1
0
mirror of https://github.com/paboyle/Grid.git synced 2024-11-15 10:15:36 +00:00

block Lanczos construction is added.

This commit is contained in:
Yong-Chull Jang 2017-12-03 23:55:22 -05:00
parent 2c35c89b92
commit 5139eaf491
3 changed files with 711 additions and 7 deletions

View File

@ -53,6 +53,7 @@ Author: Peter Boyle <paboyle@ph.ed.ac.uk>
#include <Grid/algorithms/iterative/ConjugateGradientReliableUpdate.h> #include <Grid/algorithms/iterative/ConjugateGradientReliableUpdate.h>
#include <Grid/algorithms/iterative/ImplicitlyRestartedLanczos.h> #include <Grid/algorithms/iterative/ImplicitlyRestartedLanczos.h>
#include <Grid/algorithms/iterative/ImplicitlyRestartedLanczosCJ.h> #include <Grid/algorithms/iterative/ImplicitlyRestartedLanczosCJ.h>
#include <Grid/algorithms/iterative/ImplicitlyRestartedBlockLanczos.h>
#include <Grid/algorithms/iterative/SimpleLanczos.h> #include <Grid/algorithms/iterative/SimpleLanczos.h>
#include <Grid/algorithms/CoarsenedMatrix.h> #include <Grid/algorithms/CoarsenedMatrix.h>
#include <Grid/algorithms/FFT.h> #include <Grid/algorithms/FFT.h>

View File

@ -0,0 +1,700 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ImplicitlyRestartedBlockLanczos.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Chulwoo Jung
Author: Yong-Chull Jang <ypj@quark.phy.bnl.gov>
Author: Guido Cossu
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_IRBL_H
#define GRID_IRBL_H
#include <string.h> //memset
#define clog std::cout << GridLogMessage
namespace Grid {
/////////////////////////////////////////////////////////////
// Implicitly restarted block lanczos
/////////////////////////////////////////////////////////////
template<class Field>
class ImplicitlyRestartedBlockLanczos {
private:
std::string cname = std::string("ImplicitlyRestartedBlockLanczos");
int MaxIter; // Max iterations
int Nstop; // Number of evecs checked for convergence
int Nu; // Numbeer of vecs in the unit block
int Nk; // Number of converged sought
int Nm; // total number of vectors
int Nblock_k; // Nk/Nu
int Nblock_m; // Nm/Nu
RealD eresid;
IRLdiagonalisation diagonalisation;
////////////////////////////////////
// Embedded objects
////////////////////////////////////
SortEigen<Field> _sort;
LinearOperatorBase<Field> &_Linop;
OperatorFunction<Field> &_poly;
/////////////////////////
// Constructor
/////////////////////////
public:
ImplicitlyRestartedBlockLanczos(LinearOperatorBase<Field> &Linop, // op
OperatorFunction<Field> & poly, // polynomial
int _Nstop, // really sought vecs
int _Nu, // vecs in the unit block
int _Nk, // sought vecs
int _Nm, // total vecs
RealD _eresid, // resid in lmd deficit
int _MaxIter, // Max iterations
IRLdiagonalisation _diagonalisation = IRLdiagonaliseWithEigen)
: _Linop(Linop), _poly(poly),
Nstop(_Nstop), Nu(_Nu), Nk(_Nk), Nm(_Nm),
Nblock_m(_Nm/_Nu), Nblock_k(_Nk/_Nu),
eresid(_eresid), MaxIter(_MaxIter),
diagonalisation(_diagonalisation)
{ assert( (Nk%Nu==0) && (Nm%Nu==0) ); };
////////////////////////////////
// Helpers
////////////////////////////////
static RealD normalize(Field& v)
{
RealD nn = norm2(v);
nn = sqrt(nn);
v = v * (1.0/nn);
return nn;
}
void orthogonalize(Field& w, std::vector<Field>& evec, int k)
{
typedef typename Field::scalar_type MyComplex;
MyComplex ip;
for(int j=0; j<k; ++j){
ip = innerProduct(evec[j],w);
w = w - ip * evec[j];
}
normalize(w);
}
/* Rudy Arthur's thesis pp.137
------------------------
Require: M > K P = M K
Compute the factorization AVM = VM HM + fM eM
repeat
Q=I
for i = 1,...,P do
QiRi =HM θiI Q = QQi
H M = Q i H M Q i
end for
βK =HM(K+1,K) σK =Q(M,K)
r=vK+1βK +rσK
VK =VM(1:M)Q(1:M,1:K)
HK =HM(1:K,1:K)
AVK =VKHK +fKeK Extend to an M = K + P step factorization AVM = VMHM + fMeM
until convergence
*/
void calc(std::vector<RealD>& eval,
std::vector<Field>& evec,
const std::vector<Field>& src, int& Nconv)
{
std::string fname = std::string(cname+"::calc()");
GridBase *grid = evec[0]._grid;
assert(grid == src[0]._grid);
assert( Nu = src.size() );
clog << std::string(74,'*') << std::endl;
clog << fname + " starting iteration 0 / "<< MaxIter<< std::endl;
clog << std::string(74,'*') << std::endl;
clog <<" -- seek Nk = "<< Nk <<" vectors"<< std::endl;
clog <<" -- accept Nstop = "<< Nstop <<" vectors"<< std::endl;
clog <<" -- total Nm = "<< Nm <<" vectors"<< std::endl;
clog <<" -- size of eval = "<< eval.size() << std::endl;
clog <<" -- size of evec = "<< evec.size() << std::endl;
if ( diagonalisation == IRLdiagonaliseWithDSTEGR ) {
clog << "Diagonalisation is DSTEGR "<< std::endl;
} else if ( diagonalisation == IRLdiagonaliseWithQR ) {
clog << "Diagonalisation is QR "<< std::endl;
} else if ( diagonalisation == IRLdiagonaliseWithEigen ) {
clog << "Diagonalisation is Eigen "<< std::endl;
}
clog << std::string(74,'*') << std::endl;
assert(Nm == evec.size() && Nm == eval.size());
std::vector<std::vector<ComplexD>> lmd(Nu,std::vector<ComplexD>(Nm,0.0));
std::vector<std::vector<ComplexD>> lme(Nu,std::vector<ComplexD>(Nm,0.0));
std::vector<std::vector<ComplexD>> lmd2(Nu,std::vector<ComplexD>(Nm,0.0));
std::vector<std::vector<ComplexD>> lme2(Nu,std::vector<ComplexD>(Nm,0.0));
std::vector<RealD> eval2(Nm);
Eigen::MatrixXcd Qt = Eigen::MatrixXcd::Zero(Nm,Nm);
std::vector<int> Iconv(Nm);
std::vector<Field> B(Nm,grid); // waste of space replicating
std::vector<Field> f(Nu,grid);
std::vector<Field> f_copy(Nu,grid);
Field v(grid);
int k1 = 1;
int k2 = Nk;
Nconv = 0;
RealD beta_k;
// Set initial vector
for (int i=0; i<Nu; ++i) {
clog << "norm2(src[" << i << "])= "<< norm2(src[i]) << std::endl;
evec[i] = src[i];
orthogonalize(evec[i],evec,i);
clog << "norm2(evec[" << i << "])= "<< norm2(evec[i]) << std::endl;
}
// Initial Nblock_k steps
for(int b=0; b<Nblock_k; ++b) blockwiseStep(lmd,lme,evec,f,f_copy,b);
// Restarting loop begins
int iter;
for(iter = 0; iter<MaxIter; ++iter){
clog <<" **********************"<< std::endl;
clog <<" Restart iteration = "<< iter << std::endl;
clog <<" **********************"<< std::endl;
for(int b=Nblock_k; b<Nblock_m; ++b) blockwiseStep(lmd,lme,evec,f,f_copy,b);
//f[Nu-1] *= lme[Nm-1]; // ypj[fixme] need to be changed for block method
// getting eigenvalues
for(int u=0; u<Nu; ++u){
for(int k=0; k<Nm; ++k){
lmd2[u][k] = lmd[u][k];
lme2[u][k] = lme[u][k];
}
}
Qt = Eigen::MatrixXcd::Identity(Nm,Nm);
diagonalize(eval2,lmd2,lme2,Nu,Nblock_m,Nm,Nm,Qt,grid);
// sorting
_sort.push(eval2,Nm);
break;
}
#if 0 // working up to here
// Implicitly shifted QR transformations
Qt = Eigen::MatrixXcd::Identity(Nm,Nm);
for(int ip=k2; ip<Nm; ++ip){
// Eigen replacement for qr_decomp ???
qr_decomp(eval,lme,Nm,Nm,Qt,eval2[ip],k1,Nm);
}
for(int i=0; i<(Nk+1); ++i) B[i] = 0.0;
for(int j=k1-1; j<k2+1; ++j){
for(int k=0; k<Nm; ++k){
B[j].checkerboard = evec[k].checkerboard;
B[j] += Qt(j,k) * evec[k];
}
}
for(int j=k1-1; j<k2+1; ++j) evec[j] = B[j];
// Compressed vector f and beta(k2)
f *= Qt(k2-1,Nm-1);
f += lme[k2-1] * evec[k2];
beta_k = norm2(f);
beta_k = sqrt(beta_k);
std::cout<< GridLogMessage<<" beta(k) = "<<beta_k<<std::endl;
RealD betar = 1.0/beta_k;
evec[k2] = betar * f;
lme[k2-1] = beta_k;
// Convergence test
for(int k=0; k<Nm; ++k){
eval2[k] = eval[k];
lme2[k] = lme[k];
}
Qt = Eigen::MatrixXcd::Identity(Nm,Nm);
diagonalize(eval2,lme2,Nk,Nm,Qt,grid);
for(int k = 0; k<Nk; ++k) B[k]=0.0;
for(int j = 0; j<Nk; ++j){
for(int k = 0; k<Nk; ++k){
B[j].checkerboard = evec[k].checkerboard;
B[j] += Qt(j,k) * evec[k];
}
}
Nconv = 0;
for(int i=0; i<Nk; ++i){
_Linop.HermOp(B[i],v);
RealD vnum = real(innerProduct(B[i],v)); // HermOp.
RealD vden = norm2(B[i]);
eval2[i] = vnum/vden;
v -= eval2[i]*B[i];
RealD vv = norm2(v);
std::cout.precision(13);
clog << "[" << 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;
// 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;
}
} // i-loop end
std::cout<< GridLogMessage <<" #modes converged: "<<Nconv<<std::endl;
if( Nconv>=Nstop ){
goto converged;
}
} // end of iter loop
clog <<"**************************************************************************"<< std::endl;
std::cout<< GridLogError << fname + " NOT converged.";
clog <<"**************************************************************************"<< std::endl;
abort();
converged:
// Sorting
eval.resize(Nconv);
evec.resize(Nconv,grid);
for(int i=0; i<Nconv; ++i){
eval[i] = eval2[Iconv[i]];
evec[i] = B[Iconv[i]];
}
_sort.push(eval,evec,Nconv);
clog <<"**************************************************************************"<< std::endl;
clog << fname + " CONVERGED ; Summary :\n";
clog <<"**************************************************************************"<< std::endl;
clog << " -- Iterations = "<< iter << "\n";
clog << " -- beta(k) = "<< beta_k << "\n";
clog << " -- Nconv = "<< Nconv << "\n";
clog <<"**************************************************************************"<< std::endl;
#endif
}
private:
/* Saad PP. 195
1. Choose an initial vector v1 of 2-norm unity. Set β1 0, v0 0
2. For k = 1,2,...,m Do:
3. wk:=Avkβkv_{k1}
4. αk:=(wk,vk) //
5. wk:=wkαkvk // wk orthog vk
6. βk+1 := wk2. If βk+1 = 0 then Stop
7. vk+1 := wk/βk+1
8. EndDo
*/
void blockwiseStep(std::vector<std::vector<ComplexD>>& lmd,
std::vector<std::vector<ComplexD>>& lme,
std::vector<Field>& evec,
std::vector<Field>& w,
std::vector<Field>& w_copy,
int b)
{
const RealD tiny = 1.0e-20;
int Nu = w.size();
int Nm = evec.size();
assert( b < Nm/Nu );
// converts block index to full indicies for an interval [L,R)
int L = Nu*b;
int R = Nu*(b+1);
Real beta;
clog << "A: b = " << b << std::endl;
// 3. wk:=Avkβkv_{k1}
for (int k=L, u=0; k<R; ++k, ++u) {
_poly(_Linop,evec[k],w[u]);
}
if (b>0) {
clog << "B: b = " << b << std::endl;
for (int u=0; u<Nu; ++u) {
for (int k=L-Nu; k<L; ++k) {
w[u] = w[u] - evec[k] * conjugate(lme[u][k]);
}
}
}
// 4. αk:=(vk,wk)
clog << "C: b = " << b << std::endl;
for (int u=0; u<Nu; ++u) {
for (int k=L; k<R; ++k) {
lmd[u][k] = innerProduct(evec[k],w[u]); // lmd = transpose of alpha
}
lmd[u][L+u] = real(lmd[u][L+u]); // force diagonal to be real
}
clog << "D: b = " << b << std::endl;
// 5. wk:=wkαkvk
for (int u=0; u<Nu; ++u) {
for (int k=L; k<R; ++k) {
w[u] = w[u] - evec[k]*lmd[u][k];
}
w_copy[u] = w[u];
}
// In block version, the steps 6 and 7 in Lanczos construction is
// replaced by the QR decomposition of new basis block.
// It results block version beta and orthonormal block basis.
// Here, QR decomposition is done by using Gram-Schmidt
clog << "E: b = " << b << std::endl;
for (int u=0; u<Nu; ++u) {
for (int k=L; k<R; ++k) {
lme[u][k] = 0.0;
}
}
clog << "F: b = " << b << std::endl;
beta = normalize(w[0]);
for (int u=1; u<Nu; ++u) {
//orthogonalize(w[u],w_copy,u);
orthogonalize(w[u],w,u);
}
clog << "G: b = " << b << std::endl;
for (int u=0; u<Nu; ++u) {
for (int v=0; v<Nu; ++v) {
lme[u][L+v] = innerProduct(w[u],w_copy[v]);
}
}
lme[0][L] = beta;
#if 0
for (int u=0; u<Nu; ++u) {
for (int k=L+u; k<R; ++k) {
if (lme[u][k] < tiny) {
clog <<" In block "<< b << ",";
std::cout <<" beta[" << u << "," << k-L << "] = ";
std::cout << lme[u][k] << std::endl;
}
}
}
#else
clog << "H: b = " << b << std::endl;
for (int u=0; u<Nu; ++u) {
clog << "norm2(w[" << u << "])= "<< norm2(w[u]) << std::endl;
for (int k=L+u; k<R; ++k) {
clog <<" In block "<< b << ",";
std::cout <<" beta[" << u << "," << k-L << "] = ";
std::cout << lme[u][k] << std::endl;
}
}
#endif
// re-orthogonalization for numerical stability
//clog << "I: b = " << b << std::endl;
//if (b>0) {
// for (int u=0; u<Nu; ++u) {
// orthogonalize(w[u],evec,R);
// }
//}
clog << "J: b = " << b << std::endl;
if (b < Nm/Nu-1) {
for (int u=0; u<Nu; ++u) {
evec[R+u] = w[u];
}
}
}
void diagonalize_Eigen(std::vector<RealD>& eval,
std::vector<std::vector<ComplexD>>& lmd,
std::vector<std::vector<ComplexD>>& lme,
int Nu, int Nb, int Nk, int Nm,
Eigen::MatrixXcd & Qt, // Nm x Nm
GridBase *grid)
{
assert( Nk%Nu == 0 && Nm%Nu == 0 );
assert( Nk <= Nm );
Eigen::MatrixXcd BlockTriDiag = Eigen::MatrixXcd::Zero(Nk,Nk);
for ( int u=0; u<Nu; ++u ) {
for (int k=0; k<Nk; ++k ) {
BlockTriDiag(k,u+(k/Nu)*Nu) = lmd[u][k];
}
}
for ( int u=0; u<Nu; ++u ) {
for (int k=Nu; k<Nk; ++k ) {
BlockTriDiag(u+(k/Nu)*Nu,k-Nu) = lme[u][k-Nu];
BlockTriDiag(k,u+(k/Nu)*Nu) = conjugate(lme[u][k-Nu]);
}
}
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXcd> eigensolver(BlockTriDiag);
for (int i = 0; i < Nk; i++) {
eval[Nk-1-i] = eigensolver.eigenvalues()(i);
}
for (int i = 0; i < Nk; i++) {
for (int j = 0; j < Nk; j++) {
Qt(Nk-1-i,j) = eigensolver.eigenvectors()(j,i);
}
}
}
///////////////////////////////////////////////////////////////////////////
// File could end here if settle on Eigen ???
///////////////////////////////////////////////////////////////////////////
void qr_decomp(std::vector<RealD>& lmd, // Nm
std::vector<RealD>& lme, // Nm
int Nk, int Nm, // Nk, Nm
Eigen::MatrixXd& Qt, // Nm x Nm matrix
RealD Dsh, int kmin, int kmax)
{
int k = kmin-1;
RealD x;
RealD Fden = 1.0/hypot(lmd[k]-Dsh,lme[k]);
RealD c = ( lmd[k] -Dsh) *Fden;
RealD s = -lme[k] *Fden;
RealD tmpa1 = lmd[k];
RealD tmpa2 = lmd[k+1];
RealD tmpb = lme[k];
lmd[k] = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
lme[k] = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
x =-s*lme[k+1];
lme[k+1] = c*lme[k+1];
for(int i=0; i<Nk; ++i){
RealD Qtmp1 = Qt(k,i);
RealD Qtmp2 = Qt(k+1,i);
Qt(k,i) = c*Qtmp1 - s*Qtmp2;
Qt(k+1,i)= s*Qtmp1 + c*Qtmp2;
}
// Givens transformations
for(int k = kmin; k < kmax-1; ++k){
RealD Fden = 1.0/hypot(x,lme[k-1]);
RealD c = lme[k-1]*Fden;
RealD s = - x*Fden;
RealD tmpa1 = lmd[k];
RealD tmpa2 = lmd[k+1];
RealD tmpb = lme[k];
lmd[k] = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
lme[k] = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
lme[k-1] = c*lme[k-1] -s*x;
if(k != kmax-2){
x = -s*lme[k+1];
lme[k+1] = c*lme[k+1];
}
for(int i=0; i<Nk; ++i){
RealD Qtmp1 = Qt(k,i);
RealD Qtmp2 = Qt(k+1,i);
Qt(k,i) = c*Qtmp1 -s*Qtmp2;
Qt(k+1,i) = s*Qtmp1 +c*Qtmp2;
}
}
}
void diagonalize(std::vector<RealD>& eval,
std::vector<std::vector<ComplexD>>& lmd,
std::vector<std::vector<ComplexD>>& lme,
int Nu, int Nb, int Nk, int Nm,
Eigen::MatrixXcd & Qt,
GridBase *grid)
{
Qt = Eigen::MatrixXcd::Identity(Nm,Nm);
// if ( diagonalisation == IRLdiagonaliseWithDSTEGR ) {
// diagonalize_lapack(lmd,lme,Nk,Nm,Qt,grid);
// } else if ( diagonalisation == IRLdiagonaliseWithQR ) {
// diagonalize_QR(lmd,lme,Nk,Nm,Qt,grid);
// } else if ( diagonalisation == IRLdiagonaliseWithEigen ) {
if ( diagonalisation == IRLdiagonaliseWithEigen ) {
diagonalize_Eigen(eval,lmd,lme,Nu,Nb,Nk,Nm,Qt,grid);
} else {
assert(0);
}
}
#ifdef USE_LAPACK
void LAPACK_dstegr(char *jobz, char *range, int *n, double *d, double *e,
double *vl, double *vu, int *il, int *iu, double *abstol,
int *m, double *w, double *z, int *ldz, int *isuppz,
double *work, int *lwork, int *iwork, int *liwork,
int *info);
#endif
void diagonalize_lapack(std::vector<RealD>& lmd,
std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd& Qt,
GridBase *grid)
{
#ifdef USE_LAPACK
const int size = Nm;
int NN = Nk;
double evals_tmp[NN];
double evec_tmp[NN][NN];
memset(evec_tmp[0],0,sizeof(double)*NN*NN);
double DD[NN];
double EE[NN];
for (int i = 0; i< NN; i++) {
for (int j = i - 1; j <= i + 1; j++) {
if ( j < NN && j >= 0 ) {
if (i==j) DD[i] = lmd[i];
if (i==j) evals_tmp[i] = lmd[i];
if (j==(i-1)) EE[j] = lme[j];
}
}
}
int evals_found;
int lwork = ( (18*NN) > (1+4*NN+NN*NN)? (18*NN):(1+4*NN+NN*NN)) ;
int liwork = 3+NN*10 ;
int iwork[liwork];
double work[lwork];
int isuppz[2*NN];
char jobz = 'V'; // calculate evals & evecs
char range = 'I'; // calculate all evals
// char range = 'A'; // calculate all evals
char uplo = 'U'; // refer to upper half of original matrix
char compz = 'I'; // Compute eigenvectors of tridiagonal matrix
int ifail[NN];
int info;
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);
if (iu > NN) iu=NN;
double tol = 0.0;
if (1) {
memset(evals_tmp,0,sizeof(double)*NN);
if ( il <= NN){
LAPACK_dstegr(&jobz, &range, &NN,
(double*)DD, (double*)EE,
&vl, &vu, &il, &iu, // these four are ignored if second parameteris 'A'
&tol, // tolerance
&evals_found, evals_tmp, (double*)evec_tmp, &NN,
isuppz,
work, &lwork, iwork, &liwork,
&info);
for (int i = iu-1; i>= il-1; i--){
evals_tmp[i] = evals_tmp[i - (il-1)];
if (il>1) evals_tmp[i-(il-1)]=0.;
for (int j = 0; j< NN; j++){
evec_tmp[i][j] = evec_tmp[i - (il-1)][j];
if (il>1) evec_tmp[i-(il-1)][j]=0.;
}
}
}
{
grid->GlobalSumVector(evals_tmp,NN);
grid->GlobalSumVector((double*)evec_tmp,NN*NN);
}
}
// Safer 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++){
lmd [NN-1-i]=evals_tmp[i];
for(int j=0;j<NN;j++){
Qt((NN-1-i),j)=evec_tmp[i][j];
}
}
#else
assert(0);
#endif
}
void diagonalize_QR(std::vector<RealD>& lmd, std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd & Qt,
GridBase *grid)
{
int Niter = 100*Nm;
int kmin = 1;
int kmax = Nk;
// (this should be more sophisticated)
for(int iter=0; iter<Niter; ++iter){
// determination of 2x2 leading submatrix
RealD dsub = lmd[kmax-1]-lmd[kmax-2];
RealD dd = sqrt(dsub*dsub + 4.0*lme[kmax-2]*lme[kmax-2]);
RealD Dsh = 0.5*(lmd[kmax-2]+lmd[kmax-1] +dd*(dsub/fabs(dsub)));
// (Dsh: shift)
// transformation
qr_decomp(lmd,lme,Nk,Nm,Qt,Dsh,kmin,kmax); // Nk, Nm
// Convergence criterion (redef of kmin and kamx)
for(int j=kmax-1; j>= kmin; --j){
RealD dds = fabs(lmd[j-1])+fabs(lmd[j]);
if(fabs(lme[j-1])+dds > dds){
kmax = j+1;
goto continued;
}
}
Niter = iter;
return;
continued:
for(int j=0; j<kmax-1; ++j){
RealD dds = fabs(lmd[j])+fabs(lmd[j+1]);
if(fabs(lme[j])+dds > dds){
kmin = j+1;
break;
}
}
}
std::cout << GridLogError << "[QL method] Error - Too many iteration: "<<Niter<<"\n";
abort();
}
};
}
#undef clog
#endif

View File

@ -2,7 +2,7 @@
Grid physics library, www.github.com/paboyle/Grid Grid physics library, www.github.com/paboyle/Grid
Source file: ./tests/Test_dwf_lanczos.cc Source file: ./tests/Test_dwf_block_lanczos.cc
Copyright (C) 2015 Copyright (C) 2015
@ -78,6 +78,7 @@ int main (int argc, char ** argv)
// SchurDiagMooeeOperator<DomainWallFermionR,LatticeFermion> HermOp(Ddwf); // SchurDiagMooeeOperator<DomainWallFermionR,LatticeFermion> HermOp(Ddwf);
const int Nstop = 30; const int Nstop = 30;
const int Nu = 4;
const int Nk = 60; const int Nk = 60;
const int Np = 60; const int Np = 60;
const int Nm = Nk+Np; const int Nm = Nk+Np;
@ -92,19 +93,21 @@ int main (int argc, char ** argv)
// ChebyshevLanczos<LatticeFermion> Cheb(9.,1.,0.,20); // ChebyshevLanczos<LatticeFermion> Cheb(9.,1.,0.,20);
// Cheb.csv(std::cout); // Cheb.csv(std::cout);
// exit(-24); // exit(-24);
ImplicitlyRestartedLanczos<FermionField> IRL(HermOp,Cheb,Nstop,Nk,Nm,resid,MaxIt); ImplicitlyRestartedBlockLanczos<FermionField> IRBL(HermOp,Cheb,Nstop,Nu,Nk,Nm,resid,MaxIt);
std::vector<RealD> eval(Nm); std::vector<RealD> eval(Nm);
FermionField src(FrbGrid);
gaussian(RNG5rb,src); std::vector<FermionField> src(Nu,FrbGrid);
for ( int i=0; i<Nu; ++i ) gaussian(RNG5rb,src[i]);
std::vector<FermionField> evec(Nm,FrbGrid); std::vector<FermionField> evec(Nm,FrbGrid);
for(int i=0;i<1;i++){ for(int i=0;i<1;++i){
std::cout << GridLogMessage <<i<<" / "<< Nm<< " grid pointer "<<evec[i]._grid<<std::endl; clog << i <<" / "<< Nm <<" grid pointer "<< evec[i]._grid << std::endl;
}; };
int Nconv; int Nconv;
IRL.calc(eval,evec,src,Nconv); IRBL.calc(eval,evec,src,Nconv);
Grid_finalize(); Grid_finalize();