mirror of
https://github.com/paboyle/Grid.git
synced 2024-11-14 01:35:36 +00:00
Checking in working version of Lanczos.
This commit is contained in:
Chulwoo Jung
parent
0d5af667d8
commit
1e3fb32572
@ -8,7 +8,6 @@
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Author: Peter Boyle <paboyle@ph.ed.ac.uk>
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Author: paboyle <paboyle@ph.ed.ac.uk>
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Author: Chulwoo Jung <chulwoo@bnl.gov>
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This program is free software; you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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@ -32,11 +31,16 @@ Author: Chulwoo Jung <chulwoo@bnl.gov>
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#include <string.h> //memset
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#ifdef USE_LAPACK
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#ifdef USE_MKL
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#include<mkl_lapack.h>
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#else
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void LAPACK_dstegr(char *jobz, char *range, int *n, double *d, double *e,
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double *vl, double *vu, int *il, int *iu, double *abstol,
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int *m, double *w, double *z, int *ldz, int *isuppz,
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double *work, int *lwork, int *iwork, int *liwork,
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int *info);
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//#include <lapacke/lapacke.h>
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#endif
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#endif
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#include "DenseMatrix.h"
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#include "EigenSort.h"
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@ -63,12 +67,13 @@ public:
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int Np; // Np -- Number of spare vecs in kryloc space
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int Nm; // Nm -- total number of vectors
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RealD OrthoTime;
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RealD eresid;
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SortEigen<Field> _sort;
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// GridCartesian &_fgrid;
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LinearOperatorBase<Field> &_Linop;
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OperatorFunction<Field> &_poly;
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@ -125,23 +130,23 @@ public:
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GridBase *grid = evec[0]._grid;
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Field w(grid);
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std::cout << "RitzMatrix "<<std::endl;
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std::cout<<GridLogMessage << "RitzMatrix "<<std::endl;
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for(int i=0;i<k;i++){
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_poly(_Linop,evec[i],w);
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std::cout << "["<<i<<"] ";
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std::cout<<GridLogMessage << "["<<i<<"] ";
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for(int j=0;j<k;j++){
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ComplexD in = innerProduct(evec[j],w);
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if ( fabs((double)i-j)>1 ) {
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if (abs(in) >1.0e-9 ) {
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std::cout<<"oops"<<std::endl;
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std::cout<<GridLogMessage<<"oops"<<std::endl;
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abort();
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} else
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std::cout << " 0 ";
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std::cout<<GridLogMessage << " 0 ";
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} else {
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std::cout << " "<<in<<" ";
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std::cout<<GridLogMessage << " "<<in<<" ";
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}
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}
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std::cout << std::endl;
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std::cout<<GridLogMessage << std::endl;
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}
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}
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@ -175,10 +180,10 @@ public:
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RealD beta = normalise(w); // 6. βk+1 := ∥wk∥2. If βk+1 = 0 then Stop
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// 7. vk+1 := wk/βk+1
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// std::cout << "alpha = " << zalph << " beta "<<beta<<std::endl;
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std::cout<<GridLogMessage << "alpha = " << zalph << " beta "<<beta<<std::endl;
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const RealD tiny = 1.0e-20;
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if ( beta < tiny ) {
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std::cout << " beta is tiny "<<beta<<std::endl;
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std::cout<<GridLogMessage << " beta is tiny "<<beta<<std::endl;
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}
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lmd[k] = alph;
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lme[k] = beta;
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@ -254,6 +259,7 @@ public:
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}
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#ifdef USE_LAPACK
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#define LAPACK_INT long long
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void diagonalize_lapack(DenseVector<RealD>& lmd,
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DenseVector<RealD>& lme,
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int N1,
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@ -263,7 +269,7 @@ public:
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const int size = Nm;
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// tevals.resize(size);
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// tevecs.resize(size);
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int NN = N1;
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LAPACK_INT NN = N1;
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double evals_tmp[NN];
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double evec_tmp[NN][NN];
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memset(evec_tmp[0],0,sizeof(double)*NN*NN);
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@ -277,19 +283,19 @@ public:
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if (i==j) evals_tmp[i] = lmd[i];
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if (j==(i-1)) EE[j] = lme[j];
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}
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int evals_found;
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int lwork = ( (18*NN) > (1+4*NN+NN*NN)? (18*NN):(1+4*NN+NN*NN)) ;
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int liwork = 3+NN*10 ;
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int iwork[liwork];
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LAPACK_INT evals_found;
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LAPACK_INT lwork = ( (18*NN) > (1+4*NN+NN*NN)? (18*NN):(1+4*NN+NN*NN)) ;
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LAPACK_INT liwork = 3+NN*10 ;
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LAPACK_INT iwork[liwork];
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double work[lwork];
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int isuppz[2*NN];
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LAPACK_INT isuppz[2*NN];
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char jobz = 'V'; // calculate evals & evecs
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char range = 'I'; // calculate all evals
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// char range = 'A'; // calculate all evals
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char uplo = 'U'; // refer to upper half of original matrix
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char compz = 'I'; // Compute eigenvectors of tridiagonal matrix
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int ifail[NN];
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int info;
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long long info;
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// int total = QMP_get_number_of_nodes();
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// int node = QMP_get_node_number();
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// GridBase *grid = evec[0]._grid;
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@ -297,14 +303,18 @@ public:
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int node = grid->_processor;
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int interval = (NN/total)+1;
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double vl = 0.0, vu = 0.0;
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int il = interval*node+1 , iu = interval*(node+1);
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LAPACK_INT il = interval*node+1 , iu = interval*(node+1);
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if (iu > NN) iu=NN;
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double tol = 0.0;
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if (1) {
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memset(evals_tmp,0,sizeof(double)*NN);
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if ( il <= NN){
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printf("total=%d node=%d il=%d iu=%d\n",total,node,il,iu);
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#ifdef USE_MKL
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dstegr(&jobz, &range, &NN,
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#else
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LAPACK_dstegr(&jobz, &range, &NN,
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#endif
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(double*)DD, (double*)EE,
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&vl, &vu, &il, &iu, // these four are ignored if second parameteris 'A'
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&tol, // tolerance
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@ -336,6 +346,7 @@ public:
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lmd [NN-1-i]=evals_tmp[i];
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}
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}
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#undef LAPACK_INT
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#endif
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@ -366,12 +377,14 @@ public:
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// diagonalize_lapack(lmd2,lme2,Nm2,Nm,Qt,grid);
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#endif
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int Niter = 100*N1;
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int Niter = 10000*N1;
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int kmin = 1;
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int kmax = N2;
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// (this should be more sophisticated)
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for(int iter=0; iter<Niter; ++iter){
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for(int iter=0; ; ++iter){
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if ( (iter+1)%(100*N1)==0)
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std::cout<<GridLogMessage << "[QL method] Not converged - iteration "<<iter+1<<"\n";
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// determination of 2x2 leading submatrix
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RealD dsub = lmd[kmax-1]-lmd[kmax-2];
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@ -400,11 +413,11 @@ public:
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_sort.push(lmd3,N2);
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_sort.push(lmd2,N2);
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for(int k=0; k<N2; ++k){
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if (fabs(lmd2[k] - lmd3[k]) >SMALL) std::cout <<"lmd(qr) lmd(lapack) "<< k << ": " << lmd2[k] <<" "<< lmd3[k] <<std::endl;
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// if (fabs(lme2[k] - lme[k]) >SMALL) std::cout <<"lme(qr)-lme(lapack) "<< k << ": " << lme2[k] - lme[k] <<std::endl;
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if (fabs(lmd2[k] - lmd3[k]) >SMALL) std::cout<<GridLogMessage <<"lmd(qr) lmd(lapack) "<< k << ": " << lmd2[k] <<" "<< lmd3[k] <<std::endl;
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// if (fabs(lme2[k] - lme[k]) >SMALL) std::cout<<GridLogMessage <<"lme(qr)-lme(lapack) "<< k << ": " << lme2[k] - lme[k] <<std::endl;
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}
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for(int k=0; k<N1*N1; ++k){
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// if (fabs(Qt2[k] - Qt[k]) >SMALL) std::cout <<"Qt(qr)-Qt(lapack) "<< k << ": " << Qt2[k] - Qt[k] <<std::endl;
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// if (fabs(Qt2[k] - Qt[k]) >SMALL) std::cout<<GridLogMessage <<"Qt(qr)-Qt(lapack) "<< k << ": " << Qt2[k] - Qt[k] <<std::endl;
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}
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}
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#endif
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@ -419,7 +432,7 @@ public:
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}
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}
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}
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std::cout << "[QL method] Error - Too many iteration: "<<Niter<<"\n";
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std::cout<<GridLogMessage << "[QL method] Error - Too many iteration: "<<Niter<<"\n";
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abort();
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}
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@ -436,6 +449,7 @@ public:
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DenseVector<Field>& evec,
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int k)
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{
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double t0=-usecond()/1e6;
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typedef typename Field::scalar_type MyComplex;
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MyComplex ip;
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@ -454,6 +468,8 @@ public:
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w = w - ip * evec[j];
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}
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normalise(w);
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t0+=usecond()/1e6;
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OrthoTime +=t0;
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}
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void setUnit_Qt(int Nm, DenseVector<RealD> &Qt) {
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@ -487,10 +503,10 @@ until convergence
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GridBase *grid = evec[0]._grid;
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assert(grid == src._grid);
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std::cout << " -- Nk = " << Nk << " Np = "<< Np << std::endl;
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std::cout << " -- Nm = " << Nm << std::endl;
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std::cout << " -- size of eval = " << eval.size() << std::endl;
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std::cout << " -- size of evec = " << evec.size() << std::endl;
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std::cout<<GridLogMessage << " -- Nk = " << Nk << " Np = "<< Np << std::endl;
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std::cout<<GridLogMessage << " -- Nm = " << Nm << std::endl;
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std::cout<<GridLogMessage << " -- size of eval = " << eval.size() << std::endl;
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std::cout<<GridLogMessage << " -- size of evec = " << evec.size() << std::endl;
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assert(Nm == evec.size() && Nm == eval.size());
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@ -501,6 +517,7 @@ until convergence
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DenseVector<int> Iconv(Nm);
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DenseVector<Field> B(Nm,grid); // waste of space replicating
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// DenseVector<Field> Btemp(Nm,grid); // waste of space replicating
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Field f(grid);
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Field v(grid);
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@ -516,35 +533,48 @@ until convergence
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// (uniform vector) Why not src??
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// evec[0] = 1.0;
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evec[0] = src;
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std:: cout <<"norm2(src)= " << norm2(src)<<std::endl;
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std:: cout<<GridLogMessage <<"norm2(src)= " << norm2(src)<<std::endl;
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// << src._grid << std::endl;
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normalise(evec[0]);
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std:: cout <<"norm2(evec[0])= " << norm2(evec[0]) <<std::endl;
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std:: cout<<GridLogMessage <<"norm2(evec[0])= " << norm2(evec[0]) <<std::endl;
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// << evec[0]._grid << std::endl;
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// Initial Nk steps
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OrthoTime=0.;
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double t0=usecond()/1e6;
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for(int k=0; k<Nk; ++k) step(eval,lme,evec,f,Nm,k);
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// std:: cout <<"norm2(evec[1])= " << norm2(evec[1]) << std::endl;
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// std:: cout <<"norm2(evec[2])= " << norm2(evec[2]) << std::endl;
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double t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL::Initial steps: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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std::cout<<GridLogMessage <<"IRL::Initial steps:OrthoTime "<<OrthoTime<< "seconds"<<std::endl;
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// std:: cout<<GridLogMessage <<"norm2(evec[1])= " << norm2(evec[1]) << std::endl;
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// std:: cout<<GridLogMessage <<"norm2(evec[2])= " << norm2(evec[2]) << std::endl;
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RitzMatrix(evec,Nk);
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL::RitzMatrix: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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for(int k=0; k<Nk; ++k){
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// std:: cout <<"eval " << k << " " <<eval[k] << std::endl;
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// std:: cout <<"lme " << k << " " << lme[k] << std::endl;
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// std:: cout<<GridLogMessage <<"eval " << k << " " <<eval[k] << std::endl;
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// std:: cout<<GridLogMessage <<"lme " << k << " " << lme[k] << std::endl;
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}
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// Restarting loop begins
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for(int iter = 0; iter<Niter; ++iter){
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std::cout<<"\n Restart iteration = "<< iter << std::endl;
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std::cout<<GridLogMessage<<"\n Restart iteration = "<< iter << std::endl;
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//
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// Rudy does a sort first which looks very different. Getting fed up with sorting out the algo defs.
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// We loop over
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//
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OrthoTime=0.;
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for(int k=Nk; k<Nm; ++k) step(eval,lme,evec,f,Nm,k);
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL:: "<<Np <<" steps: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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std::cout<<GridLogMessage <<"IRL::Initial steps:OrthoTime "<<OrthoTime<< "seconds"<<std::endl;
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f *= lme[Nm-1];
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RitzMatrix(evec,k2);
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL:: RitzMatrix: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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// getting eigenvalues
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for(int k=0; k<Nm; ++k){
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@ -553,18 +583,27 @@ until convergence
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}
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setUnit_Qt(Nm,Qt);
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diagonalize(eval2,lme2,Nm,Nm,Qt,grid);
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL:: diagonalize: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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// sorting
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_sort.push(eval2,Nm);
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL:: eval sorting: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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// Implicitly shifted QR transformations
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setUnit_Qt(Nm,Qt);
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for(int ip=0; ip<k2; ++ip){
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std::cout<<GridLogMessage << "eval "<< ip << " "<< eval2[ip] << std::endl;
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}
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for(int ip=k2; ip<Nm; ++ip){
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std::cout << "qr_decomp "<< ip << " "<< eval2[ip] << std::endl;
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std::cout<<GridLogMessage << "qr_decomp "<< ip << " "<< eval2[ip] << std::endl;
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qr_decomp(eval,lme,Nm,Nm,Qt,eval2[ip],k1,Nm);
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}
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL::qr_decomp: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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if (0) {
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for(int i=0; i<(Nk+1); ++i) B[i] = 0.0;
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for(int j=k1-1; j<k2+1; ++j){
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@ -573,6 +612,30 @@ until convergence
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B[j] += Qt[k+Nm*j] * evec[k];
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}
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}
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL::QR Rotate: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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}
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if (1) {
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for(int i=0; i<(Nk+1); ++i) {
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B[i] = 0.0;
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B[i].checkerboard = evec[0].checkerboard;
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}
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int j_block = 24; int k_block=24;
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PARALLEL_FOR_LOOP
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for(int ss=0;ss < grid->oSites();ss++){
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for(int jj=k1-1; jj<k2+1; jj += j_block)
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for(int kk=0; kk<Nm; kk += k_block)
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for(int j=jj; (j<(k2+1)) && j<(jj+j_block); ++j){
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for(int k=kk; (k<Nm) && k<(kk+k_block) ; ++k){
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B[j]._odata[ss] +=Qt[k+Nm*j] * evec[k]._odata[ss];
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}
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}
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}
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL::QR rotation: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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}
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for(int j=k1-1; j<k2+1; ++j) evec[j] = B[j];
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// Compressed vector f and beta(k2)
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@ -580,7 +643,7 @@ until convergence
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f += lme[k2-1] * evec[k2];
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beta_k = norm2(f);
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beta_k = sqrt(beta_k);
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std::cout<<" beta(k) = "<<beta_k<<std::endl;
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std::cout<<GridLogMessage<<" beta(k) = "<<beta_k<<std::endl;
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RealD betar = 1.0/beta_k;
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evec[k2] = betar * f;
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@ -593,7 +656,10 @@ until convergence
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}
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setUnit_Qt(Nm,Qt);
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diagonalize(eval2,lme2,Nk,Nm,Qt,grid);
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t1=usecond()/1e6;
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std::cout<<GridLogMessage <<"IRL::diagonalize: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
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if (0) {
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for(int k = 0; k<Nk; ++k) B[k]=0.0;
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for(int j = 0; j<Nk; ++j){
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@ -601,12 +667,34 @@ until convergence
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B[j].checkerboard = evec[k].checkerboard;
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B[j] += Qt[k+j*Nm] * evec[k];
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}
|
||||
// std::cout << "norm(B["<<j<<"])="<<norm2(B[j])<<std::endl;
|
||||
std::cout<<GridLogMessage << "norm(B["<<j<<"])="<<norm2(B[j])<<std::endl;
|
||||
}
|
||||
// _sort.push(eval2,B,Nk);
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::Convergence rotation: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
}
|
||||
if (1) {
|
||||
for(int i=0; i<(Nk+1); ++i) {
|
||||
B[i] = 0.0;
|
||||
B[i].checkerboard = evec[0].checkerboard;
|
||||
}
|
||||
|
||||
int j_block = 24; int k_block=24;
|
||||
PARALLEL_FOR_LOOP
|
||||
for(int ss=0;ss < grid->oSites();ss++){
|
||||
for(int jj=0; jj<Nk; jj += j_block)
|
||||
for(int kk=0; kk<Nk; kk += k_block)
|
||||
for(int j=jj; (j<Nk) && j<(jj+j_block); ++j){
|
||||
for(int k=kk; (k<Nk) && k<(kk+k_block) ; ++k){
|
||||
B[j]._odata[ss] +=Qt[k+Nm*j] * evec[k]._odata[ss];
|
||||
}
|
||||
}
|
||||
}
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::convergence rotation : "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
}
|
||||
|
||||
Nconv = 0;
|
||||
// std::cout << std::setiosflags(std::ios_base::scientific);
|
||||
// std::cout<<GridLogMessage << std::setiosflags(std::ios_base::scientific);
|
||||
for(int i=0; i<Nk; ++i){
|
||||
|
||||
// _poly(_Linop,B[i],v);
|
||||
@ -614,14 +702,16 @@ until convergence
|
||||
|
||||
RealD vnum = real(innerProduct(B[i],v)); // HermOp.
|
||||
RealD vden = norm2(B[i]);
|
||||
RealD vv0 = norm2(v);
|
||||
eval2[i] = vnum/vden;
|
||||
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;
|
||||
std::cout<<GridLogMessage << "[" << 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::cout<<" "<< vnum/(sqrt(vden)*sqrt(vv0)) << std::endl;
|
||||
|
||||
// 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) ){
|
||||
@ -630,17 +720,19 @@ until convergence
|
||||
}
|
||||
|
||||
} // i-loop end
|
||||
// std::cout << std::resetiosflags(std::ios_base::scientific);
|
||||
// std::cout<<GridLogMessage << std::resetiosflags(std::ios_base::scientific);
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::convergence testing: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
|
||||
|
||||
std::cout<<" #modes converged: "<<Nconv<<std::endl;
|
||||
std::cout<<GridLogMessage<<" #modes converged: "<<Nconv<<std::endl;
|
||||
|
||||
if( Nconv>=Nstop ){
|
||||
goto converged;
|
||||
}
|
||||
} // end of iter loop
|
||||
|
||||
std::cout<<"\n NOT converged.\n";
|
||||
std::cout<<GridLogMessage<<"\n NOT converged.\n";
|
||||
abort();
|
||||
|
||||
converged:
|
||||
@ -653,10 +745,10 @@ until convergence
|
||||
}
|
||||
_sort.push(eval,evec,Nconv);
|
||||
|
||||
std::cout << "\n Converged\n Summary :\n";
|
||||
std::cout << " -- Iterations = "<< Nconv << "\n";
|
||||
std::cout << " -- beta(k) = "<< beta_k << "\n";
|
||||
std::cout << " -- Nconv = "<< Nconv << "\n";
|
||||
std::cout<<GridLogMessage << "\n Converged\n Summary :\n";
|
||||
std::cout<<GridLogMessage << " -- Iterations = "<< Nconv << "\n";
|
||||
std::cout<<GridLogMessage << " -- beta(k) = "<< beta_k << "\n";
|
||||
std::cout<<GridLogMessage << " -- Nconv = "<< Nconv << "\n";
|
||||
}
|
||||
|
||||
/////////////////////////////////////////////////
|
||||
@ -679,25 +771,25 @@ until convergence
|
||||
}
|
||||
}
|
||||
|
||||
std::cout<<"Lanczos_Factor start/end " <<start <<"/"<<end<<std::endl;
|
||||
std::cout<<GridLogMessage<<"Lanczos_Factor start/end " <<start <<"/"<<end<<std::endl;
|
||||
|
||||
// Starting from scratch, bq[0] contains a random vector and |bq[0]| = 1
|
||||
int first;
|
||||
if(start == 0){
|
||||
|
||||
std::cout << "start == 0\n"; //TESTING
|
||||
std::cout<<GridLogMessage << "start == 0\n"; //TESTING
|
||||
|
||||
_poly(_Linop,bq[0],bf);
|
||||
|
||||
alpha = real(innerProduct(bq[0],bf));//alpha = bq[0]^dag A bq[0]
|
||||
|
||||
std::cout << "alpha = " << alpha << std::endl;
|
||||
std::cout<<GridLogMessage << "alpha = " << alpha << std::endl;
|
||||
|
||||
bf = bf - alpha * bq[0]; //bf = A bq[0] - alpha bq[0]
|
||||
|
||||
H[0][0]=alpha;
|
||||
|
||||
std::cout << "Set H(0,0) to " << H[0][0] << std::endl;
|
||||
std::cout<<GridLogMessage << "Set H(0,0) to " << H[0][0] << std::endl;
|
||||
|
||||
first = 1;
|
||||
|
||||
@ -717,19 +809,19 @@ until convergence
|
||||
|
||||
beta = 0;sqbt = 0;
|
||||
|
||||
std::cout << "cont is true so setting beta to zero\n";
|
||||
std::cout<<GridLogMessage << "cont is true so setting beta to zero\n";
|
||||
|
||||
} else {
|
||||
|
||||
beta = norm2(bf);
|
||||
sqbt = sqrt(beta);
|
||||
|
||||
std::cout << "beta = " << beta << std::endl;
|
||||
std::cout<<GridLogMessage << "beta = " << beta << std::endl;
|
||||
}
|
||||
|
||||
for(int j=first;j<end;j++){
|
||||
|
||||
std::cout << "Factor j " << j <<std::endl;
|
||||
std::cout<<GridLogMessage << "Factor j " << j <<std::endl;
|
||||
|
||||
if(cont){ // switches to factoring; understand start!=0 and initial bf value is right.
|
||||
bq[j] = bf; cont = false;
|
||||
@ -752,7 +844,7 @@ until convergence
|
||||
|
||||
beta = fnorm;
|
||||
sqbt = sqrt(beta);
|
||||
std::cout << "alpha = " << alpha << " fnorm = " << fnorm << '\n';
|
||||
std::cout<<GridLogMessage << "alpha = " << alpha << " fnorm = " << fnorm << '\n';
|
||||
|
||||
///Iterative refinement of orthogonality V = [ bq[0] bq[1] ... bq[M] ]
|
||||
int re = 0;
|
||||
@ -787,8 +879,8 @@ until convergence
|
||||
bck = sqrt( nmbex );
|
||||
re++;
|
||||
}
|
||||
std::cout << "Iteratively refined orthogonality, changes alpha\n";
|
||||
if(re > 1) std::cout << "orthagonality refined " << re << " times" <<std::endl;
|
||||
std::cout<<GridLogMessage << "Iteratively refined orthogonality, changes alpha\n";
|
||||
if(re > 1) std::cout<<GridLogMessage << "orthagonality refined " << re << " times" <<std::endl;
|
||||
H[j][j]=alpha;
|
||||
}
|
||||
|
||||
@ -803,11 +895,13 @@ until convergence
|
||||
|
||||
void ImplicitRestart(int TM, DenseVector<RealD> &evals, DenseVector<DenseVector<RealD> > &evecs, DenseVector<Field> &bq, Field &bf, int cont)
|
||||
{
|
||||
std::cout << "ImplicitRestart begin. Eigensort starting\n";
|
||||
std::cout<<GridLogMessage << "ImplicitRestart begin. Eigensort starting\n";
|
||||
|
||||
DenseMatrix<RealD> H; Resize(H,Nm,Nm);
|
||||
|
||||
#ifndef USE_LAPACK
|
||||
EigenSort(evals, evecs);
|
||||
#endif
|
||||
|
||||
///Assign shifts
|
||||
int K=Nk;
|
||||
@ -830,15 +924,15 @@ until convergence
|
||||
/// Shifted H defines a new K step Arnoldi factorization
|
||||
RealD beta = H[ff][ff-1];
|
||||
RealD sig = Q[TM - 1][ff - 1];
|
||||
std::cout << "beta = " << beta << " sig = " << real(sig) <<std::endl;
|
||||
std::cout<<GridLogMessage << "beta = " << beta << " sig = " << real(sig) <<std::endl;
|
||||
|
||||
std::cout << "TM = " << TM << " ";
|
||||
std::cout << norm2(bq[0]) << " -- before" <<std::endl;
|
||||
std::cout<<GridLogMessage << "TM = " << TM << " ";
|
||||
std::cout<<GridLogMessage << norm2(bq[0]) << " -- before" <<std::endl;
|
||||
|
||||
/// q -> q Q
|
||||
times_real(bq, Q, TM);
|
||||
|
||||
std::cout << norm2(bq[0]) << " -- after " << ff <<std::endl;
|
||||
std::cout<<GridLogMessage << norm2(bq[0]) << " -- after " << ff <<std::endl;
|
||||
bf = beta* bq[ff] + sig* bf;
|
||||
|
||||
/// Do the rest of the factorization
|
||||
@ -862,7 +956,7 @@ until convergence
|
||||
int ff = Lanczos_Factor(0, M, cont, bq,bf,H); // 0--M to begin with
|
||||
|
||||
if(ff < M) {
|
||||
std::cout << "Krylov: aborting ff "<<ff <<" "<<M<<std::endl;
|
||||
std::cout<<GridLogMessage << "Krylov: aborting ff "<<ff <<" "<<M<<std::endl;
|
||||
abort(); // Why would this happen?
|
||||
}
|
||||
|
||||
@ -871,7 +965,7 @@ until convergence
|
||||
|
||||
for(int it = 0; it < Niter && (converged < Nk); ++it) {
|
||||
|
||||
std::cout << "Krylov: Iteration --> " << it << std::endl;
|
||||
std::cout<<GridLogMessage << "Krylov: Iteration --> " << it << std::endl;
|
||||
int lock_num = lock ? converged : 0;
|
||||
DenseVector<RealD> tevals(M - lock_num );
|
||||
DenseMatrix<RealD> tevecs; Resize(tevecs,M - lock_num,M - lock_num);
|
||||
@ -887,7 +981,7 @@ until convergence
|
||||
Wilkinson<RealD>(H, evals, evecs, small);
|
||||
// Check();
|
||||
|
||||
std::cout << "Done "<<std::endl;
|
||||
std::cout<<GridLogMessage << "Done "<<std::endl;
|
||||
|
||||
}
|
||||
|
||||
@ -952,7 +1046,7 @@ until convergence
|
||||
DenseVector<RealD> &tevals, DenseVector<DenseVector<RealD> > &tevecs,
|
||||
int lock, int converged)
|
||||
{
|
||||
std::cout << "Converged " << converged << " so far." << std::endl;
|
||||
std::cout<<GridLogMessage << "Converged " << converged << " so far." << std::endl;
|
||||
int lock_num = lock ? converged : 0;
|
||||
int M = Nm;
|
||||
|
||||
@ -967,7 +1061,9 @@ until convergence
|
||||
RealD small=1.0e-16;
|
||||
Wilkinson<RealD>(AH, tevals, tevecs, small);
|
||||
|
||||
#ifndef USE_LAPACK
|
||||
EigenSort(tevals, tevecs);
|
||||
#endif
|
||||
|
||||
RealD resid_nrm= norm2(bf);
|
||||
|
||||
@ -978,7 +1074,7 @@ until convergence
|
||||
RealD diff = 0;
|
||||
diff = abs( tevecs[i][Nm - 1 - lock_num] ) * resid_nrm;
|
||||
|
||||
std::cout << "residual estimate " << SS-1-i << " " << diff << " of (" << tevals[i] << ")" << std::endl;
|
||||
std::cout<<GridLogMessage << "residual estimate " << SS-1-i << " " << diff << " of (" << tevals[i] << ")" << std::endl;
|
||||
|
||||
if(diff < converged) {
|
||||
|
||||
@ -994,13 +1090,13 @@ until convergence
|
||||
lock_num++;
|
||||
}
|
||||
converged++;
|
||||
std::cout << " converged on eval " << converged << " of " << Nk << std::endl;
|
||||
std::cout<<GridLogMessage << " converged on eval " << converged << " of " << Nk << std::endl;
|
||||
} else {
|
||||
break;
|
||||
}
|
||||
}
|
||||
#endif
|
||||
std::cout << "Got " << converged << " so far " <<std::endl;
|
||||
std::cout<<GridLogMessage << "Got " << converged << " so far " <<std::endl;
|
||||
}
|
||||
|
||||
///Check
|
||||
@ -1009,7 +1105,9 @@ until convergence
|
||||
|
||||
DenseVector<RealD> goodval(this->get);
|
||||
|
||||
#ifndef USE_LAPACK
|
||||
EigenSort(evals,evecs);
|
||||
#endif
|
||||
|
||||
int NM = Nm;
|
||||
|
||||
@ -1081,10 +1179,10 @@ say con = 2
|
||||
**/
|
||||
|
||||
template<class T>
|
||||
static void Lock(DenseMatrix<T> &H, // Hess mtx
|
||||
DenseMatrix<T> &Q, // Lock Transform
|
||||
T val, // value to be locked
|
||||
int con, // number already locked
|
||||
static void Lock(DenseMatrix<T> &H, ///Hess mtx
|
||||
DenseMatrix<T> &Q, ///Lock Transform
|
||||
T val, ///value to be locked
|
||||
int con, ///number already locked
|
||||
RealD small,
|
||||
int dfg,
|
||||
bool herm)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user