std::string dataname,
const unsigned int nt, const unsigned int ni = 0,
const unsigned int nj = 0);
// destructor
~A2AMatrixIo(void) = default;
// access
unsigned int getNi(void) const;
unsigned int getNj(void) const;
unsigned int getNt(void) const;
size_t getSize(void) const;
// file allocation
template <typename MetadataType>
void initFile(const MetadataType &d, const unsigned int chunkSize);
// block I/O
void saveBlock(const T *data, const unsigned int i, const unsigned int j,
const unsigned int blockSizei, const unsigned int blockSizej);
void saveBlock(const A2AMatrixSet<T> &m, const unsigned int ext, const unsigned int str,
const unsigned int i, const unsigned int j);
template <template <class> class Vec, typename VecT>
void load(Vec<VecT> &v, double *tRead = nullptr, const bool useCache = true);
private:
std::string filename_{""}, dataname_{""};
unsigned int nt_{0}, ni_{0}, nj_{0};
};
/******************************************************************************
* Wrapper for A2A matrix block computation *
******************************************************************************/
template <typename T, typename Field, typename MetadataType, typename TIo = T>
class A2AMatrixBlockComputation
{
private:
struct IoHelper
{
A2AMatrixIo<TIo> io;
MetadataType md;
unsigned int e, s, i, j;
};
typedef std::function<std::string(const unsigned int, const unsigned int)> FilenameFn;
typedef std::function<MetadataType(const unsigned int, const unsigned int)> MetadataFn;
public:
// constructor
A2AMatrixBlockComputation(GridBase *grid,
const unsigned int orthogDim,
const unsigned int next,
const unsigned int nstr,
const unsigned int blockSize,
const unsigned int cacheBlockSize,
TimerArray *tArray = nullptr);
// execution
void execute(const std::vector<Field> &left,
const std::vector<Field> &right,
A2AKernel<T, Field> &kernel,
const FilenameFn &ionameFn,
const FilenameFn &filenameFn,
const MetadataFn &metadataFn);
private:
// I/O handler
void saveBlock(const A2AMatrixSet<TIo> &m, IoHelper &h);
private:
TimerArray *tArray_;
GridBase *grid_;
unsigned int orthogDim_, nt_, next_, nstr_, blockSize_, cacheBlockSize_;
Vector<T> mCache_;
Vector<TIo> mBuf_;
std::vector<IoHelper> nodeIo_;
};
/******************************************************************************
* A2A matrix contraction kernels *
******************************************************************************/
class A2AContraction
{
public:
// accTrMul(acc, a, b): acc += tr(a*b)
template <typename C, typename MatLeft, typename MatRight>
static inline void accTrMul(C &acc, const MatLeft &a, const MatRight &b)
{
if ((MatLeft::Options == Eigen::RowMajor) and
(MatRight::Options == Eigen::ColMajor))
{
parallel_for (unsigned int r = 0; r < a.rows(); ++r)
{
C tmp;
#ifdef USE_MKL
dotuRow(tmp, r, a, b);
#else
tmp = a.row(r).conjugate().dot(b.col(r));
#endif
parallel_critical
{
acc += tmp;
}
}
}
else
{
parallel_for (unsigned int c = 0; c < a.cols(); ++c)
{
C tmp;
#ifdef USE_MKL
dotuCol(tmp, c, a, b);
#else
tmp = a.col(c).conjugate().dot(b.row(c));
#endif
parallel_critical
{
acc += tmp;
}
}
}
}
template <typename MatLeft, typename MatRight>
static inline double accTrMulFlops(const MatLeft &a, const MatRight &b)
{
double n = a.rows()*a.cols();
return 8.*n;
}
// mul(res, a, b): res = a*b
#ifdef USE_MKL
template <template <class, int...> class Mat, int... Opts>
static inline void mul(Mat<ComplexD, Opts...> &res,
const Mat<ComplexD, Opts...> &a,
const Mat<ComplexD, Opts...> &b)
{
static const ComplexD one(1., 0.), zero(0., 0.);
if ((res.rows() != a.rows()) or (res.cols() != b.cols()))
{
res.resize(a.rows(), b.cols());
}
if (Mat<ComplexD, Opts...>::Options == Eigen::RowMajor)
{
cblas_zgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, a.rows(), b.cols(),
a.cols(), &one, a.data(), a.cols(), b.data(), b.cols(), &zero,
res.data(), res.cols());
}
else if (Mat<ComplexD, Opts...>::Options == Eigen::ColMajor)
{
cblas_zgemm(CblasColMajor, CblasNoTrans, CblasNoTrans, a.rows(), b.cols(),
a.cols(), &one, a.data(), a.rows(), b.data(), b.rows(), &zero,
res.data(), res.rows());
}
}
template <template <class, int...> class Mat, int... Opts>
static inline void mul(Mat<ComplexF, Opts...> &res,
const Mat<ComplexF, Opts...> &a,
const Mat<ComplexF, Opts...> &b)
{
static const ComplexF one(1., 0.), zero(0., 0.);
if ((res.rows() != a.rows()) or (res.cols() != b.cols()))
{
res.resize(a.rows(), b.cols());
}
if (Mat<ComplexF, Opts...>::Options == Eigen::RowMajor)
{
cblas_cgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans, a.rows(), b.cols(),
a.cols(), &one, a.data(), a.cols(), b.data(), b.cols(), &zero,
res.data(), res.cols());
}
else if (Mat<ComplexF, Opts...>::Options == Eigen::ColMajor)
{
cblas_cgemm(CblasColMajor, CblasNoTrans, CblasNoTrans, a.rows(), b.cols(),
a.cols(), &one, a.data(), a.rows(), b.data(), b.rows(), &zero,
res.data(), res.rows());
}
}
#else
template <typename Mat>
static inline void mul(Mat &res, const Mat &a, const Mat &b)
{
res = a*b;
}
#endif
template <typename Mat>
static inline double mulFlops(const Mat &a, const Mat &b)
{
double nr = a.rows(), nc = a.cols();
return nr*nr*(6.*nc + 2.*(nc - 1.));
}
private:
template <typename C, typename MatLeft, typename MatRight>
static inline void makeDotRowPt(C * &aPt, unsigned int &aInc, C * &bPt,
unsigned int &bInc, const unsigned int aRow,
const MatLeft &a, const MatRight &b)
{
if (MatLeft::Options == Eigen::RowMajor)
{
aPt = a.data() + aRow*a.cols();
aInc = 1;
}
else if (MatLeft::Options == Eigen::ColMajor)
{
aPt = a.data() + aRow;
aInc = a.rows();
}
if (MatRight::Options == Eigen::RowMajor)
{
bPt = b.data() + aRow;
bInc = b.cols();
}
else if (MatRight::Options == Eigen::ColMajor)
{
bPt = b.data() + aRow*b.rows();
bInc = 1;
}
}
#ifdef USE_MKL
template <typename C, typename MatLeft, typename MatRight>
static inline void makeDotColPt(C * &aPt, unsigned int &aInc, C * &bPt,
unsigned int &bInc, const unsigned int aCol,
const MatLeft &a, const MatRight &b)
{
if (MatLeft::Options == Eigen::RowMajor)
{
aPt = a.data() + aCol;
aInc = a.cols();
}
else if (MatLeft::Options == Eigen::ColMajor)
{
aPt = a.data() + aCol*a.rows();
aInc = 1;
}
if (MatRight::Options == Eigen::RowMajor)
{
bPt = b.data() + aCol*b.cols();
bInc = 1;
}
else if (MatRight::Options == Eigen::ColMajor)
{
bPt = b.data() + aCol;
bInc = b.rows();
}
}
template <typename MatLeft, typename MatRight>
static inline void dotuRow(ComplexF &res, const unsigned int aRow,
const MatLeft &a, const MatRight &b)
{
const ComplexF *aPt, *bPt;
unsigned int aInc, bInc;
makeDotRowPt(aPt, aInc, bPt, bInc, aRow, a, b);
cblas_cdotu_sub(a.cols(), aPt, aInc, bPt, bInc, &res);
}
template <typename MatLeft, typename MatRight>
static inline void dotuCol(ComplexF &res, const unsigned int aCol,
const MatLeft &a, const MatRight &b)
{
const ComplexF *aPt, *bPt;
unsigned int aInc, bInc;
makeDotColPt(aPt, aInc, bPt, bInc, aCol, a, b);
cblas_cdotu_sub(a.rows(), aPt, aInc, bPt, bInc, &res);
}
template <typename MatLeft, typename MatRight>
static inline void dotuRow(ComplexD &res, const unsigned int aRow,
const MatLeft &a, const MatRight &b)
{
const ComplexD *aPt, *bPt;
unsigned int aInc, bInc;
makeDotRowPt(aPt, aInc, bPt, bInc, aRow, a, b);
cblas_zdotu_sub(a.cols(), aPt, aInc, bPt, bInc, &res);
}
template <typename MatLeft, typename MatRight>
static inline void dotuCol(ComplexD &res, const unsigned int aCol,
const MatLeft &a, const MatRight &b)
{
const ComplexD *aPt, *bPt;
unsigned int aInc, bInc;
makeDotColPt(aPt, aInc, bPt, bInc, aCol, a, b);
cblas_zdotu_sub(a.rows(), aPt, aInc, bPt, bInc, &res);
}
#endif
};
/******************************************************************************
* A2AMatrixIo template implementation *
******************************************************************************/
// constructor /////////////////////////////////////////////////////////////////
template <typename T>
A2AMatrixIo<T>::A2AMatrixIo(std::string filename, std::string dataname,
const unsigned int nt, const unsigned int ni,
const unsigned int nj)
: filename_(filename), dataname_(dataname)
, nt_(nt), ni_(ni), nj_(nj)
{}
// access //////////////////////////////////////////////////////////////////////
template <typename T>
unsigned int A2AMatrixIo<T>::getNt(void) const
{
return nt_;
}
template <typename T>
unsigned int A2AMatrixIo<T>::getNi(void) const
{
return ni_;
}
template <typename T>
unsigned int A2AMatrixIo<T>::getNj(void) const
{
return nj_;
}
template <typename T>
size_t A2AMatrixIo<T>::getSize(void) const
{
return nt_*ni_*nj_*sizeof(T);
}
// file allocation /////////////////////////////////////////////////////////////
template <typename T>
template <typename MetadataType>
void A2AMatrixIo<T>::initFile(const MetadataType &d, const unsigned int chunkSize)
{
#ifdef HAVE_HDF5
std::vector<hsize_t> dim = {static_cast<hsize_t>(nt_),
static_cast<hsize_t>(ni_),
static_cast<hsize_t>(nj_)},
chunk = {static_cast<hsize_t>(nt_),
static_cast<hsize_t>(chunkSize),
static_cast<hsize_t>(chunkSize)};
H5NS::DataSpace dataspace(dim.size(), dim.data());
H5NS::DataSet dataset;
H5NS::DSetCreatPropList plist;
// create empty file just with metadata
{
Hdf5Writer writer(filename_);
write(writer, dataname_, d);
}
// create the dataset
Hdf5Reader reader(filename_, false);
push(reader, dataname_);
auto &group = reader.getGroup();
plist.setChunk(chunk.size(), chunk.data());
plist.setFletcher32();
dataset = group.createDataSet(HADRONS_A2AM_NAME, Hdf5Type<T>::type(), dataspace, plist);
#else
HADRONS_ERROR(Implementation, "all-to-all matrix I/O needs HDF5 library");
#endif
}
// block I/O ///////////////////////////////////////////////////////////////////
template <typename T>
void A2AMatrixIo<T>::saveBlock(const T *data,
const unsigned int i,
const unsigned int j,
const unsigned int blockSizei,
const unsigned int blockSizej)
{
#ifdef HAVE_HDF5
Hdf5Reader reader(filename_, false);
std::vector<hsize_t> count = {nt_, blockSizei, blockSizej},
offset = {0, static_cast<hsize_t>(i),
static_cast<hsize_t>(j)},
stride = {1, 1, 1},
block = {1, 1, 1};
H5NS::DataSpace memspace(count.size(), count.data()), dataspace;
H5NS::DataSet dataset;
size_t shift;
push(reader, dataname_);
auto &group = reader.getGroup();
dataset = group.openDataSet(HADRONS_A2AM_NAME);
dataspace = dataset.getSpace();
dataspace.selectHyperslab(H5S_SELECT_SET, count.data(), offset.data(),
stride.data(), block.data());
dataset.write(data, Hdf5Type<T>::type(), memspace, dataspace);
#else
HADRONS_ERROR(Implementation, "all-to-all matrix I/O needs HDF5 library");
#endif
}
template <typename T>
void A2AMatrixIo<T>::saveBlock(const A2AMatrixSet<T> &m,
const unsigned int ext, const unsigned int str,
const unsigned int i, const unsigned int j)
{
unsigned int blockSizei = m.dimension(3);
unsigned int blockSizej = m.dimension(4);
unsigned int nstr = m.dimension(1);
size_t offset = (ext*nstr + str)*nt_*blockSizei*blockSizej;
saveBlock(m.data() + offset, i, j, blockSizei, blockSizej);
}
template <typename T>
template <template <class> class Vec, typename VecT>
void A2AMatrixIo<T>::load(Vec<VecT> &v, double *tRead, const bool useCache)
{
#ifdef HAVE_HDF5
Hdf5Reader reader(filename_);
std::vector<hsize_t> hdim;
H5NS::DataSet dataset;
H5NS::DataSpace dataspace;
H5NS::CompType datatype;
push(reader, dataname_);
auto &group = reader.getGroup();
dataset = group.openDataSet(HADRONS_A2AM_NAME);
datatype = dataset.getCompType();
dataspace = dataset.getSpace();
hdim.resize(dataspace.getSimpleExtentNdims());
dataspace.getSimpleExtentDims(hdim.data());
if ((nt_*ni_*nj_ != 0) and
((hdim[0] != nt_) or (hdim[1] != ni_) or (hdim[2] != nj_)))
{
HADRONS_ERROR(Size, "all-to-all matrix size mismatch (got "
+ std::to_string(hdim[0]) + "x" + std::to_string(hdim[1]) + "x"
+ std::to_string(hdim[2]) + ", expected "
+ std::to_string(nt_) + "x" + std::to_string(ni_) + "x"
+ std::to_string(nj_));
}
else if (ni_*nj_ == 0)
{
if (hdim[0] != nt_)
{
HADRONS_ERROR(Size, "all-to-all time size mismatch (got "
+ std::to_string(hdim[0]) + ", expected "
+ std::to_string(nt_) + ")");
}
ni_ = hdim[1];
nj_ = hdim[2];
}
if (useCache)
{
std::vector<T> buf(nt_*ni_*nj_);
T *pt;
dataset.read(buf.data(), datatype);
pt = buf.data();
for (unsigned int t = 0; t < nt_; ++t)
{
A2AMatrixMap<T> bufMap(pt, ni_, nj_);
v[t] = bufMap.template cast<VecT>();
pt += ni_*nj_;
}
}
// if useCache = false, do I/O timeslice per timeslice (much slower)
else
{
A2AMatrix<T> buf(ni_, nj_);
std::vector<hsize_t> count = {1, static_cast<hsize_t>(ni_),
static_cast<hsize_t>(nj_)},
stride = {1, 1, 1},
block = {1, 1, 1},
memCount = {static_cast<hsize_t>(ni_),
static_cast<hsize_t>(nj_)};
H5NS::DataSpace memspace(memCount.size(), memCount.data());
std::cout << "Loading timeslice";
std::cout.flush();
*tRead = 0.;
for (unsigned int tp1 = nt_; tp1 > 0; --tp1)
{
unsigned int t = tp1 - 1;
std::vector<hsize_t> offset = {static_cast<hsize_t>(t), 0, 0};
if (t % 10 == 0)
{
std::cout << " " << t;
std::cout.flush();
}
dataspace.selectHyperslab(H5S_SELECT_SET, count.data(), offset.data(),
stride.data(), block.data());
if (tRead) *tRead -= usecond();
dataset.read(buf.data(), datatype, memspace, dataspace);
if (tRead) *tRead += usecond();
v[t] = buf.template cast<VecT>();
}
std::cout << std::endl;
}
#else
HADRONS_ERROR(Implementation, "all-to-all matrix I/O needs HDF5 library");
#endif
}
/******************************************************************************
* A2AMatrixBlockComputation template implementation *
******************************************************************************/
// constructor /////////////////////////////////////////////////////////////////
template <typename T, typename Field, typename MetadataType, typename TIo>
A2AMatrixBlockComputation<T, Field, MetadataType, TIo>
::A2AMatrixBlockComputation(GridBase *grid,
const unsigned int orthogDim,
const unsigned int next,
const unsigned int nstr,
const unsigned int blockSize,
const unsigned int cacheBlockSize,
TimerArray *tArray)
: grid_(grid), nt_(grid->GlobalDimensions()[orthogDim]), orthogDim_(orthogDim)
, next_(next), nstr_(nstr), blockSize_(blockSize), cacheBlockSize_(cacheBlockSize)
, tArray_(tArray)
{
mCache_.resize(nt_*next_*nstr_*cacheBlockSize_*cacheBlockSize_);
mBuf_.resize(nt_*next_*nstr_*blockSize_*blockSize_);
}
#define START_TIMER(name) if (tArray_) tArray_->startTimer(name)
#define STOP_TIMER(name) if (tArray_) tArray_->stopTimer(name)
#define GET_TIMER(name) ((tArray_ != nullptr) ? tArray_->getDTimer(name) : 0.)
// execution ///////////////////////////////////////////////////////////////////
template <typename T, typename Field, typename MetadataType, typename TIo>
void A2AMatrixBlockComputation<T, Field, MetadataType, TIo>
::execute(const std::vector<Field> &left, const std::vector<Field> &right,
A2AKernel<T, Field> &kernel, const FilenameFn &ionameFn,
const FilenameFn &filenameFn, const MetadataFn &metadataFn)
{
//////////////////////////////////////////////////////////////////////////
// i,j is first loop over blockSize_ factors
// ii,jj is second loop over cacheBlockSize_ factors for high perf contractions
// iii,jjj are loops within cacheBlock
// Total index is sum of these i+ii+iii etc...
//////////////////////////////////////////////////////////////////////////
int N_i = left.size();
int N_j = right.size();
double flops, bytes, t_kernel;
double nodes = grid_->NodeCount();
int NBlock_i = N_i/blockSize_ + (((N_i % blockSize_) != 0) ? 1 : 0);
int NBlock_j = N_j/blockSize_ + (((N_j % blockSize_) != 0) ? 1 : 0);
for(int i=0;i<N_i;i+=blockSize_)
for(int j=0;j<N_j;j+=blockSize_)
{
// Get the W and V vectors for this block^2 set of terms
int N_ii = MIN(N_i-i,blockSize_);
int N_jj = MIN(N_j-j,blockSize_);
A2AMatrixSet<TIo> mBlock(mBuf_.data(), next_, nstr_, nt_, N_ii, N_jj);
LOG(Message) << "All-to-all matrix block "
<< j/blockSize_ + NBlock_j*i/blockSize_ + 1
<< "/" << NBlock_i*NBlock_j << " [" << i <<" .. "
<< i+N_ii-1 << ", " << j <<" .. " << j+N_jj-1 << "]"
<< std::endl;
// Series of cache blocked chunks of the contractions within this block
flops = 0.0;
bytes = 0.0;
t_kernel = 0.0;
for(int ii=0;ii<N_ii;ii+=cacheBlockSize_)
for(int jj=0;jj<N_jj;jj+=cacheBlockSize_)
{
double t;
int N_iii = MIN(N_ii-ii,cacheBlockSize_);
int N_jjj = MIN(N_jj-jj,cacheBlockSize_);
A2AMatrixSet<T> mCacheBlock(mCache_.data(), next_, nstr_, nt_, N_iii, N_jjj);
START_TIMER("kernel");
kernel(mCacheBlock, &left[i+ii], &right[j+jj], orthogDim_, t);
STOP_TIMER("kernel");
t_kernel += t;
flops += kernel.flops(N_iii, N_jjj);
bytes += kernel.bytes(N_iii, N_jjj);
START_TIMER("cache copy");
parallel_for_nest5(int e =0;e<next_;e++)
for(int s =0;s< nstr_;s++)
for(int t =0;t< nt_;t++)
for(int iii=0;iii< N_iii;iii++)
for(int jjj=0;jjj< N_jjj;jjj++)
{
mBlock(e,s,t,ii+iii,jj+jjj) = mCacheBlock(e,s,t,iii,jjj);
}
STOP_TIMER("cache copy");
}
// perf
LOG(Message) << "Kernel perf " << flops/t_kernel/1.0e3/nodes
<< " Gflop/s/node " << std::endl;
LOG(Message) << "Kernel perf " << bytes/t_kernel*1.0e6/1024/1024/1024/nodes
<< " GB/s/node " << std::endl;
// IO
double blockSize, ioTime;
unsigned int myRank = grid_->ThisRank(), nRank = grid_->RankCount();
LOG(Message) << "Writing block to disk" << std::endl;
ioTime = -GET_TIMER("IO: write block");
START_TIMER("IO: total");
makeFileDir(filenameFn(0, 0), grid_);
#ifdef HADRONS_A2AM_PARALLEL_IO
grid_->Barrier();
// make task list for current node
nodeIo_.clear();
for(int f = myRank; f < next_*nstr_; f += nRank)
{
IoHelper h;
h.i = i;
h.j = j;
h.e = f/nstr_;
h.s = f % nstr_;
h.io = A2AMatrixIo<TIo>(filenameFn(h.e, h.s),
ionameFn(h.e, h.s), nt_, N_i, N_j);
h.md = metadataFn(h.e, h.s);
nodeIo_.push_back(h);
}
// parallel IO
for (auto &h: nodeIo_)
{
saveBlock(mBlock, h);
}
grid_->Barrier();
#else
// serial IO, for testing purposes only
for(int e = 0; e < next_; e++)
for(int s = 0; s < nstr_; s++)
{
IoHelper h;
h.i = i;
h.j = j;
h.e = e;
h.s = s;
h.io = A2AMatrixIo<TIo>(filenameFn(h.e, h.s),
ionameFn(h.e, h.s), nt_, N_i, N_j);
h.md = metadataFn(h.e, h.s);
saveBlock(mfBlock, h);
}
#endif
STOP_TIMER("IO: total");
blockSize = static_cast<double>(next_*nstr_*nt_*N_ii*N_jj*sizeof(TIo));
ioTime += GET_TIMER("IO: write block");
LOG(Message) << "HDF5 IO done " << sizeString(blockSize) << " in "
<< ioTime << " us ("
<< blockSize/ioTime*1.0e6/1024/1024
<< " MB/s)" << std::endl;
}
}
// I/O handler /////////////////////////////////////////////////////////////////
template <typename T, typename Field, typename MetadataType, typename TIo>
void A2AMatrixBlockComputation<T, Field, MetadataType, TIo>
::saveBlock(const A2AMatrixSet<TIo> &m, IoHelper &h)
{
if ((h.i == 0) and (h.j == 0))
{
START_TIMER("IO: file creation");
h.io.initFile(h.md, blockSize_);
STOP_TIMER("IO: file creation");
}
START_TIMER("IO: write block");
h.io.saveBlock(m, h.e, h.s, h.i, h.j);
STOP_TIMER("IO: write block");
}
#undef START_TIMER
#undef STOP_TIMER
#undef GET_TIMER
END_HADRONS_NAMESPACE
#endif // A2A_Matrix_hpp_
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