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Merge branch 'feature/CG-reliable-update' into ckelly_develop
This commit is contained in:
Christopher Kelly
commit
9b6cde173f
@ -44,6 +44,7 @@ Author: Peter Boyle <paboyle@ph.ed.ac.uk>
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#include <Grid/algorithms/iterative/SchurRedBlack.h>
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#include <Grid/algorithms/iterative/ConjugateGradientMultiShift.h>
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#include <Grid/algorithms/iterative/ConjugateGradientMixedPrec.h>
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#include <Grid/algorithms/iterative/ConjugateGradientReliableUpdate.h>
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// Lanczos support
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//#include <Grid/algorithms/iterative/MatrixUtils.h>
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231
lib/algorithms/iterative/ConjugateGradientReliableUpdate.h
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231
lib/algorithms/iterative/ConjugateGradientReliableUpdate.h
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@ -0,0 +1,231 @@
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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/ConjugateGradientReliableUpdate.h
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Copyright (C) 2015
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Author: Christopher Kelly <ckelly@phys.columbia.edu>
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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_CONJUGATE_GRADIENT_RELIABLE_UPDATE_H
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#define GRID_CONJUGATE_GRADIENT_RELIABLE_UPDATE_H
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namespace Grid {
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template<class FieldD,class FieldF, typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0,typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
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class ConjugateGradientReliableUpdate : public LinearFunction<FieldD> {
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public:
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bool ErrorOnNoConverge; // throw an assert when the CG fails to converge.
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// Defaults true.
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RealD Tolerance;
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Integer MaxIterations;
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Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion
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Integer ReliableUpdatesPerformed;
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bool DoFinalCleanup; //Final DP cleanup, defaults to true
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Integer IterationsToCleanup; //Final DP cleanup step iterations
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LinearOperatorBase<FieldF> &Linop_f;
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LinearOperatorBase<FieldD> &Linop_d;
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GridBase* SinglePrecGrid;
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RealD Delta; //reliable update parameter
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ConjugateGradientReliableUpdate(RealD tol, Integer maxit, RealD _delta, GridBase* _sp_grid, LinearOperatorBase<FieldF> &_Linop_f, LinearOperatorBase<FieldD> &_Linop_d, bool err_on_no_conv = true)
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: Tolerance(tol),
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MaxIterations(maxit),
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Delta(_delta),
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Linop_f(_Linop_f),
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Linop_d(_Linop_d),
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SinglePrecGrid(_sp_grid),
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ErrorOnNoConverge(err_on_no_conv),
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DoFinalCleanup(true)
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{};
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void operator()(const FieldD &src, FieldD &psi) {
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psi.checkerboard = src.checkerboard;
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conformable(psi, src);
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RealD cp, c, a, d, b, ssq, qq, b_pred;
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FieldD p(src);
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FieldD mmp(src);
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FieldD r(src);
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// Initial residual computation & set up
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RealD guess = norm2(psi);
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assert(std::isnan(guess) == 0);
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Linop_d.HermOpAndNorm(psi, mmp, d, b);
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r = src - mmp;
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p = r;
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a = norm2(p);
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cp = a;
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ssq = norm2(src);
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std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: guess " << guess << std::endl;
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std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: src " << ssq << std::endl;
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std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: mp " << d << std::endl;
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std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: mmp " << b << std::endl;
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std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: cp,r " << cp << std::endl;
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std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: p " << a << std::endl;
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RealD rsq = Tolerance * Tolerance * ssq;
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// Check if guess is really REALLY good :)
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if (cp <= rsq) {
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return;
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}
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//Single prec initialization
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FieldF r_f(SinglePrecGrid);
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r_f.checkerboard = r.checkerboard;
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precisionChange(r_f, r);
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FieldF psi_f(r_f);
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psi_f = zero;
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FieldF p_f(r_f);
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FieldF mmp_f(r_f);
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RealD MaxResidSinceLastRelUp = cp; //initial residual
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std::cout << GridLogIterative << std::setprecision(4)
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<< "ConjugateGradient: k=0 residual " << cp << " target " << rsq << std::endl;
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GridStopWatch LinalgTimer;
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GridStopWatch MatrixTimer;
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GridStopWatch SolverTimer;
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SolverTimer.Start();
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int k = 0;
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int l = 0;
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for (k = 1; k <= MaxIterations; k++) {
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c = cp;
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MatrixTimer.Start();
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Linop_f.HermOpAndNorm(p_f, mmp_f, d, qq);
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MatrixTimer.Stop();
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LinalgTimer.Start();
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a = c / d;
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b_pred = a * (a * qq - d) / c;
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cp = axpy_norm(r_f, -a, mmp_f, r_f);
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b = cp / c;
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// Fuse these loops ; should be really easy
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psi_f = a * p_f + psi_f;
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//p_f = p_f * b + r_f;
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LinalgTimer.Stop();
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std::cout << GridLogIterative << "ConjugateGradientReliableUpdate: Iteration " << k
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<< " residual " << cp << " target " << rsq << std::endl;
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std::cout << GridLogDebug << "a = "<< a << " b_pred = "<< b_pred << " b = "<< b << std::endl;
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std::cout << GridLogDebug << "qq = "<< qq << " d = "<< d << " c = "<< c << std::endl;
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if(cp > MaxResidSinceLastRelUp){
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std::cout << GridLogIterative << "ConjugateGradientReliableUpdate: updating MaxResidSinceLastRelUp : " << MaxResidSinceLastRelUp << " -> " << cp << std::endl;
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MaxResidSinceLastRelUp = cp;
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}
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// Stopping condition
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if (cp <= rsq) {
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//Although not written in the paper, I assume that I have to add on the final solution
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precisionChange(mmp, psi_f);
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psi = psi + mmp;
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SolverTimer.Stop();
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Linop_d.HermOpAndNorm(psi, mmp, d, qq);
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p = mmp - src;
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RealD srcnorm = sqrt(norm2(src));
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RealD resnorm = sqrt(norm2(p));
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RealD true_residual = resnorm / srcnorm;
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std::cout << GridLogMessage << "ConjugateGradientReliableUpdate Converged on iteration " << k << " after " << l << " reliable updates" << std::endl;
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std::cout << GridLogMessage << "\tComputed residual " << sqrt(cp / ssq)<<std::endl;
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std::cout << GridLogMessage << "\tTrue residual " << true_residual<<std::endl;
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std::cout << GridLogMessage << "\tTarget " << Tolerance << std::endl;
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std::cout << GridLogMessage << "Time breakdown "<<std::endl;
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std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl;
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std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
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std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() <<std::endl;
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IterationsToComplete = k;
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ReliableUpdatesPerformed = l;
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if(DoFinalCleanup){
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//Do a final CG to cleanup
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std::cout << GridLogMessage << "ConjugateGradientReliableUpdate performing final cleanup.\n";
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ConjugateGradient<FieldD> CG(Tolerance,MaxIterations);
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CG.ErrorOnNoConverge = ErrorOnNoConverge;
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CG(Linop_d,src,psi);
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IterationsToCleanup = CG.IterationsToComplete;
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}
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else if (ErrorOnNoConverge) assert(true_residual / Tolerance < 10000.0);
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std::cout << GridLogMessage << "ConjugateGradientReliableUpdate complete.\n";
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return;
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}
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else if(cp < Delta * MaxResidSinceLastRelUp) { //reliable update
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std::cout << GridLogMessage << "ConjugateGradientReliableUpdate "
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<< cp << "(residual) < " << Delta << "(Delta) * " << MaxResidSinceLastRelUp << "(MaxResidSinceLastRelUp) on iteration " << k << " : performing reliable update\n";
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precisionChange(mmp, psi_f);
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psi = psi + mmp;
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Linop_d.HermOpAndNorm(psi, mmp, d, qq);
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r = src - mmp;
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psi_f = zero;
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precisionChange(r_f, r);
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cp = norm2(r);
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MaxResidSinceLastRelUp = cp;
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std::cout << GridLogMessage << "ConjugateGradientReliableUpdate new residual " << cp << std::endl;
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l = l+1;
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}
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p_f = p_f * b + r_f; //update search vector after reliable update appears to help convergence
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}
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std::cout << GridLogMessage << "ConjugateGradientReliableUpdate did NOT converge"
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<< std::endl;
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if (ErrorOnNoConverge) assert(0);
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IterationsToComplete = k;
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ReliableUpdatesPerformed = l;
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}
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};
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};
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#endif
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@ -80,31 +80,47 @@ int main (int argc, char ** argv)
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LatticeFermionD src_o(FrbGrid);
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LatticeFermionD result_o(FrbGrid);
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LatticeFermionD result_o_2(FrbGrid);
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LatticeFermionD result_cg(FrbGrid);
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pickCheckerboard(Odd,src_o,src);
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result_o.checkerboard = Odd;
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result_o = zero;
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result_o_2.checkerboard = Odd;
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result_o_2 = zero;
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result_cg.checkerboard = Odd;
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result_cg = zero;
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LatticeFermionD result_mcg(result_cg);
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LatticeFermionD result_rlcg(result_cg);
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SchurDiagMooeeOperator<DomainWallFermionD,LatticeFermionD> HermOpEO(Ddwf);
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SchurDiagMooeeOperator<DomainWallFermionFH,LatticeFermionF> HermOpEO_f(Ddwf_f);
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//#define DO_MIXED_CG
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#define DO_RLUP_CG
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#ifdef DO_MIXED_CG
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std::cout << "Starting mixed CG" << std::endl;
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MixedPrecisionConjugateGradient<LatticeFermionD,LatticeFermionF> mCG(1.0e-8, 10000, 50, FrbGrid_f, HermOpEO_f, HermOpEO);
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mCG.InnerTolerance = 3.0e-5;
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mCG(src_o,result_o);
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mCG(src_o,result_mcg);
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#endif
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#ifdef DO_RLUP_CG
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std::cout << "Starting reliable update CG" << std::endl;
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ConjugateGradientReliableUpdate<LatticeFermionD,LatticeFermionF> rlCG(1.e-8, 10000, 0.1, FrbGrid_f, HermOpEO_f, HermOpEO);
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rlCG(src_o,result_rlcg);
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#endif
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std::cout << "Starting regular CG" << std::endl;
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ConjugateGradient<LatticeFermionD> CG(1.0e-8,10000);
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CG(HermOpEO,src_o,result_o_2);
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CG(HermOpEO,src_o,result_cg);
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LatticeFermionD diff_o(FrbGrid);
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RealD diff = axpy_norm(diff_o, -1.0, result_o, result_o_2);
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std::cout << "Diff between mixed and regular CG: " << diff << std::endl;
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#ifdef DO_MIXED_CG
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LatticeFermionD diff_mcg(FrbGrid);
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RealD vdiff_mcg = axpy_norm(diff_mcg, -1.0, result_cg, result_mcg);
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std::cout << "Diff between mixed and regular CG: " << vdiff_mcg << std::endl;
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#endif
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#ifdef DO_RLUP_CG
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LatticeFermionD diff_rlcg(FrbGrid);
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RealD vdiff_rlcg = axpy_norm(diff_rlcg, -1.0, result_cg, result_rlcg);
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std::cout << "Diff between reliable update and regular CG: " << vdiff_rlcg << std::endl;
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#endif
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Grid_finalize();
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}
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