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Binary IO file for generic Grid array parallel I/O.

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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.
This commit is contained in:
Peter Boyle
2015-08-26 13:40:29 +01:00
parent 612957f057
commit dc814f30da
14 changed files with 840 additions and 410 deletions
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16
lib/qcd/utils/WilsonLoops.h
View File

@ -68,6 +68,22 @@ public:
return sumplaq/vol/faces/Nc; // Nd , Nc dependent... FIXME
}
static RealD linkTrace(const GaugeLorentz &Umu){
std::vector<GaugeMat> U(4,Umu._grid);
LatticeComplex Tr(Umu._grid); Tr=zero;
for(int mu=0;mu<Nd;mu++){
U[mu] = PeekIndex<LorentzIndex>(Umu,mu);
Tr = Tr+trace(U[mu]);
}
TComplex Tp = sum(Tr);
Complex p = TensorRemove(Tp);
double vol = Umu._grid->gSites();
return p.real()/vol/4.0/3.0;
};
//////////////////////////////////////////////////
// the sum over all staples on each site
//////////////////////////////////////////////////