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mirror of https://github.com/paboyle/Grid.git synced 2025-04-10 06:00:45 +01:00

Much faster coarsening

This commit is contained in:
Peter Boyle 2020-01-27 13:43:19 -05:00
parent 114db3b99d
commit 76c823781e

View File

@ -1,3 +1,14 @@
// blockZaxpy in bockPromote - 3s, 5%
// noncoalesced linalg in Preconditionoer ~ 3s 5%
// Lancos tuning or replace 10-20s ~ 25%, open ended
// setup tuning 5s ~ 8%
// -- e.g. ordermin, orderstep tunables.
// MdagM path without norm in LinOp code. few seconds
// Mdir calc blocking kernels
// Fuse kernels in blockMaskedInnerProduct
// preallocate Vectors in Cayley 5D ~ few percent few seconds
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
@ -34,6 +45,34 @@ Author: paboyle <paboyle@ph.ed.ac.uk>
NAMESPACE_BEGIN(Grid);
template<class vobj,class CComplex>
inline void blockMaskedInnerProduct(Lattice<CComplex> &CoarseInner1,
Lattice<CComplex> &CoarseInner2,
const Lattice<decltype(innerProduct(vobj(),vobj()))> &FineMask1,
const Lattice<decltype(innerProduct(vobj(),vobj()))> &FineMask2,
const Lattice<vobj> &fineX,
const Lattice<vobj> &fineY)
{
typedef decltype(innerProduct(vobj(),vobj())) dotp;
GridBase *coarse(CoarseInner1.Grid());
GridBase *fine (fineX.Grid());
Lattice<dotp> fine_inner(fine); fine_inner.Checkerboard() = fineX.Checkerboard();
Lattice<dotp> fine_inner_msk(fine);
// Multiply could be fused with innerProduct
// Single block sum kernel could do both masks.
fine_inner = localInnerProduct(fineX,fineY);
mult(fine_inner_msk, fine_inner,FineMask1);
blockSum(CoarseInner1,fine_inner_msk);
mult(fine_inner_msk, fine_inner,FineMask2);
blockSum(CoarseInner2,fine_inner_msk);
}
class Geometry {
public:
int npoint;
@ -51,10 +90,10 @@ public:
directions.resize(npoint);
displacements.resize(npoint);
for(int d=0;d<_d;d++){
directions[2*d ] = d+base;
directions[2*d+1] = d+base;
displacements[2*d ] = +1;
displacements[2*d+1] = -1;
directions[d ] = d+base;
directions[d+_d] = d+base;
displacements[d ] = +1;
displacements[d+_d]= -1;
}
directions [2*_d]=0;
displacements[2*_d]=0;
@ -136,20 +175,15 @@ public:
std::cout<<GridLogMessage <<"CheckOrthog done"<<std::endl;
}
void ProjectToSubspace(CoarseVector &CoarseVec,const FineField &FineVec){
// std::cout << GridLogMessage<< "BlockPromote"<<std::endl;
blockProject(CoarseVec,FineVec,subspace);
// std::cout << GridLogMessage<< "BlockPromote"<<std::endl;
}
void PromoteFromSubspace(const CoarseVector &CoarseVec,FineField &FineVec){
FineVec.Checkerboard() = subspace[0].Checkerboard();
// std::cout << GridLogMessage<< "BlockPromote"<<std::endl;
blockPromote(CoarseVec,FineVec,subspace);
// std::cout << GridLogMessage<< "BlockPromote done"<<std::endl;
}
void CreateSubspaceRandom(GridParallelRNG &RNG){
for(int i=0;i<nbasis;i++){
random(RNG,subspace[i]);
// std::cout<<GridLogMessage<<" norm subspace["<<i<<"] "<<norm2(subspace[i])<<std::endl;
}
}
@ -190,12 +224,15 @@ public:
// World of possibilities here. But have tried quite a lot of experiments (250+ jobs run on Summit)
// and this is the best I found
////////////////////////////////////////////////////////////////////////////////////////////////
#if 1
virtual void CreateSubspaceChebyshev(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
int nn,
double hi,
double lo,
int order,
int orderstep
int orderfilter,
int ordermin,
int orderstep,
double filterlo
) {
RealD scale;
@ -215,7 +252,7 @@ public:
int b =0;
{
// Filter
Chebyshev<FineField> Cheb(lo,hi,order);
Chebyshev<FineField> Cheb(lo,hi,orderfilter);
Cheb(hermop,noise,Mn);
// normalise
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
@ -227,7 +264,7 @@ public:
// Generate a full sequence of Chebyshevs
{
lo=0;
lo=filterlo;
noise=Mn;
FineField T0(FineGrid); T0 = noise;
@ -245,7 +282,7 @@ public:
hermop.HermOp(T0,y);
T1=y*xscale+noise*mscale;
for(int n=2;n<=orderstep*(nn-1);n++){
for(int n=2;n<=ordermin+orderstep*(nn-2);n++){
hermop.HermOp(*Tn,y);
@ -253,6 +290,7 @@ public:
auto Tn_v = Tn->View();
auto Tnp_v = Tnp->View();
auto Tnm_v = Tnm->View();
const int Nsimd = CComplex::Nsimd();
accelerator_forNB(ss, FineGrid->oSites(), Nsimd, {
coalescedWrite(y_v[ss],xscale*y_v(ss)+mscale*Tn_v(ss));
coalescedWrite(Tnp_v[ss],2.0*y_v(ss)-Tnm_v(ss));
@ -260,12 +298,14 @@ public:
// Possible more fine grained control is needed than a linear sweep,
// but huge productivity gain if this is simple algorithm and not a tunable
if ( (n%orderstep)==0 ) {
int m =1;
if ( n>=ordermin ) m=n-ordermin;
if ( (m%orderstep)==0 ) {
Mn=*Tnp;
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
std::cout<<GridLogMessage << n<<" filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
b++;
}
@ -279,6 +319,202 @@ public:
}
assert(b==nn);
}
#endif
#if 0
virtual void CreateSubspaceChebyshev(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
int nn,
double hi,
double lo,
int orderfilter,
int ordermin,
int orderstep,
double filterlo
) {
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
FineField combined(FineGrid);
// New normalised noise
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
// Initial matrix element
hermop.Op(noise,Mn); std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
int b =0;
#define FILTERb(llo,hhi,oorder) \
{ \
Chebyshev<FineField> Cheb(llo,hhi,oorder); \
Cheb(hermop,noise,Mn); \
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale; \
subspace[b] = Mn; \
hermop.Op(Mn,tmp); \
std::cout<<GridLogMessage << oorder<< " Cheb filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl; \
b++; \
}
// JacobiPolynomial<FineField> Cheb(0.002,60.0,1500,-0.5,3.5); \
RealD alpha=-0.8;
RealD beta =-0.8;
#define FILTER(llo,hhi,oorder) \
{ \
Chebyshev<FineField> Cheb(llo,hhi,oorder); \
/* JacobiPolynomial<FineField> Cheb(0.0,60.0,oorder,alpha,beta);*/\
Cheb(hermop,noise,Mn); \
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale; \
subspace[b] = Mn; \
hermop.Op(Mn,tmp); \
std::cout<<GridLogMessage << oorder<< "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl; \
b++; \
}
#define FILTERc(llo,hhi,oorder) \
{ \
Chebyshev<FineField> Cheb(llo,hhi,oorder); \
Cheb(hermop,noise,combined); \
}
double node = 0.000;
FILTERb(lo,hi,orderfilter);// 0
// FILTERc(node,hi,51);// 0
noise = Mn;
int base = 0;
int mult = 100;
FILTER(node,hi,base+1*mult);
FILTER(node,hi,base+2*mult);
FILTER(node,hi,base+3*mult);
FILTER(node,hi,base+4*mult);
FILTER(node,hi,base+5*mult);
FILTER(node,hi,base+6*mult);
FILTER(node,hi,base+7*mult);
FILTER(node,hi,base+8*mult);
FILTER(node,hi,base+9*mult);
FILTER(node,hi,base+10*mult);
FILTER(node,hi,base+11*mult);
FILTER(node,hi,base+12*mult);
FILTER(node,hi,base+13*mult);
FILTER(node,hi,base+14*mult);
FILTER(node,hi,base+15*mult);
assert(b==nn);
}
#endif
#if 0
virtual void CreateSubspaceChebyshev(GridParallelRNG &RNG,LinearOperatorBase<FineField> &hermop,
int nn,
double hi,
double lo,
int orderfilter,
int ordermin,
int orderstep,
double filterlo
) {
RealD scale;
FineField noise(FineGrid);
FineField Mn(FineGrid);
FineField tmp(FineGrid);
FineField combined(FineGrid);
// New normalised noise
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
// Initial matrix element
hermop.Op(noise,Mn); std::cout<<GridLogMessage << "noise <n|MdagM|n> "<<norm2(Mn)<<std::endl;
int b =0;
{
Chebyshev<FineField> JacobiPoly(0.005,60.,1500);
// JacobiPolynomial<FineField> JacobiPoly(0.002,60.0,1500,-0.5,3.5);
//JacobiPolynomial<FineField> JacobiPoly(0.03,60.0,500,-0.5,3.5);
// JacobiPolynomial<FineField> JacobiPoly(0.00,60.0,1000,-0.5,3.5);
JacobiPoly(hermop,noise,Mn);
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
b++;
// scale = std::pow(norm2(tmp),-0.5); tmp=tmp*scale;
// subspace[b] = tmp; b++;
// }
}
#define FILTER(lambda) \
{ \
hermop.HermOp(subspace[0],tmp); \
tmp = tmp - lambda *subspace[0]; \
scale = std::pow(norm2(tmp),-0.5); \
tmp=tmp*scale; \
subspace[b] = tmp; \
hermop.Op(subspace[b],tmp); \
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl; \
b++; \
}
// scale = std::pow(norm2(tmp),-0.5); tmp=tmp*scale;
// subspace[b] = tmp; b++;
// }
FILTER(2.0e-5);
FILTER(2.0e-4);
FILTER(4.0e-4);
FILTER(8.0e-4);
FILTER(8.0e-4);
FILTER(2.0e-3);
FILTER(3.0e-3);
FILTER(4.0e-3);
FILTER(5.0e-3);
FILTER(6.0e-3);
FILTER(2.5e-3);
FILTER(3.5e-3);
FILTER(4.5e-3);
FILTER(5.5e-3);
FILTER(6.5e-3);
// FILTER(6.0e-5);//6
// FILTER(7.0e-5);//8
// FILTER(8.0e-5);//9
// FILTER(9.0e-5);//3
/*
// FILTER(1.0e-4);//10
FILTER(2.0e-4);//11
// FILTER(3.0e-4);//12
// FILTER(4.0e-4);//13
FILTER(5.0e-4);//14
FILTER(6.0e-3);//4
FILTER(7.0e-4);//1
FILTER(8.0e-4);//7
FILTER(9.0e-4);//15
FILTER(1.0e-3);//2
FILTER(2.0e-3);//2
FILTER(3.0e-3);//2
FILTER(4.0e-3);//2
FILTER(5.0e-3);//2
FILTER(6.0e-3);//2
FILTER(7.0e-3);//2
FILTER(8.0e-3);//2
FILTER(1.0e-2);//2
*/
std::cout << GridLogMessage <<"Jacobi filtering done" <<std::endl;
assert(b==nn);
}
#endif
};
// Fine Object == (per site) type of fine field
@ -287,7 +523,8 @@ template<class Fobj,class CComplex,int nbasis>
class CoarsenedMatrix : public SparseMatrixBase<Lattice<iVector<CComplex,nbasis > > > {
public:
typedef iVector<CComplex,nbasis > siteVector;
typedef iVector<CComplex,nbasis > siteVector;
typedef Lattice<CComplex > CoarseComplexField;
typedef Lattice<siteVector> CoarseVector;
typedef Lattice<iMatrix<CComplex,nbasis > > CoarseMatrix;
typedef iMatrix<CComplex,nbasis > Cobj;
@ -304,7 +541,6 @@ public:
CartesianStencil<siteVector,siteVector,int> Stencil;
std::vector<CoarseMatrix> A;
///////////////////////
// Interface
@ -316,7 +552,6 @@ public:
conformable(_grid,in.Grid());
conformable(in.Grid(),out.Grid());
// RealD Nin = norm2(in);
SimpleCompressor<siteVector> compressor;
@ -333,16 +568,14 @@ public:
Aview *Aview_p = & AcceleratorViewContainer[0];
const int Nsimd = CComplex::Nsimd();
typedef decltype(coalescedRead(in_v[0])) calcVector;
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
GridStopWatch ArithmeticTimer;
int osites=Grid()->oSites();
double flops = osites*Nsimd*nbasis*nbasis*8.0*geom.npoint;
double bytes = osites*nbasis*nbasis*geom.npoint*sizeof(CComplex);
// double flops = osites*Nsimd*nbasis*nbasis*8.0*geom.npoint;
// double bytes = osites*nbasis*nbasis*geom.npoint*sizeof(CComplex);
double usecs =-usecond();
// assert(geom.npoint==9);
accelerator_for(sss, Grid()->oSites()*nbasis, Nsimd, {
@ -418,7 +651,37 @@ public:
auto out_v = out.View();
auto in_v = in.View();
const int Nsimd = CComplex::Nsimd();
typedef decltype(coalescedRead(in_v[0])) calcVector;
typedef decltype(coalescedRead(in_v[0](0))) calcComplex;
accelerator_for(sss, Grid()->oSites()*nbasis, Nsimd, {
int ss = sss/nbasis;
int b = sss%nbasis;
calcComplex res = Zero();
calcVector nbr;
int ptype;
StencilEntry *SE;
int lane=SIMTlane(Nsimd);
SE=Stencil.GetEntry(ptype,point,ss);
if(SE->_is_local) {
nbr = coalescedReadPermute(in_v[SE->_offset],ptype,SE->_permute,lane);
} else {
nbr = coalescedRead(Stencil.CommBuf()[SE->_offset],lane);
}
synchronise();
for(int bb=0;bb<nbasis;bb++) {
res = res + coalescedRead(Aview_p[point][ss](b,bb))*nbr(bb);
}
coalescedWrite(out_v[ss](b),res,lane);
});
#if 0
accelerator_for(ss,Grid()->oSites(),1,{
siteVector res = Zero();
siteVector nbr;
int ptype;
@ -433,18 +696,23 @@ public:
} else {
nbr = Stencil.CommBuf()[SE->_offset];
}
synchronise();
res = res + Aview_p[point][ss]*nbr;
out_v[ss]=res;
});
#endif
}
void MdirAll(const CoarseVector &in,std::vector<CoarseVector> &out)
{
this->MdirComms(in);
int ndir=geom.npoint-1;
assert(out.size()==ndir);
if ((out.size()!=ndir)&&(out.size()!=ndir+1)) {
std::cout <<"MdirAll out size "<< out.size()<<std::endl;
std::cout <<"MdirAll ndir "<< ndir<<std::endl;
assert(0);
}
for(int p=0;p<ndir;p++){
MdirCalc(in,out[p],p);
}
@ -496,28 +764,45 @@ public:
geom(CoarseGrid._ndimension),
hermitian(hermitian_),
Stencil(&CoarseGrid,geom.npoint,Even,geom.directions,geom.displacements,0),
A(geom.npoint,&CoarseGrid)
A(geom.npoint,&CoarseGrid)
{
};
void CoarsenOperator(GridBase *FineGrid,LinearOperatorBase<Lattice<Fobj> > &linop,
Aggregation<Fobj,CComplex,nbasis> & Subspace){
Aggregation<Fobj,CComplex,nbasis> & Subspace)
{
typedef Lattice<typename Fobj::tensor_reduced> FineComplexField;
typedef typename Fobj::scalar_type scalar_type;
FineField iblock(FineGrid); // contributions from within this block
FineField oblock(FineGrid); // contributions from outwith this block
FineComplexField one(FineGrid); one=scalar_type(1.0,0.0);
FineComplexField zero(FineGrid); zero=scalar_type(0.0,0.0);
std::vector<FineComplexField> masks(geom.npoint,FineGrid);
FineComplexField imask(FineGrid); // contributions from within this block
FineComplexField omask(FineGrid); // contributions from outwith this block
FineComplexField evenmask(FineGrid);
FineComplexField oddmask(FineGrid);
FineField phi(FineGrid);
FineField tmp(FineGrid);
FineField zz(FineGrid); zz=Zero();
FineField Mphi(FineGrid);
FineField Mphie(FineGrid);
FineField Mphio(FineGrid);
std::vector<FineField> Mphi_p(geom.npoint,FineGrid);
Lattice<iScalar<vInteger> > coor(FineGrid);
Lattice<iScalar<vInteger> > coor (FineGrid);
Lattice<iScalar<vInteger> > bcoor(FineGrid);
Lattice<iScalar<vInteger> > bcb (FineGrid);
CoarseVector iProj(Grid());
CoarseVector oProj(Grid());
CoarseScalar InnerProd(Grid());
CoarseVector SelfProj(Grid());
CoarseComplexField iZProj(Grid());
CoarseComplexField oZProj(Grid());
CoarseScalar InnerProd(Grid());
// Orthogonalise the subblocks over the basis
blockOrthogonalise(InnerProd,Subspace.subspace);
@ -525,22 +810,46 @@ public:
// Compute the matrix elements of linop between this orthonormal
// set of vectors.
int self_stencil=-1;
for(int p=0;p<geom.npoint;p++){
for(int p=0;p<geom.npoint;p++)
{
int dir = geom.directions[p];
int disp = geom.displacements[p];
A[p]=Zero();
if( geom.displacements[p]==0){
self_stencil=p;
}
Integer block=(FineGrid->_rdimensions[dir])/(Grid()->_rdimensions[dir]);
LatticeCoordinate(coor,dir);
///////////////////////////////////////////////////////
// Work out even and odd block checkerboarding for fast diagonal term
///////////////////////////////////////////////////////
if ( disp==1 ) {
bcb = bcb + div(coor,block);
}
if ( disp==0 ) {
masks[p]= Zero();
} else if ( disp==1 ) {
masks[p] = where(mod(coor,block)==(block-1),one,zero);
} else if ( disp==-1 ) {
masks[p] = where(mod(coor,block)==(Integer)0,one,zero);
}
}
evenmask = where(mod(bcb,2)==(Integer)0,one,zero);
oddmask = one-evenmask;
assert(self_stencil!=-1);
for(int i=0;i<nbasis;i++){
phi=Subspace.subspace[i];
std::cout << GridLogMessage<< "CoarsenMatrix vector "<<i<<" OpDir " << std::endl;
// std::cout << GridLogMessage<< "CoarsenMatrix vector "<<i << std::endl;
linop.OpDirAll(phi,Mphi_p);
std::cout << GridLogMessage<< "CoarsenMatrix vector "<<i<<" OpDir calculated" << std::endl;
linop.OpDiag (phi,Mphi_p[geom.npoint-1]);
std::cout << GridLogMessage<< "CoarsenMatrix vector "<<i<<" OpDiag calculated" << std::endl;
for(int p=0;p<geom.npoint;p++){
@ -549,54 +858,66 @@ public:
int dir = geom.directions[p];
int disp = geom.displacements[p];
Integer block=(FineGrid->_rdimensions[dir])/(Grid()->_rdimensions[dir]);
if ( (disp==-1) || (!hermitian ) ) {
LatticeCoordinate(coor,dir);
////////////////////////////////////////////////////////////////////////
// Pick out contributions coming from this cell and neighbour cell
////////////////////////////////////////////////////////////////////////
omask = masks[p];
imask = one-omask;
for(int j=0;j<nbasis;j++){
blockMaskedInnerProduct(iZProj,oZProj,imask,omask,Subspace.subspace[j],Mphi);
auto iZProj_v = iZProj.View() ;
auto oZProj_v = oZProj.View() ;
auto A_p = A[p].View();
auto A_self = A[self_stencil].View();
accelerator_for(ss, Grid()->oSites(), Fobj::Nsimd(),{ coalescedWrite(A_p[ss](j,i),oZProj_v(ss)); });
////////////////////////////////////////////////////////////////////////
// Pick out contributions coming from this cell and neighbour cell
////////////////////////////////////////////////////////////////////////
if ( disp==0 ) {
iblock = Mphi;
oblock = Zero();
} else if ( disp==1 ) {
oblock = where(mod(coor,block)==(block-1),Mphi,zz);
iblock = where(mod(coor,block)!=(block-1),Mphi,zz);
} else if ( disp==-1 ) {
oblock = where(mod(coor,block)==(Integer)0,Mphi,zz);
iblock = where(mod(coor,block)!=(Integer)0,Mphi,zz);
} else {
assert(0);
}
}
}
///////////////////////////////////////////
// Faster alternate self coupling.. use hermiticity to save 2x
///////////////////////////////////////////
{
mult(tmp,phi,evenmask); linop.Op(tmp,Mphie);
mult(tmp,phi,oddmask ); linop.Op(tmp,Mphio);
// tmp = Mphie*evenmask + Mphio*oddmask;
{
auto tmp_ = tmp.View();
auto evenmask_ = evenmask.View();
auto oddmask_ = oddmask.View();
auto Mphie_ = Mphie.View();
auto Mphio_ = Mphio.View();
accelerator_for(ss, FineGrid->oSites(), Fobj::Nsimd(),{
coalescedWrite(tmp_[ss],evenmask_(ss)*Mphie_(ss) + oddmask_(ss)*Mphio_(ss));
});
}
// Could do local inner products,
// and then block pick the IP's.
// Ideally write a routine to do two masked block sums at once
std::cout << GridLogMessage<< "CoarsenMatrix picked "<<p<< std::endl;
Subspace.ProjectToSubspace(iProj,iblock);
Subspace.ProjectToSubspace(oProj,oblock);
std::cout << GridLogMessage<< "CoarsenMatrix projected"<<p<< std::endl;
blockProject(SelfProj,tmp,Subspace.subspace);
// 4x gain possible in this loop. Profile and identify time loss.
// i) Assume Hermiticity, upper diagonal only (2x)
// ii) Local inner product, then pick the local inners and sum. (2x)
auto iProj_v = iProj.View() ;
auto oProj_v = oProj.View() ;
auto A_p = A[p].View();
auto SelfProj_ = SelfProj.View();
auto A_self = A[self_stencil].View();
accelerator_for(ss, Grid()->oSites(),1,{
accelerator_for(ss, Grid()->oSites(), Fobj::Nsimd(),{
for(int j=0;j<nbasis;j++){
if( disp!= 0 ) {
A_p[ss](j,i) = oProj_v[ss](j);
}
A_self[ss](j,i) = A_self[ss](j,i) + iProj_v[ss](j);
coalescedWrite(A_self[ss](j,i), SelfProj_(ss)(j));
}
});
}
}
if(hermitian) {
std::cout << GridLogMessage << " ForceHermitian "<<std::endl;
ForceHermitian();
}
// AssertHermitian();
// ForceDiagonal();
}
#if 0
///////////////////////////
@ -619,25 +940,26 @@ public:
std::cout<<GridLogMessage<< iProj <<std::endl;
std::cout<<GridLogMessage<<"Computed Coarse Operator"<<std::endl;
#endif
/*
if(hermitian) {
std::cout << GridLogMessage << " ForceHermitian "<<std::endl;
ForceHermitian();
}
for(int p=0;p<geom.npoint;p++){
std::cout << GridLogMessage<< " dir "<< norm2(A[p]) <<std::endl;
}
*/
// AssertHermitian();
// ForceDiagonal();
}
void ForceHermitian(void) {
for(int d=0;d<4;d++){
int dd=d+1;
A[2*d] = adj(Cshift(A[2*d+1],dd,1));
CoarseMatrix Diff (Grid());
for(int p=0;p<geom.npoint;p++){
int dir = geom.directions[p];
int disp = geom.displacements[p];
if(disp==-1) {
// Find the opposite link
for(int pp=0;pp<geom.npoint;pp++){
int dirp = geom.directions[pp];
int dispp = geom.displacements[pp];
if ( (dirp==dir) && (dispp==1) ){
// Diff = adj(Cshift(A[p],dir,1)) - A[pp];
// std::cout << GridLogMessage<<" Replacing stencil leg "<<pp<<" with leg "<<p<< " diff "<<norm2(Diff) <<std::endl;
A[pp] = adj(Cshift(A[p],dir,1));
}
}
}
}
// A[8] = 0.5*(A[8] + adj(A[8]));
}
void AssertHermitian(void) {
CoarseMatrix AA (Grid());