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https://github.com/paboyle/Grid.git
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dc814f30da
Number of IO MPI tasks can be varied by selecting which
dimensions use parallel IO and which dimensions use Serial send to boss
I/O.
Thus can neck down from, say 1024 nodes = 4x4x8x8 to {1,8,32,64,128,256,1024} nodes
doing the I/O.
Interpolates nicely between ALL nodes write their data, a single boss per time-plane
in processor space [old UKQCD fortran code did this], and a single node doing all I/O.
Not sure I have the transfer sizes big enough and am not overly convinced fstream
is guaranteed to not give buffer inconsistencies unless I set streambuf size to zero.
Practically it has worked on 8 tasks, 2x1x2x2 writing /cloning NERSC configurations
on my MacOS + OpenMPI and Clang environment.
It is VERY easy to switch to pwrite at a later date, and also easy to send x-strips around from
each node in order to gather bigger chunks at the syscall level.
That would push us up to the circa 8x 18*4*8 == 4KB size write chunk, and by taking, say, x/y non
parallel we get to 16MB contiguous chunks written in multi 4KB transactions
per IOnode in 64^3 lattices for configuration I/O.
I suspect this is fine for system performance.
102 lines
2.7 KiB
C++
102 lines
2.7 KiB
C++
#include <Grid.h>
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using namespace std;
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using namespace Grid;
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using namespace Grid::QCD;
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int main (int argc, char ** argv)
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{
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Grid_init(&argc,&argv);
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std::vector<int> simd_layout = GridDefaultSimd(4,vComplex::Nsimd());
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std::vector<int> mpi_layout = GridDefaultMpi();
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std::vector<int> latt_size ({16,16,16,32});
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std::vector<int> clatt_size ({4,4,4,8});
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int orthodir=3;
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int orthosz =latt_size[orthodir];
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GridCartesian Fine(latt_size,simd_layout,mpi_layout);
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GridCartesian Coarse(clatt_size,simd_layout,mpi_layout);
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LatticeGaugeField Umu(&Fine);
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LatticeGaugeField Umu_diff(&Fine);
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LatticeGaugeField Umu_saved(&Fine);
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std::vector<LatticeColourMatrix> U(4,&Fine);
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NerscField header;
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std::string file("./ckpoint_lat.4000");
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NerscIO::readConfiguration(Umu,header,file);
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for(int mu=0;mu<Nd;mu++){
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U[mu] = PeekIndex<LorentzIndex>(Umu,mu);
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}
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// Painful ; fix syntactical niceness
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LatticeComplex LinkTrace(&Fine);
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LinkTrace=zero;
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for(int mu=0;mu<Nd;mu++){
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LinkTrace = LinkTrace + trace(U[mu]);
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}
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// (1+2+3)=6 = N(N-1)/2 terms
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LatticeComplex Plaq(&Fine);
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LatticeComplex cPlaq(&Coarse);
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Plaq = zero;
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#if 1
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for(int mu=1;mu<Nd;mu++){
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for(int nu=0;nu<mu;nu++){
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Plaq = Plaq + trace(U[mu]*Cshift(U[nu],mu,1)*adj(Cshift(U[mu],nu,1))*adj(U[nu]));
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}
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}
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#endif
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double vol = Fine.gSites();
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Complex PlaqScale(1.0/vol/6.0/3.0);
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std::cout<<GridLogMessage <<"PlaqScale" << PlaqScale<<std::endl;
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std::vector<TComplex> Plaq_T(orthosz);
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sliceSum(Plaq,Plaq_T,Nd-1);
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int Nt = Plaq_T.size();
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TComplex Plaq_T_sum;
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Plaq_T_sum=zero;
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for(int t=0;t<Nt;t++){
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Plaq_T_sum = Plaq_T_sum+Plaq_T[t];
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Complex Pt=TensorRemove(Plaq_T[t]);
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std::cout<<GridLogMessage << "sliced ["<<t<<"]" <<Pt*PlaqScale*Real(Nt)<<std::endl;
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}
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{
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Complex Pt = TensorRemove(Plaq_T_sum);
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std::cout<<GridLogMessage << "total " <<Pt*PlaqScale<<std::endl;
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}
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TComplex Tp = sum(Plaq);
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Complex p = TensorRemove(Tp);
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std::cout<<GridLogMessage << "calculated plaquettes " <<p*PlaqScale<<std::endl;
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Complex LinkTraceScale(1.0/vol/4.0/3.0);
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TComplex Tl = sum(LinkTrace);
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Complex l = TensorRemove(Tl);
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std::cout<<GridLogMessage << "calculated link trace " <<l*LinkTraceScale<<std::endl;
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blockSum(cPlaq,Plaq);
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TComplex TcP = sum(cPlaq);
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Complex ll= TensorRemove(TcP);
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std::cout<<GridLogMessage << "coarsened plaquettes sum to " <<ll*PlaqScale<<std::endl;
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std::string clone2x3("./ckpoint_clone2x3.4000");
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std::string clone3x3("./ckpoint_clone3x3.4000");
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int precision32 = 0;
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NerscIO::writeConfiguration(Umu,clone3x3,0,precision32);
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NerscIO::writeConfiguration(Umu,clone2x3,1,precision32);
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Grid_finalize();
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}
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