/************************************************************************************* Grid physics library, www.github.com/paboyle/Grid Source file: ./lib/algorithms/iterative/ConjugateGradientReliableUpdate.h Copyright (C) 2015 Author: Christopher Kelly 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_CONJUGATE_GRADIENT_RELIABLE_UPDATE_H #define GRID_CONJUGATE_GRADIENT_RELIABLE_UPDATE_H NAMESPACE_BEGIN(Grid); template::value == 2, int>::type = 0, typename std::enable_if< getPrecision::value == 1, int>::type = 0> class ConjugateGradientReliableUpdate : public LinearFunction { public: bool ErrorOnNoConverge; // throw an assert when the CG fails to converge. // Defaults true. RealD Tolerance; Integer MaxIterations; Integer IterationsToComplete; //Number of iterations the CG took to finish. Filled in upon completion Integer ReliableUpdatesPerformed; bool DoFinalCleanup; //Final DP cleanup, defaults to true Integer IterationsToCleanup; //Final DP cleanup step iterations LinearOperatorBase &Linop_f; LinearOperatorBase &Linop_d; GridBase* SinglePrecGrid; RealD Delta; //reliable update parameter //Optional ability to switch to a different linear operator once the tolerance reaches a certain point. Useful for single/half -> single/single LinearOperatorBase *Linop_fallback; RealD fallback_transition_tol; ConjugateGradientReliableUpdate(RealD tol, Integer maxit, RealD _delta, GridBase* _sp_grid, LinearOperatorBase &_Linop_f, LinearOperatorBase &_Linop_d, bool err_on_no_conv = true) : Tolerance(tol), MaxIterations(maxit), Delta(_delta), Linop_f(_Linop_f), Linop_d(_Linop_d), SinglePrecGrid(_sp_grid), ErrorOnNoConverge(err_on_no_conv), DoFinalCleanup(true), Linop_fallback(NULL) {}; void setFallbackLinop(LinearOperatorBase &_Linop_fallback, const RealD _fallback_transition_tol){ Linop_fallback = &_Linop_fallback; fallback_transition_tol = _fallback_transition_tol; } void operator()(const FieldD &src, FieldD &psi) { LinearOperatorBase *Linop_f_use = &Linop_f; bool using_fallback = false; psi.checkerboard = src.checkerboard; conformable(psi, src); RealD cp, c, a, d, b, ssq, qq, b_pred; FieldD p(src); FieldD mmp(src); FieldD r(src); // Initial residual computation & set up RealD guess = norm2(psi); assert(std::isnan(guess) == 0); Linop_d.HermOpAndNorm(psi, mmp, d, b); r = src - mmp; p = r; a = norm2(p); cp = a; ssq = norm2(src); std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: guess " << guess << std::endl; std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: src " << ssq << std::endl; std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: mp " << d << std::endl; std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: mmp " << b << std::endl; std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: cp,r " << cp << std::endl; std::cout << GridLogIterative << std::setprecision(4) << "ConjugateGradientReliableUpdate: p " << a << std::endl; RealD rsq = Tolerance * Tolerance * ssq; // Check if guess is really REALLY good :) if (cp <= rsq) { std::cout << GridLogMessage << "ConjugateGradientReliableUpdate guess was REALLY good\n"; std::cout << GridLogMessage << "\tComputed residual " << sqrt(cp / ssq)<HermOpAndNorm(p_f, mmp_f, d, qq); MatrixTimer.Stop(); LinalgTimer.Start(); a = c / d; b_pred = a * (a * qq - d) / c; cp = axpy_norm(r_f, -a, mmp_f, r_f); b = cp / c; // Fuse these loops ; should be really easy psi_f = a * p_f + psi_f; //p_f = p_f * b + r_f; LinalgTimer.Stop(); std::cout << GridLogIterative << "ConjugateGradientReliableUpdate: Iteration " << k << " residual " << cp << " target " << rsq << std::endl; std::cout << GridLogDebug << "a = "<< a << " b_pred = "<< b_pred << " b = "<< b << std::endl; std::cout << GridLogDebug << "qq = "<< qq << " d = "<< d << " c = "<< c << std::endl; if(cp > MaxResidSinceLastRelUp){ std::cout << GridLogIterative << "ConjugateGradientReliableUpdate: updating MaxResidSinceLastRelUp : " << MaxResidSinceLastRelUp << " -> " << cp << std::endl; MaxResidSinceLastRelUp = cp; } // Stopping condition if (cp <= rsq) { //Although not written in the paper, I assume that I have to add on the final solution precisionChange(mmp, psi_f); psi = psi + mmp; SolverTimer.Stop(); Linop_d.HermOpAndNorm(psi, mmp, d, qq); p = mmp - src; RealD srcnorm = sqrt(norm2(src)); RealD resnorm = sqrt(norm2(p)); RealD true_residual = resnorm / srcnorm; std::cout << GridLogMessage << "ConjugateGradientReliableUpdate Converged on iteration " << k << " after " << l << " reliable updates" << std::endl; std::cout << GridLogMessage << "\tComputed residual " << sqrt(cp / ssq)< CG(Tolerance,MaxIterations); CG.ErrorOnNoConverge = ErrorOnNoConverge; CG(Linop_d,src,psi); IterationsToCleanup = CG.IterationsToComplete; } else if (ErrorOnNoConverge) assert(true_residual / Tolerance < 10000.0); std::cout << GridLogMessage << "ConjugateGradientReliableUpdate complete.\n"; return; } else if(cp < Delta * MaxResidSinceLastRelUp) { //reliable update std::cout << GridLogMessage << "ConjugateGradientReliableUpdate " << cp << "(residual) < " << Delta << "(Delta) * " << MaxResidSinceLastRelUp << "(MaxResidSinceLastRelUp) on iteration " << k << " : performing reliable update\n"; precisionChange(mmp, psi_f); psi = psi + mmp; Linop_d.HermOpAndNorm(psi, mmp, d, qq); r = src - mmp; psi_f = zero; precisionChange(r_f, r); cp = norm2(r); MaxResidSinceLastRelUp = cp; b = cp/c; std::cout << GridLogMessage << "ConjugateGradientReliableUpdate new residual " << cp << std::endl; l = l+1; } p_f = p_f * b + r_f; //update search vector after reliable update appears to help convergence if(!using_fallback && Linop_fallback != NULL && cp < fallback_transition_tol){ std::cout << GridLogMessage << "ConjugateGradientReliableUpdate switching to fallback linear operator on iteration " << k << " at residual " << cp << std::endl; Linop_f_use = Linop_fallback; using_fallback = true; } } std::cout << GridLogMessage << "ConjugateGradientReliableUpdate did NOT converge" << std::endl; if (ErrorOnNoConverge) assert(0); IterationsToComplete = k; ReliableUpdatesPerformed = l; } }; NAMESPACE_END(Grid); #endif