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Merge commit 'a7d56523abee6c9030fdd9303c79954897b1086f' into feature/hadrons
This commit is contained in:
commit
b22eab8c8b
28
TODO
28
TODO
@ -1,24 +1,30 @@
|
||||
TODO:
|
||||
---------------
|
||||
|
||||
Peter's work list:
|
||||
1)- Precision conversion and sort out localConvert <--
|
||||
2)- Remove DenseVector, DenseMatrix; Use Eigen instead. <--
|
||||
Large item work list:
|
||||
1)- MultiRHS with spread out extra dim -- Go through filesystem with SciDAC I/O
|
||||
|
||||
-- Profile CG, BlockCG, etc... Flop count/rate -- PARTIAL, time but no flop/s yet
|
||||
-- Physical propagator interface
|
||||
-- Conserved currents
|
||||
-- GaugeFix into central location
|
||||
-- Multigrid Wilson and DWF, compare to other Multigrid implementations
|
||||
-- HDCR resume
|
||||
2)- Christoph's local basis expansion Lanczos
|
||||
3)- BG/Q port and check
|
||||
4)- Precision conversion and sort out localConvert <-- partial
|
||||
- Consistent linear solver flop count/rate -- PARTIAL, time but no flop/s yet
|
||||
5)- Physical propagator interface
|
||||
6)- Conserved currents
|
||||
7)- Multigrid Wilson and DWF, compare to other Multigrid implementations
|
||||
8)- HDCR resume
|
||||
|
||||
Recent DONE
|
||||
-- Lanczos Remove DenseVector, DenseMatrix; Use Eigen instead. <-- DONE
|
||||
-- GaugeFix into central location <-- DONE
|
||||
-- Scidac and Ildg metadata handling <-- DONE
|
||||
-- Binary I/O MPI2 IO <-- DONE
|
||||
-- Binary I/O speed up & x-strips <-- DONE
|
||||
-- Cut down the exterior overhead <-- DONE
|
||||
-- Interior legs from SHM comms <-- DONE
|
||||
-- Half-precision comms <-- DONE
|
||||
-- Merge high precision reduction into develop
|
||||
-- multiRHS DWF; benchmark on Cori/BNL for comms elimination
|
||||
-- Merge high precision reduction into develop <-- DONE
|
||||
-- BlockCG, BCGrQ <-- DONE
|
||||
-- multiRHS DWF; benchmark on Cori/BNL for comms elimination <-- DONE
|
||||
-- slice* linalg routines for multiRHS, BlockCG
|
||||
|
||||
-----
|
||||
|
||||
@ -1,137 +0,0 @@
|
||||
/*************************************************************************************
|
||||
|
||||
Grid physics library, www.github.com/paboyle/Grid
|
||||
|
||||
Source file: ./lib/algorithms/iterative/DenseMatrix.h
|
||||
|
||||
Copyright (C) 2015
|
||||
|
||||
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
|
||||
Author: paboyle <paboyle@ph.ed.ac.uk>
|
||||
|
||||
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_DENSE_MATRIX_H
|
||||
#define GRID_DENSE_MATRIX_H
|
||||
|
||||
namespace Grid {
|
||||
/////////////////////////////////////////////////////////////
|
||||
// Matrix untils
|
||||
/////////////////////////////////////////////////////////////
|
||||
|
||||
template<class T> using DenseVector = std::vector<T>;
|
||||
template<class T> using DenseMatrix = DenseVector<DenseVector<T> >;
|
||||
|
||||
template<class T> void Size(DenseVector<T> & vec, int &N)
|
||||
{
|
||||
N= vec.size();
|
||||
}
|
||||
template<class T> void Size(DenseMatrix<T> & mat, int &N,int &M)
|
||||
{
|
||||
N= mat.size();
|
||||
M= mat[0].size();
|
||||
}
|
||||
|
||||
template<class T> void SizeSquare(DenseMatrix<T> & mat, int &N)
|
||||
{
|
||||
int M; Size(mat,N,M);
|
||||
assert(N==M);
|
||||
}
|
||||
|
||||
template<class T> void Resize(DenseVector<T > & mat, int N) {
|
||||
mat.resize(N);
|
||||
}
|
||||
template<class T> void Resize(DenseMatrix<T > & mat, int N, int M) {
|
||||
mat.resize(N);
|
||||
for(int i=0;i<N;i++){
|
||||
mat[i].resize(M);
|
||||
}
|
||||
}
|
||||
template<class T> void Fill(DenseMatrix<T> & mat, T&val) {
|
||||
int N,M;
|
||||
Size(mat,N,M);
|
||||
for(int i=0;i<N;i++){
|
||||
for(int j=0;j<M;j++){
|
||||
mat[i][j] = val;
|
||||
}}
|
||||
}
|
||||
|
||||
/** Transpose of a matrix **/
|
||||
template<class T> DenseMatrix<T> Transpose(DenseMatrix<T> & mat){
|
||||
int N,M;
|
||||
Size(mat,N,M);
|
||||
DenseMatrix<T> C; Resize(C,M,N);
|
||||
for(int i=0;i<M;i++){
|
||||
for(int j=0;j<N;j++){
|
||||
C[i][j] = mat[j][i];
|
||||
}}
|
||||
return C;
|
||||
}
|
||||
/** Set DenseMatrix to unit matrix **/
|
||||
template<class T> void Unity(DenseMatrix<T> &A){
|
||||
int N; SizeSquare(A,N);
|
||||
for(int i=0;i<N;i++){
|
||||
for(int j=0;j<N;j++){
|
||||
if ( i==j ) A[i][j] = 1;
|
||||
else A[i][j] = 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/** Add C * I to matrix **/
|
||||
template<class T>
|
||||
void PlusUnit(DenseMatrix<T> & A,T c){
|
||||
int dim; SizeSquare(A,dim);
|
||||
for(int i=0;i<dim;i++){A[i][i] = A[i][i] + c;}
|
||||
}
|
||||
|
||||
/** return the Hermitian conjugate of matrix **/
|
||||
template<class T>
|
||||
DenseMatrix<T> HermitianConj(DenseMatrix<T> &mat){
|
||||
|
||||
int dim; SizeSquare(mat,dim);
|
||||
|
||||
DenseMatrix<T> C; Resize(C,dim,dim);
|
||||
|
||||
for(int i=0;i<dim;i++){
|
||||
for(int j=0;j<dim;j++){
|
||||
C[i][j] = conj(mat[j][i]);
|
||||
}
|
||||
}
|
||||
return C;
|
||||
}
|
||||
/**Get a square submatrix**/
|
||||
template <class T>
|
||||
DenseMatrix<T> GetSubMtx(DenseMatrix<T> &A,int row_st, int row_end, int col_st, int col_end)
|
||||
{
|
||||
DenseMatrix<T> H; Resize(H,row_end - row_st,col_end-col_st);
|
||||
|
||||
for(int i = row_st; i<row_end; i++){
|
||||
for(int j = col_st; j<col_end; j++){
|
||||
H[i-row_st][j-col_st]=A[i][j];
|
||||
}}
|
||||
return H;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
#include "Householder.h"
|
||||
#include "Francis.h"
|
||||
|
||||
#endif
|
||||
|
||||
@ -1,525 +0,0 @@
|
||||
/*************************************************************************************
|
||||
|
||||
Grid physics library, www.github.com/paboyle/Grid
|
||||
|
||||
Source file: ./lib/algorithms/iterative/Francis.h
|
||||
|
||||
Copyright (C) 2015
|
||||
|
||||
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
|
||||
|
||||
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 FRANCIS_H
|
||||
#define FRANCIS_H
|
||||
|
||||
#include <cstdlib>
|
||||
#include <string>
|
||||
#include <cmath>
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include <stdexcept>
|
||||
#include <fstream>
|
||||
#include <complex>
|
||||
#include <algorithm>
|
||||
|
||||
//#include <timer.h>
|
||||
//#include <lapacke.h>
|
||||
//#include <Eigen/Dense>
|
||||
|
||||
namespace Grid {
|
||||
|
||||
template <class T> int SymmEigensystem(DenseMatrix<T > &Ain, DenseVector<T> &evals, DenseMatrix<T> &evecs, RealD small);
|
||||
template <class T> int Eigensystem(DenseMatrix<T > &Ain, DenseVector<T> &evals, DenseMatrix<T> &evecs, RealD small);
|
||||
|
||||
/**
|
||||
Find the eigenvalues of an upper hessenberg matrix using the Francis QR algorithm.
|
||||
H =
|
||||
x x x x x x x x x
|
||||
x x x x x x x x x
|
||||
0 x x x x x x x x
|
||||
0 0 x x x x x x x
|
||||
0 0 0 x x x x x x
|
||||
0 0 0 0 x x x x x
|
||||
0 0 0 0 0 x x x x
|
||||
0 0 0 0 0 0 x x x
|
||||
0 0 0 0 0 0 0 x x
|
||||
Factorization is P T P^H where T is upper triangular (mod cc blocks) and P is orthagonal/unitary.
|
||||
**/
|
||||
template <class T>
|
||||
int QReigensystem(DenseMatrix<T> &Hin, DenseVector<T> &evals, DenseMatrix<T> &evecs, RealD small)
|
||||
{
|
||||
DenseMatrix<T> H = Hin;
|
||||
|
||||
int N ; SizeSquare(H,N);
|
||||
int M = N;
|
||||
|
||||
Fill(evals,0);
|
||||
Fill(evecs,0);
|
||||
|
||||
T s,t,x=0,y=0,z=0;
|
||||
T u,d;
|
||||
T apd,amd,bc;
|
||||
DenseVector<T> p(N,0);
|
||||
T nrm = Norm(H); ///DenseMatrix Norm
|
||||
int n, m;
|
||||
int e = 0;
|
||||
int it = 0;
|
||||
int tot_it = 0;
|
||||
int l = 0;
|
||||
int r = 0;
|
||||
DenseMatrix<T> P; Resize(P,N,N); Unity(P);
|
||||
DenseVector<int> trows(N,0);
|
||||
|
||||
/// Check if the matrix is really hessenberg, if not abort
|
||||
RealD sth = 0;
|
||||
for(int j=0;j<N;j++){
|
||||
for(int i=j+2;i<N;i++){
|
||||
sth = abs(H[i][j]);
|
||||
if(sth > small){
|
||||
std::cout << "Non hessenberg H = " << sth << " > " << small << std::endl;
|
||||
exit(1);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
do{
|
||||
std::cout << "Francis QR Step N = " << N << std::endl;
|
||||
/** Check for convergence
|
||||
x x x x x
|
||||
0 x x x x
|
||||
0 0 x x x
|
||||
0 0 x x x
|
||||
0 0 0 0 x
|
||||
for this matrix l = 4
|
||||
**/
|
||||
do{
|
||||
l = Chop_subdiag(H,nrm,e,small);
|
||||
r = 0; ///May have converged on more than one eval
|
||||
///Single eval
|
||||
if(l == N-1){
|
||||
evals[e] = H[l][l];
|
||||
N--; e++; r++; it = 0;
|
||||
}
|
||||
///RealD eval
|
||||
if(l == N-2){
|
||||
trows[l+1] = 1; ///Needed for UTSolve
|
||||
apd = H[l][l] + H[l+1][l+1];
|
||||
amd = H[l][l] - H[l+1][l+1];
|
||||
bc = (T)4.0*H[l+1][l]*H[l][l+1];
|
||||
evals[e] = (T)0.5*( apd + sqrt(amd*amd + bc) );
|
||||
evals[e+1] = (T)0.5*( apd - sqrt(amd*amd + bc) );
|
||||
N-=2; e+=2; r++; it = 0;
|
||||
}
|
||||
} while(r>0);
|
||||
|
||||
if(N ==0) break;
|
||||
|
||||
DenseVector<T > ck; Resize(ck,3);
|
||||
DenseVector<T> v; Resize(v,3);
|
||||
|
||||
for(int m = N-3; m >= l; m--){
|
||||
///Starting vector essentially random shift.
|
||||
if(it%10 == 0 && N >= 3 && it > 0){
|
||||
s = (T)1.618033989*( abs( H[N-1][N-2] ) + abs( H[N-2][N-3] ) );
|
||||
t = (T)0.618033989*( abs( H[N-1][N-2] ) + abs( H[N-2][N-3] ) );
|
||||
x = H[m][m]*H[m][m] + H[m][m+1]*H[m+1][m] - s*H[m][m] + t;
|
||||
y = H[m+1][m]*(H[m][m] + H[m+1][m+1] - s);
|
||||
z = H[m+1][m]*H[m+2][m+1];
|
||||
}
|
||||
///Starting vector implicit Q theorem
|
||||
else{
|
||||
s = (H[N-2][N-2] + H[N-1][N-1]);
|
||||
t = (H[N-2][N-2]*H[N-1][N-1] - H[N-2][N-1]*H[N-1][N-2]);
|
||||
x = H[m][m]*H[m][m] + H[m][m+1]*H[m+1][m] - s*H[m][m] + t;
|
||||
y = H[m+1][m]*(H[m][m] + H[m+1][m+1] - s);
|
||||
z = H[m+1][m]*H[m+2][m+1];
|
||||
}
|
||||
ck[0] = x; ck[1] = y; ck[2] = z;
|
||||
|
||||
if(m == l) break;
|
||||
|
||||
/** Some stupid thing from numerical recipies, seems to work**/
|
||||
// PAB.. for heaven's sake quote page, purpose, evidence it works.
|
||||
// what sort of comment is that!?!?!?
|
||||
u=abs(H[m][m-1])*(abs(y)+abs(z));
|
||||
d=abs(x)*(abs(H[m-1][m-1])+abs(H[m][m])+abs(H[m+1][m+1]));
|
||||
if ((T)abs(u+d) == (T)abs(d) ){
|
||||
l = m; break;
|
||||
}
|
||||
|
||||
//if (u < small){l = m; break;}
|
||||
}
|
||||
if(it > 100000){
|
||||
std::cout << "QReigensystem: bugger it got stuck after 100000 iterations" << std::endl;
|
||||
std::cout << "got " << e << " evals " << l << " " << N << std::endl;
|
||||
exit(1);
|
||||
}
|
||||
normalize(ck); ///Normalization cancels in PHP anyway
|
||||
T beta;
|
||||
Householder_vector<T >(ck, 0, 2, v, beta);
|
||||
Householder_mult<T >(H,v,beta,0,l,l+2,0);
|
||||
Householder_mult<T >(H,v,beta,0,l,l+2,1);
|
||||
///Accumulate eigenvector
|
||||
Householder_mult<T >(P,v,beta,0,l,l+2,1);
|
||||
int sw = 0; ///Are we on the last row?
|
||||
for(int k=l;k<N-2;k++){
|
||||
x = H[k+1][k];
|
||||
y = H[k+2][k];
|
||||
z = (T)0.0;
|
||||
if(k+3 <= N-1){
|
||||
z = H[k+3][k];
|
||||
} else{
|
||||
sw = 1;
|
||||
v[2] = (T)0.0;
|
||||
}
|
||||
ck[0] = x; ck[1] = y; ck[2] = z;
|
||||
normalize(ck);
|
||||
Householder_vector<T >(ck, 0, 2-sw, v, beta);
|
||||
Householder_mult<T >(H,v, beta,0,k+1,k+3-sw,0);
|
||||
Householder_mult<T >(H,v, beta,0,k+1,k+3-sw,1);
|
||||
///Accumulate eigenvector
|
||||
Householder_mult<T >(P,v, beta,0,k+1,k+3-sw,1);
|
||||
}
|
||||
it++;
|
||||
tot_it++;
|
||||
}while(N > 1);
|
||||
N = evals.size();
|
||||
///Annoying - UT solves in reverse order;
|
||||
DenseVector<T> tmp; Resize(tmp,N);
|
||||
for(int i=0;i<N;i++){
|
||||
tmp[i] = evals[N-i-1];
|
||||
}
|
||||
evals = tmp;
|
||||
UTeigenvectors(H, trows, evals, evecs);
|
||||
for(int i=0;i<evals.size();i++){evecs[i] = P*evecs[i]; normalize(evecs[i]);}
|
||||
return tot_it;
|
||||
}
|
||||
|
||||
template <class T>
|
||||
int my_Wilkinson(DenseMatrix<T> &Hin, DenseVector<T> &evals, DenseMatrix<T> &evecs, RealD small)
|
||||
{
|
||||
/**
|
||||
Find the eigenvalues of an upper Hessenberg matrix using the Wilkinson QR algorithm.
|
||||
H =
|
||||
x x 0 0 0 0
|
||||
x x x 0 0 0
|
||||
0 x x x 0 0
|
||||
0 0 x x x 0
|
||||
0 0 0 x x x
|
||||
0 0 0 0 x x
|
||||
Factorization is P T P^H where T is upper triangular (mod cc blocks) and P is orthagonal/unitary. **/
|
||||
return my_Wilkinson(Hin, evals, evecs, small, small);
|
||||
}
|
||||
|
||||
template <class T>
|
||||
int my_Wilkinson(DenseMatrix<T> &Hin, DenseVector<T> &evals, DenseMatrix<T> &evecs, RealD small, RealD tol)
|
||||
{
|
||||
int N; SizeSquare(Hin,N);
|
||||
int M = N;
|
||||
|
||||
///I don't want to modify the input but matricies must be passed by reference
|
||||
//Scale a matrix by its "norm"
|
||||
//RealD Hnorm = abs( Hin.LargestDiag() ); H = H*(1.0/Hnorm);
|
||||
DenseMatrix<T> H; H = Hin;
|
||||
|
||||
RealD Hnorm = abs(Norm(Hin));
|
||||
H = H * (1.0 / Hnorm);
|
||||
|
||||
// TODO use openmp and memset
|
||||
Fill(evals,0);
|
||||
Fill(evecs,0);
|
||||
|
||||
T s, t, x = 0, y = 0, z = 0;
|
||||
T u, d;
|
||||
T apd, amd, bc;
|
||||
DenseVector<T> p; Resize(p,N); Fill(p,0);
|
||||
|
||||
T nrm = Norm(H); ///DenseMatrix Norm
|
||||
int n, m;
|
||||
int e = 0;
|
||||
int it = 0;
|
||||
int tot_it = 0;
|
||||
int l = 0;
|
||||
int r = 0;
|
||||
DenseMatrix<T> P; Resize(P,N,N);
|
||||
Unity(P);
|
||||
DenseVector<int> trows(N, 0);
|
||||
/// Check if the matrix is really symm tridiag
|
||||
RealD sth = 0;
|
||||
for(int j = 0; j < N; ++j)
|
||||
{
|
||||
for(int i = j + 2; i < N; ++i)
|
||||
{
|
||||
if(abs(H[i][j]) > tol || abs(H[j][i]) > tol)
|
||||
{
|
||||
std::cout << "Non Tridiagonal H(" << i << ","<< j << ") = |" << Real( real( H[j][i] ) ) << "| > " << tol << std::endl;
|
||||
std::cout << "Warning tridiagonalize and call again" << std::endl;
|
||||
// exit(1); // see what is going on
|
||||
//return;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
do{
|
||||
do{
|
||||
//Jasper
|
||||
//Check if the subdiagonal term is small enough (<small)
|
||||
//if true then it is converged.
|
||||
//check start from H.dim - e - 1
|
||||
//How to deal with more than 2 are converged?
|
||||
//What if Chop_symm_subdiag return something int the middle?
|
||||
//--------------
|
||||
l = Chop_symm_subdiag(H,nrm, e, small);
|
||||
r = 0; ///May have converged on more than one eval
|
||||
//Jasper
|
||||
//In this case
|
||||
// x x 0 0 0 0
|
||||
// x x x 0 0 0
|
||||
// 0 x x x 0 0
|
||||
// 0 0 x x x 0
|
||||
// 0 0 0 x x 0
|
||||
// 0 0 0 0 0 x <- l
|
||||
//--------------
|
||||
///Single eval
|
||||
if(l == N - 1)
|
||||
{
|
||||
evals[e] = H[l][l];
|
||||
N--;
|
||||
e++;
|
||||
r++;
|
||||
it = 0;
|
||||
}
|
||||
//Jasper
|
||||
// x x 0 0 0 0
|
||||
// x x x 0 0 0
|
||||
// 0 x x x 0 0
|
||||
// 0 0 x x 0 0
|
||||
// 0 0 0 0 x x <- l
|
||||
// 0 0 0 0 x x
|
||||
//--------------
|
||||
///RealD eval
|
||||
if(l == N - 2)
|
||||
{
|
||||
trows[l + 1] = 1; ///Needed for UTSolve
|
||||
apd = H[l][l] + H[l + 1][ l + 1];
|
||||
amd = H[l][l] - H[l + 1][l + 1];
|
||||
bc = (T) 4.0 * H[l + 1][l] * H[l][l + 1];
|
||||
evals[e] = (T) 0.5 * (apd + sqrt(amd * amd + bc));
|
||||
evals[e + 1] = (T) 0.5 * (apd - sqrt(amd * amd + bc));
|
||||
N -= 2;
|
||||
e += 2;
|
||||
r++;
|
||||
it = 0;
|
||||
}
|
||||
}while(r > 0);
|
||||
//Jasper
|
||||
//Already converged
|
||||
//--------------
|
||||
if(N == 0) break;
|
||||
|
||||
DenseVector<T> ck,v; Resize(ck,2); Resize(v,2);
|
||||
|
||||
for(int m = N - 3; m >= l; m--)
|
||||
{
|
||||
///Starting vector essentially random shift.
|
||||
if(it%10 == 0 && N >= 3 && it > 0)
|
||||
{
|
||||
t = abs(H[N - 1][N - 2]) + abs(H[N - 2][N - 3]);
|
||||
x = H[m][m] - t;
|
||||
z = H[m + 1][m];
|
||||
} else {
|
||||
///Starting vector implicit Q theorem
|
||||
d = (H[N - 2][N - 2] - H[N - 1][N - 1]) * (T) 0.5;
|
||||
t = H[N - 1][N - 1] - H[N - 1][N - 2] * H[N - 1][N - 2]
|
||||
/ (d + sign(d) * sqrt(d * d + H[N - 1][N - 2] * H[N - 1][N - 2]));
|
||||
x = H[m][m] - t;
|
||||
z = H[m + 1][m];
|
||||
}
|
||||
//Jasper
|
||||
//why it is here????
|
||||
//-----------------------
|
||||
if(m == l)
|
||||
break;
|
||||
|
||||
u = abs(H[m][m - 1]) * (abs(y) + abs(z));
|
||||
d = abs(x) * (abs(H[m - 1][m - 1]) + abs(H[m][m]) + abs(H[m + 1][m + 1]));
|
||||
if ((T)abs(u + d) == (T)abs(d))
|
||||
{
|
||||
l = m;
|
||||
break;
|
||||
}
|
||||
}
|
||||
//Jasper
|
||||
if(it > 1000000)
|
||||
{
|
||||
std::cout << "Wilkinson: bugger it got stuck after 100000 iterations" << std::endl;
|
||||
std::cout << "got " << e << " evals " << l << " " << N << std::endl;
|
||||
exit(1);
|
||||
}
|
||||
//
|
||||
T s, c;
|
||||
Givens_calc<T>(x, z, c, s);
|
||||
Givens_mult<T>(H, l, l + 1, c, -s, 0);
|
||||
Givens_mult<T>(H, l, l + 1, c, s, 1);
|
||||
Givens_mult<T>(P, l, l + 1, c, s, 1);
|
||||
//
|
||||
for(int k = l; k < N - 2; ++k)
|
||||
{
|
||||
x = H.A[k + 1][k];
|
||||
z = H.A[k + 2][k];
|
||||
Givens_calc<T>(x, z, c, s);
|
||||
Givens_mult<T>(H, k + 1, k + 2, c, -s, 0);
|
||||
Givens_mult<T>(H, k + 1, k + 2, c, s, 1);
|
||||
Givens_mult<T>(P, k + 1, k + 2, c, s, 1);
|
||||
}
|
||||
it++;
|
||||
tot_it++;
|
||||
}while(N > 1);
|
||||
|
||||
N = evals.size();
|
||||
///Annoying - UT solves in reverse order;
|
||||
DenseVector<T> tmp(N);
|
||||
for(int i = 0; i < N; ++i)
|
||||
tmp[i] = evals[N-i-1];
|
||||
evals = tmp;
|
||||
//
|
||||
UTeigenvectors(H, trows, evals, evecs);
|
||||
//UTSymmEigenvectors(H, trows, evals, evecs);
|
||||
for(int i = 0; i < evals.size(); ++i)
|
||||
{
|
||||
evecs[i] = P * evecs[i];
|
||||
normalize(evecs[i]);
|
||||
evals[i] = evals[i] * Hnorm;
|
||||
}
|
||||
// // FIXME this is to test
|
||||
// Hin.write("evecs3", evecs);
|
||||
// Hin.write("evals3", evals);
|
||||
// // check rsd
|
||||
// for(int i = 0; i < M; i++) {
|
||||
// vector<T> Aevec = Hin * evecs[i];
|
||||
// RealD norm2(0.);
|
||||
// for(int j = 0; j < M; j++) {
|
||||
// norm2 += (Aevec[j] - evals[i] * evecs[i][j]) * (Aevec[j] - evals[i] * evecs[i][j]);
|
||||
// }
|
||||
// }
|
||||
return tot_it;
|
||||
}
|
||||
|
||||
template <class T>
|
||||
void Hess(DenseMatrix<T > &A, DenseMatrix<T> &Q, int start){
|
||||
|
||||
/**
|
||||
turn a matrix A =
|
||||
x x x x x
|
||||
x x x x x
|
||||
x x x x x
|
||||
x x x x x
|
||||
x x x x x
|
||||
into
|
||||
x x x x x
|
||||
x x x x x
|
||||
0 x x x x
|
||||
0 0 x x x
|
||||
0 0 0 x x
|
||||
with householder rotations
|
||||
Slow.
|
||||
*/
|
||||
int N ; SizeSquare(A,N);
|
||||
DenseVector<T > p; Resize(p,N); Fill(p,0);
|
||||
|
||||
for(int k=start;k<N-2;k++){
|
||||
//cerr << "hess" << k << std::endl;
|
||||
DenseVector<T > ck,v; Resize(ck,N-k-1); Resize(v,N-k-1);
|
||||
for(int i=k+1;i<N;i++){ck[i-k-1] = A(i,k);} ///kth column
|
||||
normalize(ck); ///Normalization cancels in PHP anyway
|
||||
T beta;
|
||||
Householder_vector<T >(ck, 0, ck.size()-1, v, beta); ///Householder vector
|
||||
Householder_mult<T>(A,v,beta,start,k+1,N-1,0); ///A -> PA
|
||||
Householder_mult<T >(A,v,beta,start,k+1,N-1,1); ///PA -> PAP^H
|
||||
///Accumulate eigenvector
|
||||
Householder_mult<T >(Q,v,beta,start,k+1,N-1,1); ///Q -> QP^H
|
||||
}
|
||||
/*for(int l=0;l<N-2;l++){
|
||||
for(int k=l+2;k<N;k++){
|
||||
A(0,k,l);
|
||||
}
|
||||
}*/
|
||||
}
|
||||
|
||||
template <class T>
|
||||
void Tri(DenseMatrix<T > &A, DenseMatrix<T> &Q, int start){
|
||||
///Tridiagonalize a matrix
|
||||
int N; SizeSquare(A,N);
|
||||
Hess(A,Q,start);
|
||||
/*for(int l=0;l<N-2;l++){
|
||||
for(int k=l+2;k<N;k++){
|
||||
A(0,l,k);
|
||||
}
|
||||
}*/
|
||||
}
|
||||
|
||||
template <class T>
|
||||
void ForceTridiagonal(DenseMatrix<T> &A){
|
||||
///Tridiagonalize a matrix
|
||||
int N ; SizeSquare(A,N);
|
||||
for(int l=0;l<N-2;l++){
|
||||
for(int k=l+2;k<N;k++){
|
||||
A[l][k]=0;
|
||||
A[k][l]=0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template <class T>
|
||||
int my_SymmEigensystem(DenseMatrix<T > &Ain, DenseVector<T> &evals, DenseVector<DenseVector<T> > &evecs, RealD small){
|
||||
///Solve a symmetric eigensystem, not necessarily in tridiagonal form
|
||||
int N; SizeSquare(Ain,N);
|
||||
DenseMatrix<T > A; A = Ain;
|
||||
DenseMatrix<T > Q; Resize(Q,N,N); Unity(Q);
|
||||
Tri(A,Q,0);
|
||||
int it = my_Wilkinson<T>(A, evals, evecs, small);
|
||||
for(int k=0;k<N;k++){evecs[k] = Q*evecs[k];}
|
||||
return it;
|
||||
}
|
||||
|
||||
|
||||
template <class T>
|
||||
int Wilkinson(DenseMatrix<T> &Ain, DenseVector<T> &evals, DenseVector<DenseVector<T> > &evecs, RealD small){
|
||||
return my_Wilkinson(Ain, evals, evecs, small);
|
||||
}
|
||||
|
||||
template <class T>
|
||||
int SymmEigensystem(DenseMatrix<T> &Ain, DenseVector<T> &evals, DenseVector<DenseVector<T> > &evecs, RealD small){
|
||||
return my_SymmEigensystem(Ain, evals, evecs, small);
|
||||
}
|
||||
|
||||
template <class T>
|
||||
int Eigensystem(DenseMatrix<T > &Ain, DenseVector<T> &evals, DenseVector<DenseVector<T> > &evecs, RealD small){
|
||||
///Solve a general eigensystem, not necessarily in tridiagonal form
|
||||
int N = Ain.dim;
|
||||
DenseMatrix<T > A(N); A = Ain;
|
||||
DenseMatrix<T > Q(N);Q.Unity();
|
||||
Hess(A,Q,0);
|
||||
int it = QReigensystem<T>(A, evals, evecs, small);
|
||||
for(int k=0;k<N;k++){evecs[k] = Q*evecs[k];}
|
||||
return it;
|
||||
}
|
||||
|
||||
}
|
||||
#endif
|
||||
@ -1,242 +0,0 @@
|
||||
/*************************************************************************************
|
||||
|
||||
Grid physics library, www.github.com/paboyle/Grid
|
||||
|
||||
Source file: ./lib/algorithms/iterative/Householder.h
|
||||
|
||||
Copyright (C) 2015
|
||||
|
||||
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
|
||||
|
||||
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 HOUSEHOLDER_H
|
||||
#define HOUSEHOLDER_H
|
||||
|
||||
#define TIMER(A) std::cout << GridLogMessage << __FUNC__ << " file "<< __FILE__ <<" line " << __LINE__ << std::endl;
|
||||
#define ENTER() std::cout << GridLogMessage << "ENTRY "<<__FUNC__ << " file "<< __FILE__ <<" line " << __LINE__ << std::endl;
|
||||
#define LEAVE() std::cout << GridLogMessage << "EXIT "<<__FUNC__ << " file "<< __FILE__ <<" line " << __LINE__ << std::endl;
|
||||
|
||||
#include <cstdlib>
|
||||
#include <string>
|
||||
#include <cmath>
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include <stdexcept>
|
||||
#include <fstream>
|
||||
#include <complex>
|
||||
#include <algorithm>
|
||||
|
||||
namespace Grid {
|
||||
/** Comparison function for finding the max element in a vector **/
|
||||
template <class T> bool cf(T i, T j) {
|
||||
return abs(i) < abs(j);
|
||||
}
|
||||
|
||||
/**
|
||||
Calculate a real Givens angle
|
||||
**/
|
||||
template <class T> inline void Givens_calc(T y, T z, T &c, T &s){
|
||||
|
||||
RealD mz = (RealD)abs(z);
|
||||
|
||||
if(mz==0.0){
|
||||
c = 1; s = 0;
|
||||
}
|
||||
if(mz >= (RealD)abs(y)){
|
||||
T t = -y/z;
|
||||
s = (T)1.0 / sqrt ((T)1.0 + t * t);
|
||||
c = s * t;
|
||||
} else {
|
||||
T t = -z/y;
|
||||
c = (T)1.0 / sqrt ((T)1.0 + t * t);
|
||||
s = c * t;
|
||||
}
|
||||
}
|
||||
|
||||
template <class T> inline void Givens_mult(DenseMatrix<T> &A, int i, int k, T c, T s, int dir)
|
||||
{
|
||||
int q ; SizeSquare(A,q);
|
||||
|
||||
if(dir == 0){
|
||||
for(int j=0;j<q;j++){
|
||||
T nu = A[i][j];
|
||||
T w = A[k][j];
|
||||
A[i][j] = (c*nu + s*w);
|
||||
A[k][j] = (-s*nu + c*w);
|
||||
}
|
||||
}
|
||||
|
||||
if(dir == 1){
|
||||
for(int j=0;j<q;j++){
|
||||
T nu = A[j][i];
|
||||
T w = A[j][k];
|
||||
A[j][i] = (c*nu - s*w);
|
||||
A[j][k] = (s*nu + c*w);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
from input = x;
|
||||
Compute the complex Householder vector, v, such that
|
||||
P = (I - b v transpose(v) )
|
||||
b = 2/v.v
|
||||
|
||||
P | x | | x | k = 0
|
||||
| x | | 0 |
|
||||
| x | = | 0 |
|
||||
| x | | 0 | j = 3
|
||||
| x | | x |
|
||||
|
||||
These are the "Unreduced" Householder vectors.
|
||||
|
||||
**/
|
||||
template <class T> inline void Householder_vector(DenseVector<T> input, int k, int j, DenseVector<T> &v, T &beta)
|
||||
{
|
||||
int N ; Size(input,N);
|
||||
T m = *max_element(input.begin() + k, input.begin() + j + 1, cf<T> );
|
||||
|
||||
if(abs(m) > 0.0){
|
||||
T alpha = 0;
|
||||
|
||||
for(int i=k; i<j+1; i++){
|
||||
v[i] = input[i]/m;
|
||||
alpha = alpha + v[i]*conj(v[i]);
|
||||
}
|
||||
alpha = sqrt(alpha);
|
||||
beta = (T)1.0/(alpha*(alpha + abs(v[k]) ));
|
||||
|
||||
if(abs(v[k]) > 0.0) v[k] = v[k] + (v[k]/abs(v[k]))*alpha;
|
||||
else v[k] = -alpha;
|
||||
} else{
|
||||
for(int i=k; i<j+1; i++){
|
||||
v[i] = 0.0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
from input = x;
|
||||
Compute the complex Householder vector, v, such that
|
||||
P = (I - b v transpose(v) )
|
||||
b = 2/v.v
|
||||
|
||||
Px = alpha*e_dir
|
||||
|
||||
These are the "Unreduced" Householder vectors.
|
||||
|
||||
**/
|
||||
|
||||
template <class T> inline void Householder_vector(DenseVector<T> input, int k, int j, int dir, DenseVector<T> &v, T &beta)
|
||||
{
|
||||
int N = input.size();
|
||||
T m = *max_element(input.begin() + k, input.begin() + j + 1, cf);
|
||||
|
||||
if(abs(m) > 0.0){
|
||||
T alpha = 0;
|
||||
|
||||
for(int i=k; i<j+1; i++){
|
||||
v[i] = input[i]/m;
|
||||
alpha = alpha + v[i]*conj(v[i]);
|
||||
}
|
||||
|
||||
alpha = sqrt(alpha);
|
||||
beta = 1.0/(alpha*(alpha + abs(v[dir]) ));
|
||||
|
||||
if(abs(v[dir]) > 0.0) v[dir] = v[dir] + (v[dir]/abs(v[dir]))*alpha;
|
||||
else v[dir] = -alpha;
|
||||
}else{
|
||||
for(int i=k; i<j+1; i++){
|
||||
v[i] = 0.0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
Compute the product PA if trans = 0
|
||||
AP if trans = 1
|
||||
P = (I - b v transpose(v) )
|
||||
b = 2/v.v
|
||||
start at element l of matrix A
|
||||
v is of length j - k + 1 of v are nonzero
|
||||
**/
|
||||
|
||||
template <class T> inline void Householder_mult(DenseMatrix<T> &A , DenseVector<T> v, T beta, int l, int k, int j, int trans)
|
||||
{
|
||||
int N ; SizeSquare(A,N);
|
||||
|
||||
if(abs(beta) > 0.0){
|
||||
for(int p=l; p<N; p++){
|
||||
T s = 0;
|
||||
if(trans==0){
|
||||
for(int i=k;i<j+1;i++) s += conj(v[i-k])*A[i][p];
|
||||
s *= beta;
|
||||
for(int i=k;i<j+1;i++){ A[i][p] = A[i][p]-s*conj(v[i-k]);}
|
||||
} else {
|
||||
for(int i=k;i<j+1;i++){ s += conj(v[i-k])*A[p][i];}
|
||||
s *= beta;
|
||||
for(int i=k;i<j+1;i++){ A[p][i]=A[p][i]-s*conj(v[i-k]);}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
Compute the product PA if trans = 0
|
||||
AP if trans = 1
|
||||
P = (I - b v transpose(v) )
|
||||
b = 2/v.v
|
||||
start at element l of matrix A
|
||||
v is of length j - k + 1 of v are nonzero
|
||||
A is tridiagonal
|
||||
**/
|
||||
template <class T> inline void Householder_mult_tri(DenseMatrix<T> &A , DenseVector<T> v, T beta, int l, int M, int k, int j, int trans)
|
||||
{
|
||||
if(abs(beta) > 0.0){
|
||||
|
||||
int N ; SizeSquare(A,N);
|
||||
|
||||
DenseMatrix<T> tmp; Resize(tmp,N,N); Fill(tmp,0);
|
||||
|
||||
T s;
|
||||
for(int p=l; p<M; p++){
|
||||
s = 0;
|
||||
if(trans==0){
|
||||
for(int i=k;i<j+1;i++) s = s + conj(v[i-k])*A[i][p];
|
||||
}else{
|
||||
for(int i=k;i<j+1;i++) s = s + v[i-k]*A[p][i];
|
||||
}
|
||||
s = beta*s;
|
||||
if(trans==0){
|
||||
for(int i=k;i<j+1;i++) tmp[i][p] = tmp(i,p) - s*v[i-k];
|
||||
}else{
|
||||
for(int i=k;i<j+1;i++) tmp[p][i] = tmp[p][i] - s*conj(v[i-k]);
|
||||
}
|
||||
}
|
||||
for(int p=l; p<M; p++){
|
||||
if(trans==0){
|
||||
for(int i=k;i<j+1;i++) A[i][p] = A[i][p] + tmp[i][p];
|
||||
}else{
|
||||
for(int i=k;i<j+1;i++) A[p][i] = A[p][i] + tmp[p][i];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
#endif
|
||||
@ -56,11 +56,8 @@ class BlockConjugateGradient : public OperatorFunction<Field> {
|
||||
Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
|
||||
|
||||
BlockConjugateGradient(BlockCGtype cgtype,int _Orthog,RealD tol, Integer maxit, bool err_on_no_conv = true)
|
||||
: Tolerance(tol),
|
||||
CGtype(cgtype),
|
||||
blockDim(_Orthog),
|
||||
MaxIterations(maxit),
|
||||
ErrorOnNoConverge(err_on_no_conv){};
|
||||
: Tolerance(tol), CGtype(cgtype), blockDim(_Orthog), MaxIterations(maxit), ErrorOnNoConverge(err_on_no_conv)
|
||||
{};
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
// Thin QR factorisation (google it)
|
||||
|
||||
@ -1,81 +0,0 @@
|
||||
/*************************************************************************************
|
||||
|
||||
Grid physics library, www.github.com/paboyle/Grid
|
||||
|
||||
Source file: ./lib/algorithms/iterative/EigenSort.h
|
||||
|
||||
Copyright (C) 2015
|
||||
|
||||
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
|
||||
|
||||
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_EIGENSORT_H
|
||||
#define GRID_EIGENSORT_H
|
||||
|
||||
|
||||
namespace Grid {
|
||||
/////////////////////////////////////////////////////////////
|
||||
// Eigen sorter to begin with
|
||||
/////////////////////////////////////////////////////////////
|
||||
|
||||
template<class Field>
|
||||
class SortEigen {
|
||||
private:
|
||||
|
||||
//hacking for testing for now
|
||||
private:
|
||||
static bool less_lmd(RealD left,RealD right){
|
||||
return left > right;
|
||||
}
|
||||
static bool less_pair(std::pair<RealD,Field const*>& left,
|
||||
std::pair<RealD,Field const*>& right){
|
||||
return left.first > (right.first);
|
||||
}
|
||||
|
||||
|
||||
public:
|
||||
|
||||
void push(DenseVector<RealD>& lmd,
|
||||
DenseVector<Field>& evec,int N) {
|
||||
DenseVector<Field> cpy(lmd.size(),evec[0]._grid);
|
||||
for(int i=0;i<lmd.size();i++) cpy[i] = evec[i];
|
||||
|
||||
DenseVector<std::pair<RealD, Field const*> > emod(lmd.size());
|
||||
for(int i=0;i<lmd.size();++i)
|
||||
emod[i] = std::pair<RealD,Field const*>(lmd[i],&cpy[i]);
|
||||
|
||||
partial_sort(emod.begin(),emod.begin()+N,emod.end(),less_pair);
|
||||
|
||||
typename DenseVector<std::pair<RealD, Field const*> >::iterator it = emod.begin();
|
||||
for(int i=0;i<N;++i){
|
||||
lmd[i]=it->first;
|
||||
evec[i]=*(it->second);
|
||||
++it;
|
||||
}
|
||||
}
|
||||
void push(DenseVector<RealD>& lmd,int N) {
|
||||
std::partial_sort(lmd.begin(),lmd.begin()+N,lmd.end(),less_lmd);
|
||||
}
|
||||
bool saturated(RealD lmd, RealD thrs) {
|
||||
return fabs(lmd) > fabs(thrs);
|
||||
}
|
||||
};
|
||||
|
||||
}
|
||||
#endif
|
||||
File diff suppressed because it is too large
Load Diff
@ -102,7 +102,7 @@ class ILDGHmcCheckpointer : public BaseHmcCheckpointer<Implementation> {
|
||||
FieldMetaData header;
|
||||
IldgReader _IldgReader;
|
||||
_IldgReader.open(config);
|
||||
_IldgReader.readConfiguration(config,U,header); // format from the header
|
||||
_IldgReader.readConfiguration(U,header); // format from the header
|
||||
_IldgReader.close();
|
||||
|
||||
std::cout << GridLogMessage << "Read ILDG Configuration from " << config
|
||||
|
||||
@ -133,8 +133,8 @@ int main (int argc, char ** argv)
|
||||
int Nconv;
|
||||
RealD eresid = 1.0e-6;
|
||||
|
||||
ImplicitlyRestartedLanczos<LatticeComplex> IRL(HermOp,X,Nk,Nm,eresid,Nit);
|
||||
ImplicitlyRestartedLanczos<LatticeComplex> ChebyIRL(HermOp,Cheby,Nk,Nm,eresid,Nit);
|
||||
ImplicitlyRestartedLanczos<LatticeComplex> IRL(HermOp,X,Nk,Nk,Nm,eresid,Nit);
|
||||
ImplicitlyRestartedLanczos<LatticeComplex> ChebyIRL(HermOp,Cheby,Nk,Nk,Nm,eresid,Nit);
|
||||
|
||||
LatticeComplex src(grid); gaussian(RNG,src);
|
||||
{
|
||||
|
||||
@ -54,7 +54,7 @@ int main (int argc, char ** argv)
|
||||
GridParallelRNG RNG5rb(FrbGrid); RNG5.SeedFixedIntegers(seeds5);
|
||||
|
||||
LatticeGaugeField Umu(UGrid);
|
||||
SU3::TepidConfiguration(RNG4, Umu);
|
||||
SU3::HotConfiguration(RNG4, Umu);
|
||||
|
||||
std::vector<LatticeColourMatrix> U(4,UGrid);
|
||||
for(int mu=0;mu<Nd;mu++){
|
||||
@ -92,16 +92,15 @@ int main (int argc, char ** argv)
|
||||
|
||||
|
||||
std::vector<RealD> eval(Nm);
|
||||
FermionField src(FrbGrid); gaussian(RNG5rb,src);
|
||||
FermionField src(FrbGrid);
|
||||
gaussian(RNG5rb,src);
|
||||
std::vector<FermionField> evec(Nm,FrbGrid);
|
||||
for(int i=0;i<1;i++){
|
||||
std::cout << i<<" / "<< Nm<< " grid pointer "<<evec[i]._grid<<std::endl;
|
||||
std::cout << GridLogMessage <<i<<" / "<< Nm<< " grid pointer "<<evec[i]._grid<<std::endl;
|
||||
};
|
||||
|
||||
int Nconv;
|
||||
IRL.calc(eval,evec,
|
||||
src,
|
||||
Nconv);
|
||||
IRL.calc(eval,evec,src,Nconv);
|
||||
|
||||
|
||||
Grid_finalize();
|
||||
|
||||
Loading…
Reference in New Issue
Block a user