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https://github.com/paboyle/Grid.git
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Block compressed Lanczos
This commit is contained in:
paboyle
@@ -207,7 +207,6 @@ namespace Grid {
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void OpDir (const Field &in, Field &out,int dir,int disp) {
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assert(0);
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}
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};
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template<class Matrix,class Field>
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class SchurDiagMooeeOperator : public SchurOperatorBase<Field> {
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@@ -265,7 +264,6 @@ namespace Grid {
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return axpy_norm(out,-1.0,tmp,in);
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}
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};
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template<class Matrix,class Field>
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class SchurDiagTwoOperator : public SchurOperatorBase<Field> {
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protected:
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@@ -294,8 +292,15 @@ namespace Grid {
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return axpy_norm(out,-1.0,tmp,in);
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}
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};
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//
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///////////////////////////////////////////////////////////////////////////////////////////////////
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// Left handed Moo^-1 ; (Moo - Moe Mee^-1 Meo) psi = eta --> ( 1 - Moo^-1 Moe Mee^-1 Meo ) psi = Moo^-1 eta
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// Right handed Moo^-1 ; (Moo - Moe Mee^-1 Meo) Moo^-1 Moo psi = eta --> ( 1 - Moe Mee^-1 Meo ) Moo^-1 phi=eta ; psi = Moo^-1 phi
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///////////////////////////////////////////////////////////////////////////////////////////////////
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template<class Matrix,class Field> using SchurDiagOneRH = SchurDiagTwoOperator<Matrix,Field> ;
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template<class Matrix,class Field> using SchurDiagOneLH = SchurDiagOneOperator<Matrix,Field> ;
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///////////////////////////////////////////////////////////////////////////////////////////////////
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// Staggered use
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///////////////////////////////////////////////////////////////////////////////////////////////////
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template<class Matrix,class Field>
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class SchurStaggeredOperator : public SchurOperatorBase<Field> {
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protected:
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@@ -303,9 +308,8 @@ namespace Grid {
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public:
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SchurStaggeredOperator (Matrix &Mat): _Mat(Mat){};
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virtual void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
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ComplexD dot;
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n2 = Mpc(in,out);
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dot= innerProduct(in,out);
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ComplexD dot= innerProduct(in,out);
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n1 = real(dot);
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}
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virtual void HermOp(const Field &in, Field &out){
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@@ -0,0 +1,754 @@
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/*************************************************************************************
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Grid physics library, www.github.com/paboyle/Grid
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Source file: ./lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
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Copyright (C) 2015
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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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Author: Christoph Lehner <clehner@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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the Free Software Foundation; either version 2 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License along
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with this program; if not, write to the Free Software Foundation, Inc.,
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51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
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See the full license in the file "LICENSE" in the top level distribution directory
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*************************************************************************************/
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/* END LEGAL */
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#ifndef GRID_BIRL_H
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#define GRID_BIRL_H
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#include <string.h> //memset
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#include <zlib.h>
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#include <sys/stat.h>
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#include <Grid/algorithms/iterative/BlockImplicitlyRestartedLanczos/BlockedGrid.h>
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#include <Grid/algorithms/iterative/BlockImplicitlyRestartedLanczos/FieldBasisVector.h>
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#include <Grid/algorithms/iterative/BlockImplicitlyRestartedLanczos/BlockProjector.h>
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#include <Grid/algorithms/iterative/BlockImplicitlyRestartedLanczos/FieldVectorIO.h>
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namespace Grid {
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/////////////////////////////////////////////////////////////
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// Implicitly restarted lanczos
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/////////////////////////////////////////////////////////////
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template<class Field>
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class BlockImplicitlyRestartedLanczos {
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const RealD small = 1.0e-16;
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public:
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int lock;
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int get;
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int Niter;
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int converged;
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int Nminres; // Minimum number of restarts; only check for convergence after
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int Nstop; // Number of evecs checked for convergence
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int Nk; // Number of converged sought
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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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int orth_period;
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RealD OrthoTime;
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RealD eresid, betastp;
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SortEigen<Field> _sort;
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LinearFunction<Field> &_HermOp;
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LinearFunction<Field> &_HermOpTest;
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/////////////////////////
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// Constructor
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/////////////////////////
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BlockImplicitlyRestartedLanczos(
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LinearFunction<Field> & HermOp,
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LinearFunction<Field> & HermOpTest,
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int _Nstop, // sought vecs
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int _Nk, // sought vecs
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int _Nm, // spare vecs
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RealD _eresid, // resid in lmdue deficit
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RealD _betastp, // if beta(k) < betastp: converged
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int _Niter, // Max iterations
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int _Nminres, int _orth_period = 1) :
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_HermOp(HermOp),
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_HermOpTest(HermOpTest),
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Nstop(_Nstop),
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Nk(_Nk),
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Nm(_Nm),
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eresid(_eresid),
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betastp(_betastp),
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Niter(_Niter),
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Nminres(_Nminres),
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orth_period(_orth_period)
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{
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Np = Nm-Nk; assert(Np>0);
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};
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BlockImplicitlyRestartedLanczos(
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LinearFunction<Field> & HermOp,
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LinearFunction<Field> & HermOpTest,
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int _Nk, // sought vecs
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int _Nm, // spare vecs
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RealD _eresid, // resid in lmdue deficit
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RealD _betastp, // if beta(k) < betastp: converged
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int _Niter, // Max iterations
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int _Nminres,
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int _orth_period = 1) :
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_HermOp(HermOp),
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_HermOpTest(HermOpTest),
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Nstop(_Nk),
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Nk(_Nk),
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Nm(_Nm),
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eresid(_eresid),
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betastp(_betastp),
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Niter(_Niter),
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Nminres(_Nminres),
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orth_period(_orth_period)
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{
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Np = Nm-Nk; assert(Np>0);
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};
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/* Saad PP. 195
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1. Choose an initial vector v1 of 2-norm unity. Set β1 ≡ 0, v0 ≡ 0
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2. For k = 1,2,...,m Do:
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3. wk:=Avk−βkv_{k−1}
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4. αk:=(wk,vk) //
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5. wk:=wk−αkvk // wk orthog vk
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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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8. EndDo
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*/
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void step(std::vector<RealD>& lmd,
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std::vector<RealD>& lme,
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BasisFieldVector<Field>& evec,
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Field& w,int Nm,int k)
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{
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assert( k< Nm );
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GridStopWatch gsw_op,gsw_o;
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Field& evec_k = evec[k];
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gsw_op.Start();
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_HermOp(evec_k,w);
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gsw_op.Stop();
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if(k>0){
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w -= lme[k-1] * evec[k-1];
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}
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ComplexD zalph = innerProduct(evec_k,w); // 4. αk:=(wk,vk)
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RealD alph = real(zalph);
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w = w - alph * evec_k;// 5. wk:=wk−αkvk
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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<<GridLogMessage << "alpha[" << k << "] = " << zalph << " beta[" << k << "] = "<<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<<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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gsw_o.Start();
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if (k>0 && k % orth_period == 0) {
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orthogonalize(w,evec,k); // orthonormalise
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}
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gsw_o.Stop();
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if(k < Nm-1) {
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evec[k+1] = w;
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}
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std::cout << GridLogMessage << "Timing: operator=" << gsw_op.Elapsed() <<
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" orth=" << gsw_o.Elapsed() << std::endl;
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}
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void qr_decomp(std::vector<RealD>& lmd,
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std::vector<RealD>& lme,
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int Nk,
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int Nm,
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std::vector<RealD>& Qt,
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RealD Dsh,
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int kmin,
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int kmax)
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{
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int k = kmin-1;
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RealD x;
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RealD Fden = 1.0/hypot(lmd[k]-Dsh,lme[k]);
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RealD c = ( lmd[k] -Dsh) *Fden;
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RealD s = -lme[k] *Fden;
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RealD tmpa1 = lmd[k];
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RealD tmpa2 = lmd[k+1];
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RealD tmpb = lme[k];
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lmd[k] = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
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lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
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lme[k] = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
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x =-s*lme[k+1];
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lme[k+1] = c*lme[k+1];
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for(int i=0; i<Nk; ++i){
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RealD Qtmp1 = Qt[i+Nm*k ];
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RealD Qtmp2 = Qt[i+Nm*(k+1)];
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Qt[i+Nm*k ] = c*Qtmp1 - s*Qtmp2;
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Qt[i+Nm*(k+1)] = s*Qtmp1 + c*Qtmp2;
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}
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// Givens transformations
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for(int k = kmin; k < kmax-1; ++k){
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RealD Fden = 1.0/hypot(x,lme[k-1]);
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RealD c = lme[k-1]*Fden;
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RealD s = - x*Fden;
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RealD tmpa1 = lmd[k];
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RealD tmpa2 = lmd[k+1];
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RealD tmpb = lme[k];
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lmd[k] = c*c*tmpa1 +s*s*tmpa2 -2.0*c*s*tmpb;
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lmd[k+1] = s*s*tmpa1 +c*c*tmpa2 +2.0*c*s*tmpb;
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lme[k] = c*s*(tmpa1-tmpa2) +(c*c-s*s)*tmpb;
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lme[k-1] = c*lme[k-1] -s*x;
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if(k != kmax-2){
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x = -s*lme[k+1];
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lme[k+1] = c*lme[k+1];
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}
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for(int i=0; i<Nk; ++i){
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RealD Qtmp1 = Qt[i+Nm*k ];
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RealD Qtmp2 = Qt[i+Nm*(k+1)];
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Qt[i+Nm*k ] = c*Qtmp1 -s*Qtmp2;
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Qt[i+Nm*(k+1)] = s*Qtmp1 +c*Qtmp2;
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}
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}
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}
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#ifdef USE_LAPACK_IRL
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#define LAPACK_INT int
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//long long
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void diagonalize_lapack(std::vector<RealD>& lmd,
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std::vector<RealD>& lme,
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int N1,
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int N2,
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std::vector<RealD>& Qt,
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GridBase *grid){
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std::cout << GridLogMessage << "diagonalize_lapack start\n";
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GridStopWatch gsw;
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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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LAPACK_INT NN = N1;
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std::vector<double> evals_tmp(NN);
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std::vector<double> evec_tmp(NN*NN);
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memset(&evec_tmp[0],0,sizeof(double)*NN*NN);
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// double AA[NN][NN];
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std::vector<double> DD(NN);
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std::vector<double> EE(NN);
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for (int i = 0; i< NN; i++)
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for (int j = i - 1; j <= i + 1; j++)
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if ( j < NN && j >= 0 ) {
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if (i==j) DD[i] = lmd[i];
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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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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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std::vector<LAPACK_INT> iwork(liwork);
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std::vector<double> work(lwork);
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std::vector<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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std::vector<int> ifail(NN);
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LAPACK_INT 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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int total = grid->_Nprocessors;
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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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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],0,sizeof(double)*NN);
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if ( il <= NN){
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std::cout << GridLogMessage << "dstegr started" << std::endl;
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gsw.Start();
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dstegr(&jobz, &range, &NN,
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(double*)&DD[0], (double*)&EE[0],
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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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&evals_found, &evals_tmp[0], (double*)&evec_tmp[0], &NN,
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&isuppz[0],
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&work[0], &lwork, &iwork[0], &liwork,
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&info);
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gsw.Stop();
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std::cout << GridLogMessage << "dstegr completed in " << gsw.Elapsed() << std::endl;
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for (int i = iu-1; i>= il-1; i--){
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evals_tmp[i] = evals_tmp[i - (il-1)];
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if (il>1) evals_tmp[i-(il-1)]=0.;
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for (int j = 0; j< NN; j++){
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evec_tmp[i*NN + j] = evec_tmp[(i - (il-1)) * NN + j];
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if (il>1) evec_tmp[(i-(il-1)) * NN + j]=0.;
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}
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}
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}
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{
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// QMP_sum_double_array(evals_tmp,NN);
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// QMP_sum_double_array((double *)evec_tmp,NN*NN);
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grid->GlobalSumVector(&evals_tmp[0],NN);
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grid->GlobalSumVector(&evec_tmp[0],NN*NN);
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}
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}
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// cheating a bit. It is better to sort instead of just reversing it, but the document of the routine says evals are sorted in increasing order. qr gives evals in decreasing order.
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for(int i=0;i<NN;i++){
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for(int j=0;j<NN;j++)
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Qt[(NN-1-i)*N2+j]=evec_tmp[i*NN + j];
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lmd [NN-1-i]=evals_tmp[i];
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}
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std::cout << GridLogMessage << "diagonalize_lapack complete\n";
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}
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#undef LAPACK_INT
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#endif
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void diagonalize(std::vector<RealD>& lmd,
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std::vector<RealD>& lme,
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int N2,
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int N1,
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std::vector<RealD>& Qt,
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||||
GridBase *grid)
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{
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#ifdef USE_LAPACK_IRL
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const int check_lapack=0; // just use lapack if 0, check against lapack if 1
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if(!check_lapack)
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return diagonalize_lapack(lmd,lme,N2,N1,Qt,grid);
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||||
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std::vector <RealD> lmd2(N1);
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||||
std::vector <RealD> lme2(N1);
|
||||
std::vector<RealD> Qt2(N1*N1);
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||||
for(int k=0; k<N1; ++k){
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lmd2[k] = lmd[k];
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||||
lme2[k] = lme[k];
|
||||
}
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for(int k=0; k<N1*N1; ++k)
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Qt2[k] = Qt[k];
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||||
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// diagonalize_lapack(lmd2,lme2,Nm2,Nm,Qt,grid);
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#endif
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||||
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||||
int Niter = 10000*N1;
|
||||
int kmin = 1;
|
||||
int kmax = N2;
|
||||
// (this should be more sophisticated)
|
||||
|
||||
for(int iter=0; ; ++iter){
|
||||
if ( (iter+1)%(100*N1)==0)
|
||||
std::cout<<GridLogMessage << "[QL method] Not converged - iteration "<<iter+1<<"\n";
|
||||
|
||||
// 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,N2,N1,Qt,Dsh,kmin,kmax);
|
||||
|
||||
// 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;
|
||||
#ifdef USE_LAPACK_IRL
|
||||
if(check_lapack){
|
||||
const double SMALL=1e-8;
|
||||
diagonalize_lapack(lmd2,lme2,N2,N1,Qt2,grid);
|
||||
std::vector <RealD> lmd3(N2);
|
||||
for(int k=0; k<N2; ++k) lmd3[k]=lmd[k];
|
||||
_sort.push(lmd3,N2);
|
||||
_sort.push(lmd2,N2);
|
||||
for(int k=0; k<N2; ++k){
|
||||
if (fabs(lmd2[k] - lmd3[k]) >SMALL) std::cout<<GridLogMessage <<"lmd(qr) lmd(lapack) "<< k << ": " << lmd2[k] <<" "<< lmd3[k] <<std::endl;
|
||||
// if (fabs(lme2[k] - lme[k]) >SMALL) std::cout<<GridLogMessage <<"lme(qr)-lme(lapack) "<< k << ": " << lme2[k] - lme[k] <<std::endl;
|
||||
}
|
||||
for(int k=0; k<N1*N1; ++k){
|
||||
// if (fabs(Qt2[k] - Qt[k]) >SMALL) std::cout<<GridLogMessage <<"Qt(qr)-Qt(lapack) "<< k << ": " << Qt2[k] - Qt[k] <<std::endl;
|
||||
}
|
||||
}
|
||||
#endif
|
||||
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<<GridLogMessage << "[QL method] Error - Too many iteration: "<<Niter<<"\n";
|
||||
abort();
|
||||
}
|
||||
|
||||
#if 1
|
||||
template<typename T>
|
||||
static RealD normalise(T& v)
|
||||
{
|
||||
RealD nn = norm2(v);
|
||||
nn = sqrt(nn);
|
||||
v = v * (1.0/nn);
|
||||
return nn;
|
||||
}
|
||||
|
||||
void orthogonalize(Field& w,
|
||||
BasisFieldVector<Field>& evec,
|
||||
int k)
|
||||
{
|
||||
double t0=-usecond()/1e6;
|
||||
|
||||
evec.orthogonalize(w,k);
|
||||
|
||||
normalise(w);
|
||||
t0+=usecond()/1e6;
|
||||
OrthoTime +=t0;
|
||||
}
|
||||
|
||||
void setUnit_Qt(int Nm, std::vector<RealD> &Qt) {
|
||||
for(int i=0; i<Qt.size(); ++i) Qt[i] = 0.0;
|
||||
for(int k=0; k<Nm; ++k) Qt[k + k*Nm] = 1.0;
|
||||
}
|
||||
|
||||
/* 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 +fKe†K † Extend to an M = K + P step factorization AVM = VMHM + fMeM
|
||||
until convergence
|
||||
*/
|
||||
|
||||
void calc(std::vector<RealD>& eval,
|
||||
BasisFieldVector<Field>& evec,
|
||||
const Field& src,
|
||||
int& Nconv,
|
||||
bool reverse,
|
||||
int SkipTest)
|
||||
{
|
||||
|
||||
GridBase *grid = evec._v[0]._grid;//evec.get(0 + evec_offset)._grid;
|
||||
assert(grid == src._grid);
|
||||
|
||||
std::cout<<GridLogMessage << " -- Nk = " << Nk << " Np = "<< Np << std::endl;
|
||||
std::cout<<GridLogMessage << " -- Nm = " << Nm << std::endl;
|
||||
std::cout<<GridLogMessage << " -- size of eval = " << eval.size() << std::endl;
|
||||
std::cout<<GridLogMessage << " -- size of evec = " << evec.size() << std::endl;
|
||||
|
||||
assert(Nm <= evec.size() && Nm <= eval.size());
|
||||
|
||||
// quickly get an idea of the largest eigenvalue to more properly normalize the residuum
|
||||
RealD evalMaxApprox = 0.0;
|
||||
{
|
||||
auto src_n = src;
|
||||
auto tmp = src;
|
||||
const int _MAX_ITER_IRL_MEVAPP_ = 50;
|
||||
for (int i=0;i<_MAX_ITER_IRL_MEVAPP_;i++) {
|
||||
_HermOpTest(src_n,tmp);
|
||||
RealD vnum = real(innerProduct(src_n,tmp)); // HermOp.
|
||||
RealD vden = norm2(src_n);
|
||||
RealD na = vnum/vden;
|
||||
if (fabs(evalMaxApprox/na - 1.0) < 0.05)
|
||||
i=_MAX_ITER_IRL_MEVAPP_;
|
||||
evalMaxApprox = na;
|
||||
std::cout << GridLogMessage << " Approximation of largest eigenvalue: " << evalMaxApprox << std::endl;
|
||||
src_n = tmp;
|
||||
}
|
||||
}
|
||||
|
||||
std::vector<RealD> lme(Nm);
|
||||
std::vector<RealD> lme2(Nm);
|
||||
std::vector<RealD> eval2(Nm);
|
||||
std::vector<RealD> eval2_copy(Nm);
|
||||
std::vector<RealD> Qt(Nm*Nm);
|
||||
|
||||
|
||||
Field f(grid);
|
||||
Field v(grid);
|
||||
|
||||
int k1 = 1;
|
||||
int k2 = Nk;
|
||||
|
||||
Nconv = 0;
|
||||
|
||||
RealD beta_k;
|
||||
|
||||
// Set initial vector
|
||||
evec[0] = src;
|
||||
normalise(evec[0]);
|
||||
std:: cout<<GridLogMessage <<"norm2(evec[0])= " << norm2(evec[0])<<std::endl;
|
||||
|
||||
// Initial Nk steps
|
||||
OrthoTime=0.;
|
||||
double t0=usecond()/1e6;
|
||||
for(int k=0; k<Nk; ++k) step(eval,lme,evec,f,Nm,k);
|
||||
double t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::Initial steps: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
std::cout<<GridLogMessage <<"IRL::Initial steps:OrthoTime "<<OrthoTime<< "seconds"<<std::endl;
|
||||
t1=usecond()/1e6;
|
||||
|
||||
// Restarting loop begins
|
||||
for(int iter = 0; iter<Niter; ++iter){
|
||||
|
||||
std::cout<<GridLogMessage<<"\n Restart iteration = "<< iter << std::endl;
|
||||
|
||||
//
|
||||
// Rudy does a sort first which looks very different. Getting fed up with sorting out the algo defs.
|
||||
// We loop over
|
||||
//
|
||||
OrthoTime=0.;
|
||||
for(int k=Nk; k<Nm; ++k) step(eval,lme,evec,f,Nm,k);
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL:: "<<Np <<" steps: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
std::cout<<GridLogMessage <<"IRL::Initial steps:OrthoTime "<<OrthoTime<< "seconds"<<std::endl;
|
||||
f *= lme[Nm-1];
|
||||
|
||||
t1=usecond()/1e6;
|
||||
|
||||
|
||||
// getting eigenvalues
|
||||
for(int k=0; k<Nm; ++k){
|
||||
eval2[k] = eval[k+k1-1];
|
||||
lme2[k] = lme[k+k1-1];
|
||||
}
|
||||
setUnit_Qt(Nm,Qt);
|
||||
diagonalize(eval2,lme2,Nm,Nm,Qt,grid);
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL:: diagonalize: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
|
||||
// sorting
|
||||
eval2_copy = eval2;
|
||||
|
||||
_sort.push(eval2,Nm);
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL:: eval sorting: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
|
||||
// Implicitly shifted QR transformations
|
||||
setUnit_Qt(Nm,Qt);
|
||||
for(int ip=0; ip<k2; ++ip){
|
||||
std::cout<<GridLogMessage << "eval "<< ip << " "<< eval2[ip] << std::endl;
|
||||
}
|
||||
|
||||
for(int ip=k2; ip<Nm; ++ip){
|
||||
std::cout<<GridLogMessage << "qr_decomp "<< ip << " "<< eval2[ip] << std::endl;
|
||||
qr_decomp(eval,lme,Nm,Nm,Qt,eval2[ip],k1,Nm);
|
||||
|
||||
}
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::qr_decomp: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
assert(k2<Nm);
|
||||
|
||||
|
||||
assert(k2<Nm);
|
||||
assert(k1>0);
|
||||
evec.rotate(Qt,k1-1,k2+1,0,Nm,Nm);
|
||||
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::QR rotation: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
fflush(stdout);
|
||||
|
||||
// Compressed vector f and beta(k2)
|
||||
f *= Qt[Nm-1+Nm*(k2-1)];
|
||||
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];
|
||||
|
||||
std::cout<<GridLogMessage << "eval2[" << k << "] = " << eval2[k] << std::endl;
|
||||
}
|
||||
setUnit_Qt(Nm,Qt);
|
||||
diagonalize(eval2,lme2,Nk,Nm,Qt,grid);
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::diagonalize: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
|
||||
|
||||
Nconv = 0;
|
||||
|
||||
if (iter >= Nminres) {
|
||||
std::cout << GridLogMessage << "Rotation to test convergence " << std::endl;
|
||||
|
||||
Field ev0_orig(grid);
|
||||
ev0_orig = evec[0];
|
||||
|
||||
evec.rotate(Qt,0,Nk,0,Nk,Nm);
|
||||
|
||||
{
|
||||
std::cout << GridLogMessage << "Test convergence" << std::endl;
|
||||
Field B(grid);
|
||||
|
||||
for(int j = 0; j<Nk; j+=SkipTest){
|
||||
B=evec[j];
|
||||
//std::cout << "Checkerboard: " << evec[j].checkerboard << std::endl;
|
||||
B.checkerboard = evec[0].checkerboard;
|
||||
|
||||
_HermOpTest(B,v);
|
||||
|
||||
RealD vnum = real(innerProduct(B,v)); // HermOp.
|
||||
RealD vden = norm2(B);
|
||||
RealD vv0 = norm2(v);
|
||||
eval2[j] = vnum/vden;
|
||||
v -= eval2[j]*B;
|
||||
RealD vv = norm2(v) / ::pow(evalMaxApprox,2.0);
|
||||
std::cout.precision(13);
|
||||
std::cout<<GridLogMessage << "[" << std::setw(3)<< std::setiosflags(std::ios_base::right) <<j<<"] "
|
||||
<<"eval = "<<std::setw(25)<< std::setiosflags(std::ios_base::left)<< eval2[j] << " (" << eval2_copy[j] << ")"
|
||||
<<" |H B[i] - eval[i]B[i]|^2 / evalMaxApprox^2 " << std::setw(25)<< std::setiosflags(std::ios_base::right)<< vv
|
||||
<<" "<< vnum/(sqrt(vden)*sqrt(vv0))
|
||||
<< " norm(B["<<j<<"])="<< vden <<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) && (j == Nconv) ){
|
||||
Nconv+=SkipTest;
|
||||
}
|
||||
}
|
||||
|
||||
// test if we converged, if so, terminate
|
||||
t1=usecond()/1e6;
|
||||
std::cout<<GridLogMessage <<"IRL::convergence testing: "<<t1-t0<< "seconds"<<std::endl; t0=t1;
|
||||
|
||||
std::cout<<GridLogMessage<<" #modes converged: "<<Nconv<<std::endl;
|
||||
|
||||
if( Nconv>=Nstop || beta_k < betastp){
|
||||
goto converged;
|
||||
}
|
||||
|
||||
std::cout << GridLogMessage << "Rotate back" << std::endl;
|
||||
//B[j] +=Qt[k+_Nm*j] * _v[k]._odata[ss];
|
||||
{
|
||||
Eigen::MatrixXd qm = Eigen::MatrixXd::Zero(Nk,Nk);
|
||||
for (int k=0;k<Nk;k++)
|
||||
for (int j=0;j<Nk;j++)
|
||||
qm(j,k) = Qt[k+Nm*j];
|
||||
GridStopWatch timeInv;
|
||||
timeInv.Start();
|
||||
Eigen::MatrixXd qmI = qm.inverse();
|
||||
timeInv.Stop();
|
||||
std::vector<RealD> QtI(Nm*Nm);
|
||||
for (int k=0;k<Nk;k++)
|
||||
for (int j=0;j<Nk;j++)
|
||||
QtI[k+Nm*j] = qmI(j,k);
|
||||
|
||||
RealD res_check_rotate_inverse = (qm*qmI - Eigen::MatrixXd::Identity(Nk,Nk)).norm(); // sqrt( |X|^2 )
|
||||
assert(res_check_rotate_inverse < 1e-7);
|
||||
evec.rotate(QtI,0,Nk,0,Nk,Nm);
|
||||
|
||||
axpy(ev0_orig,-1.0,evec[0],ev0_orig);
|
||||
std::cout << GridLogMessage << "Rotation done (in " << timeInv.Elapsed() << " = " << timeInv.useconds() << " us" <<
|
||||
", error = " << res_check_rotate_inverse <<
|
||||
"); | evec[0] - evec[0]_orig | = " << ::sqrt(norm2(ev0_orig)) << std::endl;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
std::cout << GridLogMessage << "iter < Nminres: do not yet test for convergence\n";
|
||||
} // end of iter loop
|
||||
}
|
||||
|
||||
std::cout<<GridLogMessage<<"\n NOT converged.\n";
|
||||
abort();
|
||||
|
||||
converged:
|
||||
|
||||
if (SkipTest == 1) {
|
||||
eval = eval2;
|
||||
} else {
|
||||
|
||||
// test quickly
|
||||
for (int j=0;j<Nstop;j+=SkipTest) {
|
||||
std::cout<<GridLogMessage << "Eigenvalue[" << j << "] = " << eval2[j] << " (" << eval2_copy[j] << ")" << std::endl;
|
||||
}
|
||||
|
||||
eval2_copy.resize(eval2.size());
|
||||
eval = eval2_copy;
|
||||
}
|
||||
|
||||
evec.sortInPlace(eval,reverse);
|
||||
|
||||
{
|
||||
|
||||
// test
|
||||
for (int j=0;j<Nstop;j++) {
|
||||
std::cout<<GridLogMessage << " |e[" << j << "]|^2 = " << norm2(evec[j]) << std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
//_sort.push(eval,evec,Nconv);
|
||||
//evec.sort(eval,Nconv);
|
||||
|
||||
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";
|
||||
}
|
||||
#endif
|
||||
|
||||
};
|
||||
|
||||
}
|
||||
#endif
|
||||
|
||||
@@ -0,0 +1,143 @@
|
||||
namespace Grid {
|
||||
|
||||
/*
|
||||
BlockProjector
|
||||
|
||||
If _HP_BLOCK_PROJECTORS_ is defined, we assume that _evec is a basis that is not
|
||||
fully orthonormalized (to the precision of the coarse field) and we allow for higher-precision
|
||||
coarse field than basis field.
|
||||
|
||||
*/
|
||||
//#define _HP_BLOCK_PROJECTORS_
|
||||
|
||||
template<typename Field>
|
||||
class BlockProjector {
|
||||
public:
|
||||
|
||||
BasisFieldVector<Field>& _evec;
|
||||
BlockedGrid<Field>& _bgrid;
|
||||
|
||||
BlockProjector(BasisFieldVector<Field>& evec, BlockedGrid<Field>& bgrid) : _evec(evec), _bgrid(bgrid) {
|
||||
}
|
||||
|
||||
void createOrthonormalBasis(RealD thres = 0.0) {
|
||||
|
||||
GridStopWatch sw;
|
||||
sw.Start();
|
||||
|
||||
int cnt = 0;
|
||||
|
||||
#pragma omp parallel shared(cnt)
|
||||
{
|
||||
int lcnt = 0;
|
||||
|
||||
#pragma omp for
|
||||
for (int b=0;b<_bgrid._o_blocks;b++) {
|
||||
|
||||
for (int i=0;i<_evec._Nm;i++) {
|
||||
|
||||
auto nrm0 = _bgrid.block_sp(b,_evec._v[i],_evec._v[i]);
|
||||
|
||||
// |i> -= <j|i> |j>
|
||||
for (int j=0;j<i;j++) {
|
||||
_bgrid.block_caxpy(b,_evec._v[i],-_bgrid.block_sp(b,_evec._v[j],_evec._v[i]),_evec._v[j],_evec._v[i]);
|
||||
}
|
||||
|
||||
auto nrm = _bgrid.block_sp(b,_evec._v[i],_evec._v[i]);
|
||||
|
||||
auto eps = nrm/nrm0;
|
||||
if (Reduce(eps).real() < thres) {
|
||||
lcnt++;
|
||||
}
|
||||
|
||||
// TODO: if norm is too small, remove this eigenvector/mark as not needed; in practice: set it to zero norm here and return a mask
|
||||
// that is then used later to decide not to write certain eigenvectors to disk (add a norm calculation before subtraction step and look at nrm/nrm0 < eps to decide)
|
||||
_bgrid.block_cscale(b,1.0 / sqrt(nrm),_evec._v[i]);
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
#pragma omp critical
|
||||
{
|
||||
cnt += lcnt;
|
||||
}
|
||||
}
|
||||
sw.Stop();
|
||||
std::cout << GridLogMessage << "Gram-Schmidt to create blocked basis took " << sw.Elapsed() << " (" << ((RealD)cnt / (RealD)_bgrid._o_blocks / (RealD)_evec._Nm)
|
||||
<< " below threshold)" << std::endl;
|
||||
|
||||
}
|
||||
|
||||
template<typename CoarseField>
|
||||
void coarseToFine(const CoarseField& in, Field& out) {
|
||||
|
||||
out = zero;
|
||||
out.checkerboard = _evec._v[0].checkerboard;
|
||||
|
||||
int Nbasis = sizeof(in._odata[0]._internal._internal) / sizeof(in._odata[0]._internal._internal[0]);
|
||||
assert(Nbasis == _evec._Nm);
|
||||
|
||||
#pragma omp parallel for
|
||||
for (int b=0;b<_bgrid._o_blocks;b++) {
|
||||
for (int j=0;j<_evec._Nm;j++) {
|
||||
_bgrid.block_caxpy(b,out,in._odata[b]._internal._internal[j],_evec._v[j],out);
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
template<typename CoarseField>
|
||||
void fineToCoarse(const Field& in, CoarseField& out) {
|
||||
|
||||
out = zero;
|
||||
|
||||
int Nbasis = sizeof(out._odata[0]._internal._internal) / sizeof(out._odata[0]._internal._internal[0]);
|
||||
assert(Nbasis == _evec._Nm);
|
||||
|
||||
|
||||
Field tmp(_bgrid._grid);
|
||||
tmp = in;
|
||||
|
||||
#pragma omp parallel for
|
||||
for (int b=0;b<_bgrid._o_blocks;b++) {
|
||||
for (int j=0;j<_evec._Nm;j++) {
|
||||
// |rhs> -= <j|rhs> |j>
|
||||
auto c = _bgrid.block_sp(b,_evec._v[j],tmp);
|
||||
_bgrid.block_caxpy(b,tmp,-c,_evec._v[j],tmp); // may make this more numerically stable
|
||||
out._odata[b]._internal._internal[j] = c;
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
template<typename CoarseField>
|
||||
void deflateFine(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
|
||||
result = zero;
|
||||
for (int i=0;i<N;i++) {
|
||||
Field tmp(result._grid);
|
||||
coarseToFine(_coef._v[i],tmp);
|
||||
axpy(result,TensorRemove(innerProduct(tmp,src_orig)) / eval[i],tmp,result);
|
||||
}
|
||||
}
|
||||
|
||||
template<typename CoarseField>
|
||||
void deflateCoarse(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
|
||||
CoarseField src_coarse(_coef._v[0]._grid);
|
||||
CoarseField result_coarse = src_coarse;
|
||||
result_coarse = zero;
|
||||
fineToCoarse(src_orig,src_coarse);
|
||||
for (int i=0;i<N;i++) {
|
||||
axpy(result_coarse,TensorRemove(innerProduct(_coef._v[i],src_coarse)) / eval[i],_coef._v[i],result_coarse);
|
||||
}
|
||||
coarseToFine(result_coarse,result);
|
||||
}
|
||||
|
||||
template<typename CoarseField>
|
||||
void deflate(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
|
||||
// Deflation on coarse Grid is much faster, so use it by default. Deflation on fine Grid is kept for legacy reasons for now.
|
||||
deflateCoarse(_coef,eval,N,src_orig,result);
|
||||
}
|
||||
|
||||
};
|
||||
}
|
||||
@@ -0,0 +1,401 @@
|
||||
namespace Grid {
|
||||
|
||||
template<typename Field>
|
||||
class BlockedGrid {
|
||||
public:
|
||||
GridBase* _grid;
|
||||
typedef typename Field::scalar_type Coeff_t;
|
||||
typedef typename Field::vector_type vCoeff_t;
|
||||
|
||||
std::vector<int> _bs; // block size
|
||||
std::vector<int> _nb; // number of blocks
|
||||
std::vector<int> _l; // local dimensions irrespective of cb
|
||||
std::vector<int> _l_cb; // local dimensions of checkerboarded vector
|
||||
std::vector<int> _l_cb_o; // local dimensions of inner checkerboarded vector
|
||||
std::vector<int> _bs_cb; // block size in checkerboarded vector
|
||||
std::vector<int> _nb_o; // number of blocks of simd o-sites
|
||||
|
||||
int _nd, _blocks, _cf_size, _cf_block_size, _cf_o_block_size, _o_blocks, _block_sites;
|
||||
|
||||
BlockedGrid(GridBase* grid, const std::vector<int>& block_size) :
|
||||
_grid(grid), _bs(block_size), _nd((int)_bs.size()),
|
||||
_nb(block_size), _l(block_size), _l_cb(block_size), _nb_o(block_size),
|
||||
_l_cb_o(block_size), _bs_cb(block_size) {
|
||||
|
||||
_blocks = 1;
|
||||
_o_blocks = 1;
|
||||
_l = grid->FullDimensions();
|
||||
_l_cb = grid->LocalDimensions();
|
||||
_l_cb_o = grid->_rdimensions;
|
||||
|
||||
_cf_size = 1;
|
||||
_block_sites = 1;
|
||||
for (int i=0;i<_nd;i++) {
|
||||
_l[i] /= grid->_processors[i];
|
||||
|
||||
assert(!(_l[i] % _bs[i])); // lattice must accommodate choice of blocksize
|
||||
|
||||
int r = _l[i] / _l_cb[i];
|
||||
assert(!(_bs[i] % r)); // checkerboarding must accommodate choice of blocksize
|
||||
_bs_cb[i] = _bs[i] / r;
|
||||
_block_sites *= _bs_cb[i];
|
||||
_nb[i] = _l[i] / _bs[i];
|
||||
_nb_o[i] = _nb[i] / _grid->_simd_layout[i];
|
||||
if (_nb[i] % _grid->_simd_layout[i]) { // simd must accommodate choice of blocksize
|
||||
std::cout << GridLogMessage << "Problem: _nb[" << i << "] = " << _nb[i] << " _grid->_simd_layout[" << i << "] = " << _grid->_simd_layout[i] << std::endl;
|
||||
assert(0);
|
||||
}
|
||||
_blocks *= _nb[i];
|
||||
_o_blocks *= _nb_o[i];
|
||||
_cf_size *= _l[i];
|
||||
}
|
||||
|
||||
_cf_size *= 12 / 2;
|
||||
_cf_block_size = _cf_size / _blocks;
|
||||
_cf_o_block_size = _cf_size / _o_blocks;
|
||||
|
||||
std::cout << GridLogMessage << "BlockedGrid:" << std::endl;
|
||||
std::cout << GridLogMessage << " _l = " << _l << std::endl;
|
||||
std::cout << GridLogMessage << " _l_cb = " << _l_cb << std::endl;
|
||||
std::cout << GridLogMessage << " _l_cb_o = " << _l_cb_o << std::endl;
|
||||
std::cout << GridLogMessage << " _bs = " << _bs << std::endl;
|
||||
std::cout << GridLogMessage << " _bs_cb = " << _bs_cb << std::endl;
|
||||
|
||||
std::cout << GridLogMessage << " _nb = " << _nb << std::endl;
|
||||
std::cout << GridLogMessage << " _nb_o = " << _nb_o << std::endl;
|
||||
std::cout << GridLogMessage << " _blocks = " << _blocks << std::endl;
|
||||
std::cout << GridLogMessage << " _o_blocks = " << _o_blocks << std::endl;
|
||||
std::cout << GridLogMessage << " sizeof(vCoeff_t) = " << sizeof(vCoeff_t) << std::endl;
|
||||
std::cout << GridLogMessage << " _cf_size = " << _cf_size << std::endl;
|
||||
std::cout << GridLogMessage << " _cf_block_size = " << _cf_block_size << std::endl;
|
||||
std::cout << GridLogMessage << " _block_sites = " << _block_sites << std::endl;
|
||||
std::cout << GridLogMessage << " _grid->oSites() = " << _grid->oSites() << std::endl;
|
||||
|
||||
// _grid->Barrier();
|
||||
//abort();
|
||||
}
|
||||
|
||||
void block_to_coor(int b, std::vector<int>& x0) {
|
||||
|
||||
std::vector<int> bcoor;
|
||||
bcoor.resize(_nd);
|
||||
x0.resize(_nd);
|
||||
assert(b < _o_blocks);
|
||||
Lexicographic::CoorFromIndex(bcoor,b,_nb_o);
|
||||
int i;
|
||||
|
||||
for (i=0;i<_nd;i++) {
|
||||
x0[i] = bcoor[i]*_bs_cb[i];
|
||||
}
|
||||
|
||||
//std::cout << GridLogMessage << "Map block b -> " << x0 << std::endl;
|
||||
|
||||
}
|
||||
|
||||
void block_site_to_o_coor(const std::vector<int>& x0, std::vector<int>& coor, int i) {
|
||||
Lexicographic::CoorFromIndex(coor,i,_bs_cb);
|
||||
for (int j=0;j<_nd;j++)
|
||||
coor[j] += x0[j];
|
||||
}
|
||||
|
||||
int block_site_to_o_site(const std::vector<int>& x0, int i) {
|
||||
std::vector<int> coor; coor.resize(_nd);
|
||||
block_site_to_o_coor(x0,coor,i);
|
||||
Lexicographic::IndexFromCoor(coor,i,_l_cb_o);
|
||||
return i;
|
||||
}
|
||||
|
||||
vCoeff_t block_sp(int b, const Field& x, const Field& y) {
|
||||
|
||||
std::vector<int> x0;
|
||||
block_to_coor(b,x0);
|
||||
|
||||
vCoeff_t ret = 0.0;
|
||||
for (int i=0;i<_block_sites;i++) { // only odd sites
|
||||
int ss = block_site_to_o_site(x0,i);
|
||||
ret += TensorRemove(innerProduct(x._odata[ss],y._odata[ss]));
|
||||
}
|
||||
|
||||
return ret;
|
||||
|
||||
}
|
||||
|
||||
vCoeff_t block_sp(int b, const Field& x, const std::vector< ComplexD >& y) {
|
||||
|
||||
std::vector<int> x0;
|
||||
block_to_coor(b,x0);
|
||||
|
||||
constexpr int nsimd = sizeof(vCoeff_t) / sizeof(Coeff_t);
|
||||
int lsize = _cf_o_block_size / _block_sites;
|
||||
|
||||
std::vector< ComplexD > ret(nsimd);
|
||||
for (int i=0;i<nsimd;i++)
|
||||
ret[i] = 0.0;
|
||||
|
||||
for (int i=0;i<_block_sites;i++) { // only odd sites
|
||||
int ss = block_site_to_o_site(x0,i);
|
||||
|
||||
int n = lsize / nsimd;
|
||||
for (int l=0;l<n;l++) {
|
||||
for (int j=0;j<nsimd;j++) {
|
||||
int t = lsize * i + l*nsimd + j;
|
||||
|
||||
ret[j] += conjugate(((Coeff_t*)&x._odata[ss]._internal)[l*nsimd + j]) * y[t];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
vCoeff_t vret;
|
||||
for (int i=0;i<nsimd;i++)
|
||||
((Coeff_t*)&vret)[i] = (Coeff_t)ret[i];
|
||||
|
||||
return vret;
|
||||
|
||||
}
|
||||
|
||||
template<class T>
|
||||
void vcaxpy(iScalar<T>& r,const vCoeff_t& a,const iScalar<T>& x,const iScalar<T>& y) {
|
||||
vcaxpy(r._internal,a,x._internal,y._internal);
|
||||
}
|
||||
|
||||
template<class T,int N>
|
||||
void vcaxpy(iVector<T,N>& r,const vCoeff_t& a,const iVector<T,N>& x,const iVector<T,N>& y) {
|
||||
for (int i=0;i<N;i++)
|
||||
vcaxpy(r._internal[i],a,x._internal[i],y._internal[i]);
|
||||
}
|
||||
|
||||
void vcaxpy(vCoeff_t& r,const vCoeff_t& a,const vCoeff_t& x,const vCoeff_t& y) {
|
||||
r = a*x + y;
|
||||
}
|
||||
|
||||
void block_caxpy(int b, Field& ret, const vCoeff_t& a, const Field& x, const Field& y) {
|
||||
|
||||
std::vector<int> x0;
|
||||
block_to_coor(b,x0);
|
||||
|
||||
for (int i=0;i<_block_sites;i++) { // only odd sites
|
||||
int ss = block_site_to_o_site(x0,i);
|
||||
vcaxpy(ret._odata[ss],a,x._odata[ss],y._odata[ss]);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
void block_caxpy(int b, std::vector< ComplexD >& ret, const vCoeff_t& a, const Field& x, const std::vector< ComplexD >& y) {
|
||||
std::vector<int> x0;
|
||||
block_to_coor(b,x0);
|
||||
|
||||
constexpr int nsimd = sizeof(vCoeff_t) / sizeof(Coeff_t);
|
||||
int lsize = _cf_o_block_size / _block_sites;
|
||||
|
||||
for (int i=0;i<_block_sites;i++) { // only odd sites
|
||||
int ss = block_site_to_o_site(x0,i);
|
||||
|
||||
int n = lsize / nsimd;
|
||||
for (int l=0;l<n;l++) {
|
||||
vCoeff_t r = a* ((vCoeff_t*)&x._odata[ss]._internal)[l];
|
||||
|
||||
for (int j=0;j<nsimd;j++) {
|
||||
int t = lsize * i + l*nsimd + j;
|
||||
ret[t] = y[t] + ((Coeff_t*)&r)[j];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
void block_set(int b, Field& ret, const std::vector< ComplexD >& x) {
|
||||
std::vector<int> x0;
|
||||
block_to_coor(b,x0);
|
||||
|
||||
int lsize = _cf_o_block_size / _block_sites;
|
||||
|
||||
for (int i=0;i<_block_sites;i++) { // only odd sites
|
||||
int ss = block_site_to_o_site(x0,i);
|
||||
|
||||
for (int l=0;l<lsize;l++)
|
||||
((Coeff_t*)&ret._odata[ss]._internal)[l] = (Coeff_t)x[lsize * i + l]; // convert precision
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
void block_get(int b, const Field& ret, std::vector< ComplexD >& x) {
|
||||
std::vector<int> x0;
|
||||
block_to_coor(b,x0);
|
||||
|
||||
int lsize = _cf_o_block_size / _block_sites;
|
||||
|
||||
for (int i=0;i<_block_sites;i++) { // only odd sites
|
||||
int ss = block_site_to_o_site(x0,i);
|
||||
|
||||
for (int l=0;l<lsize;l++)
|
||||
x[lsize * i + l] = (ComplexD)((Coeff_t*)&ret._odata[ss]._internal)[l];
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
template<class T>
|
||||
void vcscale(iScalar<T>& r,const vCoeff_t& a,const iScalar<T>& x) {
|
||||
vcscale(r._internal,a,x._internal);
|
||||
}
|
||||
|
||||
template<class T,int N>
|
||||
void vcscale(iVector<T,N>& r,const vCoeff_t& a,const iVector<T,N>& x) {
|
||||
for (int i=0;i<N;i++)
|
||||
vcscale(r._internal[i],a,x._internal[i]);
|
||||
}
|
||||
|
||||
void vcscale(vCoeff_t& r,const vCoeff_t& a,const vCoeff_t& x) {
|
||||
r = a*x;
|
||||
}
|
||||
|
||||
void block_cscale(int b, const vCoeff_t& a, Field& ret) {
|
||||
|
||||
std::vector<int> x0;
|
||||
block_to_coor(b,x0);
|
||||
|
||||
for (int i=0;i<_block_sites;i++) { // only odd sites
|
||||
int ss = block_site_to_o_site(x0,i);
|
||||
vcscale(ret._odata[ss],a,ret._odata[ss]);
|
||||
}
|
||||
}
|
||||
|
||||
void getCanonicalBlockOffset(int cb, std::vector<int>& x0) {
|
||||
const int ndim = 5;
|
||||
assert(_nb.size() == ndim);
|
||||
std::vector<int> _nbc = { _nb[1], _nb[2], _nb[3], _nb[4], _nb[0] };
|
||||
std::vector<int> _bsc = { _bs[1], _bs[2], _bs[3], _bs[4], _bs[0] };
|
||||
x0.resize(ndim);
|
||||
|
||||
assert(cb >= 0);
|
||||
assert(cb < _nbc[0]*_nbc[1]*_nbc[2]*_nbc[3]*_nbc[4]);
|
||||
|
||||
Lexicographic::CoorFromIndex(x0,cb,_nbc);
|
||||
int i;
|
||||
|
||||
for (i=0;i<ndim;i++) {
|
||||
x0[i] *= _bsc[i];
|
||||
}
|
||||
|
||||
//if (cb < 2)
|
||||
// std::cout << GridLogMessage << "Map: " << cb << " To: " << x0 << std::endl;
|
||||
}
|
||||
|
||||
void pokeBlockOfVectorCanonical(int cb,Field& v,const std::vector<float>& buf) {
|
||||
std::vector<int> _bsc = { _bs[1], _bs[2], _bs[3], _bs[4], _bs[0] };
|
||||
std::vector<int> ldim = v._grid->LocalDimensions();
|
||||
std::vector<int> cldim = { ldim[1], ldim[2], ldim[3], ldim[4], ldim[0] };
|
||||
const int _nbsc = _bs_cb[0]*_bs_cb[1]*_bs_cb[2]*_bs_cb[3]*_bs_cb[4];
|
||||
// take canonical block cb of v and put it in canonical ordering in buf
|
||||
std::vector<int> cx0;
|
||||
getCanonicalBlockOffset(cb,cx0);
|
||||
|
||||
#pragma omp parallel
|
||||
{
|
||||
std::vector<int> co0,cl0;
|
||||
co0=cx0; cl0=cx0;
|
||||
|
||||
#pragma omp for
|
||||
for (int i=0;i<_nbsc;i++) {
|
||||
Lexicographic::CoorFromIndex(co0,2*i,_bsc); // 2* for eo
|
||||
for (int j=0;j<(int)_bsc.size();j++)
|
||||
cl0[j] = cx0[j] + co0[j];
|
||||
|
||||
std::vector<int> l0 = { cl0[4], cl0[0], cl0[1], cl0[2], cl0[3] };
|
||||
int oi = v._grid->oIndex(l0);
|
||||
int ii = v._grid->iIndex(l0);
|
||||
int lti = i;
|
||||
|
||||
//if (cb < 2 && i<2)
|
||||
// std::cout << GridLogMessage << "Map: " << cb << ", " << i << " To: " << cl0 << ", " << cx0 << ", " << oi << ", " << ii << std::endl;
|
||||
|
||||
for (int s=0;s<4;s++)
|
||||
for (int c=0;c<3;c++) {
|
||||
Coeff_t& ld = ((Coeff_t*)&v._odata[oi]._internal._internal[s]._internal[c])[ii];
|
||||
int ti = 12*lti + 3*s + c;
|
||||
ld = Coeff_t(buf[2*ti+0], buf[2*ti+1]);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void peekBlockOfVectorCanonical(int cb,const Field& v,std::vector<float>& buf) {
|
||||
std::vector<int> _bsc = { _bs[1], _bs[2], _bs[3], _bs[4], _bs[0] };
|
||||
std::vector<int> ldim = v._grid->LocalDimensions();
|
||||
std::vector<int> cldim = { ldim[1], ldim[2], ldim[3], ldim[4], ldim[0] };
|
||||
const int _nbsc = _bs_cb[0]*_bs_cb[1]*_bs_cb[2]*_bs_cb[3]*_bs_cb[4];
|
||||
// take canonical block cb of v and put it in canonical ordering in buf
|
||||
std::vector<int> cx0;
|
||||
getCanonicalBlockOffset(cb,cx0);
|
||||
|
||||
buf.resize(_cf_block_size * 2);
|
||||
|
||||
#pragma omp parallel
|
||||
{
|
||||
std::vector<int> co0,cl0;
|
||||
co0=cx0; cl0=cx0;
|
||||
|
||||
#pragma omp for
|
||||
for (int i=0;i<_nbsc;i++) {
|
||||
Lexicographic::CoorFromIndex(co0,2*i,_bsc); // 2* for eo
|
||||
for (int j=0;j<(int)_bsc.size();j++)
|
||||
cl0[j] = cx0[j] + co0[j];
|
||||
|
||||
std::vector<int> l0 = { cl0[4], cl0[0], cl0[1], cl0[2], cl0[3] };
|
||||
int oi = v._grid->oIndex(l0);
|
||||
int ii = v._grid->iIndex(l0);
|
||||
int lti = i;
|
||||
|
||||
//if (cb < 2 && i<2)
|
||||
// std::cout << GridLogMessage << "Map: " << cb << ", " << i << " To: " << cl0 << ", " << cx0 << ", " << oi << ", " << ii << std::endl;
|
||||
|
||||
for (int s=0;s<4;s++)
|
||||
for (int c=0;c<3;c++) {
|
||||
Coeff_t& ld = ((Coeff_t*)&v._odata[oi]._internal._internal[s]._internal[c])[ii];
|
||||
int ti = 12*lti + 3*s + c;
|
||||
buf[2*ti+0] = ld.real();
|
||||
buf[2*ti+1] = ld.imag();
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
int globalToLocalCanonicalBlock(int slot,const std::vector<int>& src_nodes,int nb) {
|
||||
// processor coordinate
|
||||
int _nd = (int)src_nodes.size();
|
||||
std::vector<int> _src_nodes = src_nodes;
|
||||
std::vector<int> pco(_nd);
|
||||
Lexicographic::CoorFromIndex(pco,slot,_src_nodes);
|
||||
std::vector<int> cpco = { pco[1], pco[2], pco[3], pco[4], pco[0] };
|
||||
|
||||
// get local block
|
||||
std::vector<int> _nbc = { _nb[1], _nb[2], _nb[3], _nb[4], _nb[0] };
|
||||
assert(_nd == 5);
|
||||
std::vector<int> c_src_local_blocks(_nd);
|
||||
for (int i=0;i<_nd;i++) {
|
||||
assert(_grid->_fdimensions[i] % (src_nodes[i] * _bs[i]) == 0);
|
||||
c_src_local_blocks[(i+4) % 5] = _grid->_fdimensions[i] / src_nodes[i] / _bs[i];
|
||||
}
|
||||
std::vector<int> cbcoor(_nd); // coordinate of block in slot in canonical form
|
||||
Lexicographic::CoorFromIndex(cbcoor,nb,c_src_local_blocks);
|
||||
|
||||
// cpco, cbcoor
|
||||
std::vector<int> clbcoor(_nd);
|
||||
for (int i=0;i<_nd;i++) {
|
||||
int cgcoor = cpco[i] * c_src_local_blocks[i] + cbcoor[i]; // global block coordinate
|
||||
int pcoor = cgcoor / _nbc[i]; // processor coordinate in my Grid
|
||||
int tpcoor = _grid->_processor_coor[(i+1)%5];
|
||||
if (pcoor != tpcoor)
|
||||
return -1;
|
||||
clbcoor[i] = cgcoor - tpcoor * _nbc[i]; // canonical local block coordinate for canonical dimension i
|
||||
}
|
||||
|
||||
int lnb;
|
||||
Lexicographic::IndexFromCoor(clbcoor,lnb,_nbc);
|
||||
//std::cout << "Mapped slot = " << slot << " nb = " << nb << " to " << lnb << std::endl;
|
||||
return lnb;
|
||||
}
|
||||
|
||||
|
||||
};
|
||||
|
||||
}
|
||||
@@ -0,0 +1,163 @@
|
||||
namespace Grid {
|
||||
|
||||
template<class Field>
|
||||
class BasisFieldVector {
|
||||
public:
|
||||
int _Nm;
|
||||
|
||||
typedef typename Field::scalar_type Coeff_t;
|
||||
typedef typename Field::vector_type vCoeff_t;
|
||||
typedef typename Field::vector_object vobj;
|
||||
typedef typename vobj::scalar_object sobj;
|
||||
|
||||
std::vector<Field> _v; // _Nfull vectors
|
||||
|
||||
void report(int n,GridBase* value) {
|
||||
|
||||
std::cout << GridLogMessage << "BasisFieldVector allocated:\n";
|
||||
std::cout << GridLogMessage << " Delta N = " << n << "\n";
|
||||
std::cout << GridLogMessage << " Size of full vectors (size) = " <<
|
||||
((double)n*sizeof(vobj)*value->oSites() / 1024./1024./1024.) << " GB\n";
|
||||
std::cout << GridLogMessage << " Size = " << _v.size() << " Capacity = " << _v.capacity() << std::endl;
|
||||
|
||||
value->Barrier();
|
||||
|
||||
if (value->IsBoss()) {
|
||||
system("cat /proc/meminfo");
|
||||
}
|
||||
|
||||
value->Barrier();
|
||||
|
||||
}
|
||||
|
||||
BasisFieldVector(int Nm,GridBase* value) : _Nm(Nm), _v(Nm,value) {
|
||||
report(Nm,value);
|
||||
}
|
||||
|
||||
~BasisFieldVector() {
|
||||
}
|
||||
|
||||
Field& operator[](int i) {
|
||||
return _v[i];
|
||||
}
|
||||
|
||||
void orthogonalize(Field& w, int k) {
|
||||
for(int j=0; j<k; ++j){
|
||||
Coeff_t ip = (Coeff_t)innerProduct(_v[j],w);
|
||||
w = w - ip*_v[j];
|
||||
}
|
||||
}
|
||||
|
||||
void rotate(std::vector<RealD>& Qt,int j0, int j1, int k0,int k1,int Nm) {
|
||||
|
||||
GridBase* grid = _v[0]._grid;
|
||||
|
||||
#pragma omp parallel
|
||||
{
|
||||
std::vector < vobj > B(Nm);
|
||||
|
||||
#pragma omp for
|
||||
for(int ss=0;ss < grid->oSites();ss++){
|
||||
for(int j=j0; j<j1; ++j) B[j]=0.;
|
||||
|
||||
for(int j=j0; j<j1; ++j){
|
||||
for(int k=k0; k<k1; ++k){
|
||||
B[j] +=Qt[k+Nm*j] * _v[k]._odata[ss];
|
||||
}
|
||||
}
|
||||
for(int j=j0; j<j1; ++j){
|
||||
_v[j]._odata[ss] = B[j];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
size_t size() const {
|
||||
return _Nm;
|
||||
}
|
||||
|
||||
void resize(int n) {
|
||||
if (n > _Nm)
|
||||
_v.reserve(n);
|
||||
|
||||
_v.resize(n,_v[0]._grid);
|
||||
|
||||
if (n < _Nm)
|
||||
_v.shrink_to_fit();
|
||||
|
||||
report(n - _Nm,_v[0]._grid);
|
||||
|
||||
_Nm = n;
|
||||
}
|
||||
|
||||
std::vector<int> getIndex(std::vector<RealD>& sort_vals) {
|
||||
|
||||
std::vector<int> idx(sort_vals.size());
|
||||
iota(idx.begin(), idx.end(), 0);
|
||||
|
||||
// sort indexes based on comparing values in v
|
||||
sort(idx.begin(), idx.end(),
|
||||
[&sort_vals](int i1, int i2) {return ::fabs(sort_vals[i1]) < ::fabs(sort_vals[i2]);});
|
||||
|
||||
return idx;
|
||||
}
|
||||
|
||||
void reorderInPlace(std::vector<RealD>& sort_vals, std::vector<int>& idx) {
|
||||
GridStopWatch gsw;
|
||||
gsw.Start();
|
||||
|
||||
int nswaps = 0;
|
||||
for (size_t i=0;i<idx.size();i++) {
|
||||
if (idx[i] != i) {
|
||||
|
||||
// find proper place (this could be done in logarithmic time, don't bother for now)
|
||||
size_t j;
|
||||
for (j=i;j<idx.size();j++)
|
||||
if (idx[j]==i)
|
||||
break;
|
||||
assert(j!=idx.size());
|
||||
|
||||
Field _t(_v[0]._grid);
|
||||
_t = _v[idx[j]];
|
||||
_v[idx[j]] = _v[idx[i]];
|
||||
_v[idx[i]] = _t;
|
||||
|
||||
RealD _td = sort_vals[idx[j]];
|
||||
sort_vals[idx[j]] = sort_vals[idx[i]];
|
||||
sort_vals[idx[i]] = _td;
|
||||
|
||||
int _tt = idx[i];
|
||||
idx[i] = idx[j];
|
||||
idx[j] = _tt;
|
||||
|
||||
nswaps++;
|
||||
}
|
||||
}
|
||||
|
||||
// sort values
|
||||
gsw.Stop();
|
||||
std::cout << GridLogMessage << "Sorted eigenspace in place in " << gsw.Elapsed() << " using " << nswaps << " swaps" << std::endl;
|
||||
}
|
||||
|
||||
void sortInPlace(std::vector<RealD>& sort_vals, bool reverse) {
|
||||
|
||||
std::vector<int> idx = getIndex(sort_vals);
|
||||
if (reverse)
|
||||
std::reverse(idx.begin(), idx.end());
|
||||
|
||||
reorderInPlace(sort_vals,idx);
|
||||
|
||||
}
|
||||
|
||||
void deflate(const std::vector<RealD>& eval,const Field& src_orig,Field& result) {
|
||||
result = zero;
|
||||
int N = (int)_v.size();
|
||||
for (int i=0;i<N;i++) {
|
||||
Field& tmp = _v[i];
|
||||
axpy(result,TensorRemove(innerProduct(tmp,src_orig)) / eval[i],tmp,result);
|
||||
}
|
||||
}
|
||||
|
||||
};
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user