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Merge branch 'develop' of https://github.com/paboyle/Grid into specflow

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This commit is contained in:
Chulwoo Jung
2025-04-18 19:55:36 +00:00
parent 570b72a47b e652fc2825
commit cee4c8ce8c
149 changed files with 4714 additions and 3394 deletions
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9
Grid/algorithms/FFT.h
View File

@@ -168,6 +168,7 @@ public:
template<class vobj>
void FFT_dim(Lattice<vobj> &result,const Lattice<vobj> &source,int dim, int sign){
#ifndef HAVE_FFTW
std::cerr << "FFTW is not compiled but is called"<<std::endl;
assert(0);
#else
conformable(result.Grid(),vgrid);
@@ -190,7 +191,8 @@ public:
Lattice<sobj> pgbuf(&pencil_g);
autoView(pgbuf_v , pgbuf, CpuWrite);
//std::cout << "CPU view" << std::endl;
typedef typename FFTW<scalar>::FFTW_scalar FFTW_scalar;
typedef typename FFTW<scalar>::FFTW_plan FFTW_plan;
@@ -213,6 +215,7 @@ public:
else if ( sign == forward ) div = 1.0;
else assert(0);
//std::cout << GridLogPerformance<<"Making FFTW plan" << std::endl;
FFTW_plan p;
{
FFTW_scalar *in = (FFTW_scalar *)&pgbuf_v[0];
@@ -226,6 +229,7 @@ public:
}
// Barrel shift and collect global pencil
//std::cout << GridLogPerformance<<"Making pencil" << std::endl;
Coordinate lcoor(Nd), gcoor(Nd);
result = source;
int pc = processor_coor[dim];
@@ -247,6 +251,7 @@ public:
}
}
//std::cout <<GridLogPerformance<< "Looping orthog" << std::endl;
// Loop over orthog coords
int NN=pencil_g.lSites();
GridStopWatch timer;
@@ -269,6 +274,7 @@ public:
usec += timer.useconds();
flops+= flops_call*NN;
//std::cout <<GridLogPerformance<< "Writing back results " << std::endl;
// writing out result
{
autoView(pgbuf_v,pgbuf,CpuRead);
@@ -285,6 +291,7 @@ public:
}
result = result*div;
//std::cout <<GridLogPerformance<< "Destroying plan " << std::endl;
// destroying plan
FFTW<scalar>::fftw_destroy_plan(p);
#endif

32
Grid/algorithms/LinearOperator.h
View File

@@ -277,6 +277,38 @@ public:
assert(0);
}
};
template<class Matrix,class Field>
class ShiftedNonHermitianLinearOperator : public LinearOperatorBase<Field> {
Matrix &_Mat;
RealD shift;
public:
ShiftedNonHermitianLinearOperator(Matrix &Mat,RealD shft): _Mat(Mat),shift(shft){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
_Mat.Mdiag(in,out);
out = out + shift*in;
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
_Mat.Mdir(in,out,dir,disp);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
_Mat.MdirAll(in,out);
};
void Op (const Field &in, Field &out){
_Mat.M(in,out);
out = out + shift * in;
}
void AdjOp (const Field &in, Field &out){
_Mat.Mdag(in,out);
out = out + shift * in;
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
assert(0);
}
void HermOp(const Field &in, Field &out){
assert(0);
}
};
//////////////////////////////////////////////////////////
// Even Odd Schur decomp operators; there are several

157
Grid/algorithms/blas/BatchedBlas.h
View File

@@ -55,10 +55,10 @@ NAMESPACE_BEGIN(Grid);
typedef cublasHandle_t gridblasHandle_t;
#endif
#ifdef GRID_SYCL
typedef cl::sycl::queue *gridblasHandle_t;
typedef sycl::queue *gridblasHandle_t;
#endif
#ifdef GRID_ONE_MKL
typedef cl::sycl::queue *gridblasHandle_t;
typedef sycl::queue *gridblasHandle_t;
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP) && !defined(GRID_ONE_MKL)
typedef int32_t gridblasHandle_t;
@@ -89,9 +89,9 @@ public:
gridblasHandle = theGridAccelerator;
#endif
#ifdef GRID_ONE_MKL
cl::sycl::gpu_selector selector;
cl::sycl::device selectedDevice { selector };
cl::sycl::property_list q_prop{cl::sycl::property::queue::in_order()};
sycl::gpu_selector selector;
sycl::device selectedDevice { selector };
sycl::property_list q_prop{sycl::property::queue::in_order()};
gridblasHandle =new sycl::queue (selectedDevice,q_prop);
#endif
gridblasInit=1;
@@ -208,8 +208,8 @@ public:
assert(Bkn.size()==batchCount);
assert(Cmn.size()==batchCount);
assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
assert(OpB!=GridBLAS_OP_T);
//assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
//assert(OpB!=GridBLAS_OP_T);
int lda = m; // m x k column major
int ldb = k; // k x n column major
@@ -367,28 +367,67 @@ public:
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
else
eCmn = alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
else
eCmn = alpha * eAmk.adjoint() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
else
eCmn = alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
else
eCmn = alpha * eAmk * eBkn.adjoint() ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
else
eCmn = alpha * eAmk.adjoint() * eBkn.adjoint() ;
} );
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
else
eCmn = alpha * eAmk.transpose() * eBkn.transpose() ;
} );
} else {
assert(0);
@@ -414,8 +453,8 @@ public:
RealD t2=usecond();
int32_t batchCount = Amk.size();
assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
assert(OpB!=GridBLAS_OP_T);
//assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
//assert(OpB!=GridBLAS_OP_T);
int lda = m; // m x k column major
int ldb = k; // k x n column major
@@ -514,28 +553,70 @@ public:
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
else
eCmn = alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
else
eCmn = alpha * eAmk.adjoint() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
else
eCmn = alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
else
eCmn = alpha * eAmk * eBkn.adjoint() ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
else
eCmn = alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
else
eCmn = alpha * eAmk.adjoint() * eBkn.adjoint() ;
} );
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
else
eCmn = alpha * eAmk.transpose() * eBkn.transpose() ;
} );
} else {
assert(0);
@@ -661,29 +742,41 @@ public:
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
else
eCmn = alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
else
eCmn = alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
else
eCmn = alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
} );
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
else
eCmn = alpha * eAmk.transpose() * eBkn.transpose() ;
});
} else {
assert(0);
}
@@ -809,28 +902,40 @@ public:
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
else
eCmn = alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
else
eCmn = alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
else
eCmn = alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
if (std::abs(beta) != 0.0)
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
else
eCmn = alpha * eAmk.transpose() * eBkn.transpose() ;
});
} else {
assert(0);

4
Grid/algorithms/iterative/ConjugateGradientMixedPrec.h
View File

@@ -116,14 +116,14 @@ NAMESPACE_BEGIN(Grid);
//Compute double precision rsd and also new RHS vector.
Linop_d.HermOp(sol_d, tmp_d);
RealD norm = axpy_norm(src_d, -1., tmp_d, src_d_in); //src_d is residual vector
std::cout<<GridLogMessage<<" rsd norm "<<norm<<std::endl;
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Outer iteration " <<outer_iter<<" residual "<< norm<< " target "<< stop<<std::endl;
if(norm < OuterLoopNormMult * stop){
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradient: Outer iteration converged on iteration " <<outer_iter <<std::endl;
break;
}
while(norm * inner_tol * inner_tol < stop) inner_tol *= 2; // inner_tol = sqrt(stop/norm) ??
while(norm * inner_tol * inner_tol < stop*1.01) inner_tol *= 2; // inner_tol = sqrt(stop/norm) ??
PrecChangeTimer.Start();
precisionChange(src_f, src_d, pc_wk_dp_to_sp);

10
Grid/algorithms/iterative/ConjugateGradientMultiShift.h
View File

@@ -102,11 +102,11 @@ public:
assert(mass.size()==nshift);
assert(mresidual.size()==nshift);
// dynamic sized arrays on stack; 2d is a pain with vector
RealD bs[nshift];
RealD rsq[nshift];
RealD z[nshift][2];
int converged[nshift];
// remove dynamic sized arrays on stack; 2d is a pain with vector
std::vector<RealD> bs(nshift);
std::vector<RealD> rsq(nshift);
std::vector<std::array<RealD,2> > z(nshift);
std::vector<int> converged(nshift);
const int primary =0;

10
Grid/algorithms/iterative/ConjugateGradientMultiShiftCleanup.h
View File

@@ -123,11 +123,11 @@ public:
assert(mresidual.size()==nshift);
// dynamic sized arrays on stack; 2d is a pain with vector
RealD bs[nshift];
RealD rsq[nshift];
RealD rsqf[nshift];
RealD z[nshift][2];
int converged[nshift];
std::vector<RealD> bs(nshift);
std::vector<RealD> rsq(nshift);
std::vector<RealD> rsqf(nshift);
std::vector<std::array<RealD,2> > z(nshift);
std::vector<int> converged(nshift);
const int primary =0;

10
Grid/algorithms/iterative/ConjugateGradientMultiShiftMixedPrec.h
View File

@@ -156,11 +156,11 @@ public:
assert(mresidual.size()==nshift);
// dynamic sized arrays on stack; 2d is a pain with vector
RealD bs[nshift];
RealD rsq[nshift];
RealD rsqf[nshift];
RealD z[nshift][2];
int converged[nshift];
std::vector<RealD> bs(nshift);
std::vector<RealD> rsq(nshift);
std::vector<RealD> rsqf(nshift);
std::vector<std::array<RealD,2> > z(nshift);
std::vector<int> converged(nshift);
const int primary =0;

2
Grid/algorithms/iterative/PrecGeneralisedConjugateResidualNonHermitian.h
View File

@@ -74,7 +74,7 @@ public:
void operator() (const Field &src, Field &psi){
psi=Zero();
// psi=Zero();
RealD cp, ssq,rsq;
ssq=norm2(src);
rsq=Tolerance*Tolerance*ssq;

78
Grid/algorithms/multigrid/Aggregates.h
View File

@@ -30,6 +30,8 @@ Author: paboyle <paboyle@ph.ed.ac.uk>
/* END LEGAL */
#pragma once
#include <Grid/algorithms/iterative/PrecGeneralisedConjugateResidualNonHermitian.h>
NAMESPACE_BEGIN(Grid);
inline RealD AggregatePowerLaw(RealD x)
@@ -95,7 +97,7 @@ public:
RealD scale;
ConjugateGradient<FineField> CG(1.0e-2,100,false);
ConjugateGradient<FineField> CG(1.0e-3,400,false);
FineField noise(FineGrid);
FineField Mn(FineGrid);
@@ -108,7 +110,7 @@ public:
hermop.Op(noise,Mn); std::cout<<GridLogMessage << "noise ["<<b<<"] <n|MdagM|n> "<<norm2(Mn)<<std::endl;
for(int i=0;i<1;i++){
for(int i=0;i<4;i++){
CG(hermop,noise,subspace[b]);
@@ -124,6 +126,53 @@ public:
}
}
virtual void CreateSubspaceGCR(GridParallelRNG &RNG,LinearOperatorBase<FineField> &DiracOp,int nn=nbasis)
{
RealD scale;
TrivialPrecon<FineField> simple_fine;
PrecGeneralisedConjugateResidualNonHermitian<FineField> GCR(0.001,30,DiracOp,simple_fine,12,12);
FineField noise(FineGrid);
FineField src(FineGrid);
FineField guess(FineGrid);
FineField Mn(FineGrid);
for(int b=0;b<nn;b++){
subspace[b] = Zero();
gaussian(RNG,noise);
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
DiracOp.Op(noise,Mn); std::cout<<GridLogMessage << "noise ["<<b<<"] <n|Op|n> "<<innerProduct(noise,Mn)<<std::endl;
for(int i=0;i<2;i++){
// void operator() (const Field &src, Field &psi){
#if 1
std::cout << GridLogMessage << " inverting on noise "<<std::endl;
src = noise;
guess=Zero();
GCR(src,guess);
subspace[b] = guess;
#else
std::cout << GridLogMessage << " inverting on zero "<<std::endl;
src=Zero();
guess = noise;
GCR(src,guess);
subspace[b] = guess;
#endif
noise = subspace[b];
scale = std::pow(norm2(noise),-0.5);
noise=noise*scale;
}
DiracOp.Op(noise,Mn); std::cout<<GridLogMessage << "filtered["<<b<<"] <f|Op|f> "<<innerProduct(noise,Mn)<<std::endl;
subspace[b] = noise;
}
}
////////////////////////////////////////////////////////////////////////////////////////////////
// World of possibilities here. But have tried quite a lot of experiments (250+ jobs run on Summit)
// and this is the best I found
@@ -160,14 +209,21 @@ public:
int b =0;
{
ComplexD ip;
// Filter
Chebyshev<FineField> Cheb(lo,hi,orderfilter);
Cheb(hermop,noise,Mn);
// normalise
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;
hermop.Op(Mn,tmp);
ip= innerProduct(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|Op|n> "<<norm2(tmp)<<" "<<ip<<std::endl;
hermop.AdjOp(Mn,tmp);
ip = innerProduct(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|AdjOp|n> "<<norm2(tmp)<<" "<<ip<<std::endl;
b++;
}
@@ -213,8 +269,18 @@ public:
Mn=*Tnp;
scale = std::pow(norm2(Mn),-0.5); Mn=Mn*scale;
subspace[b] = Mn;
hermop.Op(Mn,tmp);
std::cout<<GridLogMessage << n<<" filt ["<<b<<"] <n|MdagM|n> "<<norm2(tmp)<<std::endl;
ComplexD ip;
hermop.Op(Mn,tmp);
ip= innerProduct(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|Op|n> "<<norm2(tmp)<<" "<<ip<<std::endl;
hermop.AdjOp(Mn,tmp);
ip = innerProduct(Mn,tmp);
std::cout<<GridLogMessage << "filt ["<<b<<"] <n|AdjOp|n> "<<norm2(tmp)<<" "<<ip<<std::endl;
b++;
}

67
Grid/algorithms/multigrid/CoarsenedMatrix.h
View File

@@ -99,7 +99,7 @@ public:
CoarseMatrix AselfInvEven;
CoarseMatrix AselfInvOdd;
Vector<RealD> dag_factor;
deviceVector<RealD> dag_factor;
///////////////////////
// Interface
@@ -124,9 +124,13 @@ public:
int npoint = geom.npoint;
typedef LatticeView<Cobj> Aview;
Vector<Aview> AcceleratorViewContainer;
deviceVector<Aview> AcceleratorViewContainer(geom.npoint);
hostVector<Aview> hAcceleratorViewContainer(geom.npoint);
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer.push_back(A[p].View(AcceleratorRead));
for(int p=0;p<geom.npoint;p++) {
hAcceleratorViewContainer[p] = A[p].View(AcceleratorRead);
acceleratorPut(AcceleratorViewContainer[p],hAcceleratorViewContainer[p]);
}
Aview *Aview_p = & AcceleratorViewContainer[0];
const int Nsimd = CComplex::Nsimd();
@@ -161,7 +165,7 @@ public:
coalescedWrite(out_v[ss](b),res);
});
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer[p].ViewClose();
for(int p=0;p<geom.npoint;p++) hAcceleratorViewContainer[p].ViewClose();
};
void Mdag (const CoarseVector &in, CoarseVector &out)
@@ -190,9 +194,14 @@ public:
int npoint = geom.npoint;
typedef LatticeView<Cobj> Aview;
Vector<Aview> AcceleratorViewContainer;
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer.push_back(A[p].View(AcceleratorRead));
deviceVector<Aview> AcceleratorViewContainer(geom.npoint);
hostVector<Aview> hAcceleratorViewContainer(geom.npoint);
for(int p=0;p<geom.npoint;p++) {
hAcceleratorViewContainer[p] = A[p].View(AcceleratorRead);
acceleratorPut(AcceleratorViewContainer[p],hAcceleratorViewContainer[p]);
}
Aview *Aview_p = & AcceleratorViewContainer[0];
const int Nsimd = CComplex::Nsimd();
@@ -201,10 +210,10 @@ public:
int osites=Grid()->oSites();
Vector<int> points(geom.npoint, 0);
for(int p=0; p<geom.npoint; p++)
points[p] = geom.points_dagger[p];
deviceVector<int> points(geom.npoint);
for(int p=0; p<geom.npoint; p++) {
acceleratorPut(points[p],geom.points_dagger[p]);
}
auto points_p = &points[0];
RealD* dag_factor_p = &dag_factor[0];
@@ -236,7 +245,7 @@ public:
coalescedWrite(out_v[ss](b),res);
});
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer[p].ViewClose();
for(int p=0;p<geom.npoint;p++) hAcceleratorViewContainer[p].ViewClose();
}
void MdirComms(const CoarseVector &in)
@@ -251,8 +260,14 @@ public:
out.Checkerboard() = in.Checkerboard();
typedef LatticeView<Cobj> Aview;
Vector<Aview> AcceleratorViewContainer;
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer.push_back(A[p].View(AcceleratorRead));
deviceVector<Aview> AcceleratorViewContainer(geom.npoint);
hostVector<Aview> hAcceleratorViewContainer(geom.npoint);
for(int p=0;p<geom.npoint;p++) {
hAcceleratorViewContainer[p] = A[p].View(AcceleratorRead);
acceleratorPut(AcceleratorViewContainer[p],hAcceleratorViewContainer[p]);
}
Aview *Aview_p = & AcceleratorViewContainer[0];
autoView( out_v , out, AcceleratorWrite);
@@ -285,7 +300,7 @@ public:
}
coalescedWrite(out_v[ss](b),res);
});
for(int p=0;p<geom.npoint;p++) AcceleratorViewContainer[p].ViewClose();
for(int p=0;p<geom.npoint;p++) hAcceleratorViewContainer[p].ViewClose();
}
void MdirAll(const CoarseVector &in,std::vector<CoarseVector> &out)
{
@@ -469,14 +484,20 @@ public:
// determine in what order we need the points
int npoint = geom.npoint-1;
Vector<int> points(npoint, 0);
for(int p=0; p<npoint; p++)
points[p] = (dag && !hermitian) ? geom.points_dagger[p] : p;
deviceVector<int> points(npoint);
for(int p=0; p<npoint; p++) {
int val = (dag && !hermitian) ? geom.points_dagger[p] : p;
acceleratorPut(points[p], val);
}
auto points_p = &points[0];
Vector<Aview> AcceleratorViewContainer;
for(int p=0;p<npoint;p++) AcceleratorViewContainer.push_back(a[p].View(AcceleratorRead));
deviceVector<Aview> AcceleratorViewContainer(geom.npoint);
hostVector<Aview> hAcceleratorViewContainer(geom.npoint);
for(int p=0;p<geom.npoint;p++) {
hAcceleratorViewContainer[p] = a[p].View(AcceleratorRead);
acceleratorPut(AcceleratorViewContainer[p],hAcceleratorViewContainer[p]);
}
Aview *Aview_p = & AcceleratorViewContainer[0];
const int Nsimd = CComplex::Nsimd();
@@ -539,7 +560,7 @@ public:
});
}
for(int p=0;p<npoint;p++) AcceleratorViewContainer[p].ViewClose();
for(int p=0;p<npoint;p++) hAcceleratorViewContainer[p].ViewClose();
}
CoarsenedMatrix(GridCartesian &CoarseGrid, int hermitian_=0) :
@@ -590,11 +611,13 @@ public:
}
// GPU readable prefactor
std::vector<RealD> h_dag_factor(nbasis*nbasis);
thread_for(i, nbasis*nbasis, {
int j = i/nbasis;
int k = i%nbasis;
dag_factor[i] = dag_factor_eigen(j, k);
h_dag_factor[i] = dag_factor_eigen(j, k);
});
acceleratorCopyToDevice(&h_dag_factor[0],&dag_factor[0],dag_factor.size()*sizeof(RealD));
}
void CoarsenOperator(GridBase *FineGrid,LinearOperatorBase<Lattice<Fobj> > &linop,

22
Grid/algorithms/multigrid/GeneralCoarsenedMatrix.h
View File

@@ -441,8 +441,20 @@ public:
std::cout << GridLogMessage<<"CoarsenOperator inv "<<tinv<<" us"<<std::endl;
}
#else
//////////////////////////////////////////////////////////////////////
// Galerkin projection of matrix
//////////////////////////////////////////////////////////////////////
void CoarsenOperator(LinearOperatorBase<Lattice<Fobj> > &linop,
Aggregation<Fobj,CComplex,nbasis> & Subspace)
{
CoarsenOperator(linop,Subspace,Subspace);
}
//////////////////////////////////////////////////////////////////////
// Petrov - Galerkin projection of matrix
//////////////////////////////////////////////////////////////////////
void CoarsenOperator(LinearOperatorBase<Lattice<Fobj> > &linop,
Aggregation<Fobj,CComplex,nbasis> & U,
Aggregation<Fobj,CComplex,nbasis> & V)
{
std::cout << GridLogMessage<< "GeneralCoarsenMatrix "<< std::endl;
GridBase *grid = FineGrid();
@@ -458,11 +470,9 @@ public:
// Orthogonalise the subblocks over the basis
/////////////////////////////////////////////////////////////
CoarseScalar InnerProd(CoarseGrid());
blockOrthogonalise(InnerProd,Subspace.subspace);
blockOrthogonalise(InnerProd,V.subspace);
blockOrthogonalise(InnerProd,U.subspace);
// for(int s=0;s<Subspace.subspace.size();s++){
// std::cout << " subspace norm "<<norm2(Subspace.subspace[s])<<std::endl;
// }
const int npoint = geom.npoint;
Coordinate clatt = CoarseGrid()->GlobalDimensions();
@@ -542,7 +552,7 @@ public:
std::cout << GridLogMessage<< "CoarsenMatrixColoured vec "<<i<<"/"<<nbasis<< std::endl;
for(int p=0;p<npoint;p++){ // Loop over momenta in npoint
tphaseBZ-=usecond();
phaV = phaF[p]*Subspace.subspace[i];
phaV = phaF[p]*V.subspace[i];
tphaseBZ+=usecond();
/////////////////////////////////////////////////////////////////////
@@ -555,7 +565,7 @@ public:
// std::cout << i << " " <<p << " MphaV "<<norm2(MphaV)<<" "<<norm2(phaV)<<std::endl;
tproj-=usecond();
blockProject(coarseInner,MphaV,Subspace.subspace);
blockProject(coarseInner,MphaV,U.subspace);
coarseInner = conjugate(pha[p]) * coarseInner;
ComputeProj[p] = coarseInner;