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Added configure flag for LAPACK. Tested ImplicitlyRestartedLanczos::calc()

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Checking in before cleaning up
This commit is contained in:
Jung
2016-02-20 02:50:32 -05:00
parent bd84c23298
commit 9f0d9ade68
10 changed files with 212 additions and 52 deletions
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9
lib/algorithms/LinearOperator.h
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@ -222,6 +222,7 @@ namespace Grid {
SchurDiagMooeeOperator (Matrix &Mat): _Mat(Mat){};
virtual RealD Mpc (const Field &in, Field &out) {
Field tmp(in._grid);
// std::cout <<"grid pointers: in._grid="<< in._grid << " out._grid=" << out._grid << " _Mat.Grid=" << _Mat.Grid() << " _Mat.RedBlackGrid=" << _Mat.RedBlackGrid() << std::endl;
_Mat.Meooe(in,tmp);
_Mat.MooeeInv(tmp,out);
@ -251,10 +252,10 @@ namespace Grid {
virtual RealD Mpc (const Field &in, Field &out) {
Field tmp(in._grid);
_Mat.Meooe(in,tmp);
_Mat.MooeeInv(tmp,out);
_Mat.Meooe(out,tmp);
_Mat.MooeeInv(tmp,out);
_Mat.Meooe(in,out);
_Mat.MooeeInv(out,tmp);
_Mat.Meooe(tmp,out);
_Mat.MooeeInv(out,tmp);
return axpy_norm(out,-1.0,tmp,in);
}

2
lib/algorithms/approx/Chebyshev.h
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@ -198,6 +198,8 @@ namespace Grid {
void operator() (LinearOperatorBase<Field> &Linop, const Field &in, Field &out) {
GridBase *grid=in._grid;
//std::cout << "Chevyshef(): in._grid="<<in._grid<<std::endl;
//<<" Linop.Grid()="<<Linop.Grid()<<"Linop.RedBlackGrid()="<<Linop.RedBlackGrid()<<std::endl;
int vol=grid->gSites();

2
lib/algorithms/iterative/ConjugateGradientMultiShift.h
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@ -274,7 +274,7 @@ void operator() (LinearOperatorBase<Field> &Linop, const Field &src, std::vector
}
// ugly hack
std::cout<<GridLogMessage<<"CG multi shift did not converge"<<std::endl;
assert(0);
// assert(0);
}
};

127
lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
View File

@ -30,7 +30,9 @@ Author: paboyle <paboyle@ph.ed.ac.uk>
#define GRID_IRL_H
#include <string.h> //memset
#include <lapacke.h> //memset
#ifdef USE_LAPACK
#include <lapacke.h>
#endif
#include <algorithms/iterative/DenseMatrix.h>
#include <algorithms/iterative/EigenSort.h>
@ -60,7 +62,7 @@ public:
SortEigen<Field> _sort;
GridCartesian &_fgrid;
// GridCartesian &_fgrid;
LinearOperatorBase<Field> &_Linop;
@ -72,14 +74,14 @@ public:
void init(void){};
void Abort(int ff, DenseVector<RealD> &evals, DenseVector<DenseVector<RealD> > &evecs);
ImplicitlyRestartedLanczos(GridCartesian &fgrid, LinearOperatorBase<Field> &Linop, // op
ImplicitlyRestartedLanczos(
LinearOperatorBase<Field> &Linop, // op
OperatorFunction<Field> & poly, // polynmial
int _Nstop, // sought vecs
int _Nk, // sought vecs
int _Nm, // spare vecs
RealD _eresid, // resid in lmdue deficit
int _Niter) : // Max iterations
_fgrid(fgrid),
_Linop(Linop),
_poly(poly),
Nstop(_Nstop),
@ -91,6 +93,24 @@ public:
Np = Nm-Nk; assert(Np>0);
};
ImplicitlyRestartedLanczos(
LinearOperatorBase<Field> &Linop, // op
OperatorFunction<Field> & poly, // polynmial
int _Nk, // sought vecs
int _Nm, // spare vecs
RealD _eresid, // resid in lmdue deficit
int _Niter) : // Max iterations
_Linop(Linop),
_poly(poly),
Nstop(_Nk),
Nk(_Nk),
Nm(_Nm),
eresid(_eresid),
Niter(_Niter)
{
Np = Nm-Nk; assert(Np>0);
};
/////////////////////////
// Sanity checked this routine (step) against Saad.
/////////////////////////
@ -228,16 +248,17 @@ public:
}
}
//int lapackcj_Wilkinson(Matrix<T> &AH, vector<T> &tevals, vector<vector<T> > &tevecs, double small) {
#ifdef USE_LAPACK
void diagonalize_lapack(DenseVector<RealD>& lmd,
DenseVector<RealD>& lme,
int Nm2,
int Nm,
DenseVector<RealD>& Qt){
int N1,
int N2,
DenseVector<RealD>& Qt,
GridBase *grid){
const int size = Nm;
// tevals.resize(size);
// tevecs.resize(size);
int NN = Nm;
int NN = N1;
double evals_tmp[NN];
double evec_tmp[NN][NN];
memset(evec_tmp[0],0,sizeof(double)*NN*NN);
@ -266,8 +287,9 @@ public:
int info;
// int total = QMP_get_number_of_nodes();
// int node = QMP_get_node_number();
int total = _fgrid._Nprocessors;
int node = _fgrid._processor;
// GridBase *grid = evec[0]._grid;
int total = grid->_Nprocessors;
int node = grid->_processor;
int interval = (NN/total)+1;
double vl = 0.0, vu = 0.0;
int il = interval*node+1 , iu = interval*(node+1);
@ -298,40 +320,50 @@ public:
{
// QMP_sum_double_array(evals_tmp,NN);
// QMP_sum_double_array((double *)evec_tmp,NN*NN);
_fgrid.GlobalSumVector(evals_tmp,NN);
_fgrid.GlobalSumVector((double*)evec_tmp,NN*NN);
grid->GlobalSumVector(evals_tmp,NN);
grid->GlobalSumVector((double*)evec_tmp,NN*NN);
}
}
// cheating a bit. It is better to sort instead of just reversing it, but the document of the routine says evals are sorted in increasing order. qr gives evals in decreasing order.
for(int i=0;i<NN;i++){
for(int j=0;j<NN;j++)
Qt[i*NN+j]=evec_tmp[i][j];
lmd [i]=evals_tmp[i];
Qt[(NN-1-i)*N2+j]=evec_tmp[i][j];
lmd [NN-1-i]=evals_tmp[i];
}
}
#endif
void diagonalize(DenseVector<RealD>& lmd,
DenseVector<RealD>& lme,
int Nm2,
int Nm,
DenseVector<RealD>& Qt)
int N2,
int N1,
DenseVector<RealD>& Qt,
GridBase *grid)
{
if(1)
{
DenseVector <RealD> lmd2(Nm);
DenseVector <RealD> lme2(Nm);
for(int k=0; k<Nm; ++k){
#ifdef USE_LAPACK
const int check_lapack=0; // just use lapack if 0, check against lapack if 1
if(!check_lapack)
return diagonalize_lapack(lmd,lme,N2,N1,Qt,grid);
DenseVector <RealD> lmd2(N1);
DenseVector <RealD> lme2(N1);
DenseVector<RealD> Qt2(N1*N1);
for(int k=0; k<N1; ++k){
lmd2[k] = lmd[k];
lme2[k] = lme[k];
}
for(int k=0; k<N1*N1; ++k)
Qt2[k] = Qt[k];
return diagonalize_lapack(lmd,lme,Nm2,Nm,Qt);
}
// diagonalize_lapack(lmd2,lme2,Nm2,Nm,Qt,grid);
#endif
int Niter = 100*Nm;
int Niter = 100*N1;
int kmin = 1;
int kmax = Nk;
int kmax = N2;
// (this should be more sophisticated)
for(int iter=0; iter<Niter; ++iter){
@ -343,7 +375,7 @@ if(1)
// (Dsh: shift)
// transformation
qr_decomp(lmd,lme,Nk,Nm,Qt,Dsh,kmin,kmax);
qr_decomp(lmd,lme,N2,N1,Qt,Dsh,kmin,kmax);
// Convergence criterion (redef of kmin and kamx)
for(int j=kmax-1; j>= kmin; --j){
@ -354,6 +386,23 @@ if(1)
}
}
Niter = iter;
#ifdef USE_LAPACK
if(check_lapack){
const double SMALL=1e-8;
diagonalize_lapack(lmd2,lme2,N2,N1,Qt2,grid);
DenseVector <RealD> lmd3(N2);
for(int k=0; k<N2; ++k) lmd3[k]=lmd[k];
_sort.push(lmd3,N2);
_sort.push(lmd2,N2);
for(int k=0; k<N2; ++k){
if (fabs(lmd2[k] - lmd3[k]) >SMALL) std::cout <<"lmd(qr) lmd(lapack) "<< k << ": " << lmd2[k] <<" "<< lmd3[k] <<std::endl;
// if (fabs(lme2[k] - lme[k]) >SMALL) std::cout <<"lme(qr)-lme(lapack) "<< k << ": " << lme2[k] - lme[k] <<std::endl;
}
for(int k=0; k<N1*N1; ++k){
// if (fabs(Qt2[k] - Qt[k]) >SMALL) std::cout <<"Qt(qr)-Qt(lapack) "<< k << ": " << Qt2[k] - Qt[k] <<std::endl;
}
}
#endif
return;
continued:
@ -369,6 +418,7 @@ if(1)
abort();
}
#if 1
static RealD normalise(Field& v)
{
RealD nn = norm2(v);
@ -430,6 +480,7 @@ until convergence
{
GridBase *grid = evec[0]._grid;
assert(grid == src._grid);
std::cout << " -- Nk = " << Nk << " Np = "<< Np << std::endl;
std::cout << " -- Nm = " << Nm << std::endl;
@ -460,9 +511,11 @@ until convergence
// (uniform vector) Why not src??
// evec[0] = 1.0;
evec[0] = src;
std:: cout <<"norm2(src)= " << norm2(src) << std::endl;
std:: cout <<"norm2(src)= " << norm2(src)<<std::endl;
// << src._grid << std::endl;
normalise(evec[0]);
std:: cout <<"norm2(evec[0])= " << norm2(evec[0]) << std::endl;
std:: cout <<"norm2(evec[0])= " << norm2(evec[0]) <<std::endl;
// << evec[0]._grid << std::endl;
// Initial Nk steps
for(int k=0; k<Nk; ++k) step(eval,lme,evec,f,Nm,k);
@ -494,7 +547,7 @@ until convergence
lme2[k] = lme[k+k1-1];
}
setUnit_Qt(Nm,Qt);
diagonalize(eval2,lme2,Nm,Nm,Qt);
diagonalize(eval2,lme2,Nm,Nm,Qt,grid);
// sorting
_sort.push(eval2,Nm);
@ -533,7 +586,7 @@ until convergence
lme2[k] = lme[k];
}
setUnit_Qt(Nm,Qt);
diagonalize(eval2,lme2,Nk,Nm,Qt);
diagonalize(eval2,lme2,Nk,Nm,Qt,grid);
for(int k = 0; k<Nk; ++k) B[k]=0.0;
@ -541,13 +594,16 @@ until convergence
for(int k = 0; k<Nk; ++k){
B[j] += Qt[k+j*Nm] * evec[k];
}
// std::cout << "norm(B["<<j<<"])="<<norm2(B[j])<<std::endl;
}
// _sort.push(eval2,B,Nk);
Nconv = 0;
// std::cout << std::setiosflags(std::ios_base::scientific);
for(int i=0; i<Nk; ++i){
_poly(_Linop,B[i],v);
// _poly(_Linop,B[i],v);
_Linop.HermOp(B[i],v);
RealD vnum = real(innerProduct(B[i],v)); // HermOp.
RealD vden = norm2(B[i]);
@ -555,11 +611,13 @@ until convergence
v -= eval2[i]*B[i];
RealD vv = norm2(v);
std::cout.precision(13);
std::cout << "[" << std::setw(3)<< std::setiosflags(std::ios_base::right) <<i<<"] ";
std::cout << "eval = "<<std::setw(25)<< std::setiosflags(std::ios_base::left)<< eval2[i];
std::cout <<" |H B[i] - eval[i]B[i]|^2 "<< std::setw(25)<< std::setiosflags(std::ios_base::right)<< vv<< std::endl;
if(vv<eresid*eresid){
// change the criteria as evals are supposed to be sorted, all evals smaller(larger) than Nstop should have converged
if((vv<eresid*eresid) && (i == Nconv) ){
Iconv[Nconv] = i;
++Nconv;
}
@ -1140,6 +1198,7 @@ static void Lock(DenseMatrix<T> &H, ///Hess mtx
}
}
#endif
};