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Grid/lib/algorithms/iterative/ConjugateGradient.h
2016-11-09 04:11:03 -08:00

169 lines
5.4 KiB
C++

/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradient.h
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: paboyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution
directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_CONJUGATE_GRADIENT_H
#define GRID_CONJUGATE_GRADIENT_H
namespace Grid {
/////////////////////////////////////////////////////////////
// Base classes for iterative processes based on operators
// single input vec, single output vec.
/////////////////////////////////////////////////////////////
template <class Field>
class ConjugateGradient : public OperatorFunction<Field> {
public:
bool ErrorOnNoConverge; // throw an assert when the CG fails to converge.
// Defaults true.
RealD Tolerance;
Integer MaxIterations;
ConjugateGradient(RealD tol, Integer maxit, bool err_on_no_conv = true)
: Tolerance(tol),
MaxIterations(maxit),
ErrorOnNoConverge(err_on_no_conv){};
void operator()(LinearOperatorBase<Field> &Linop, const Field &src,
Field &psi) {
psi.checkerboard = src.checkerboard;
conformable(psi, src);
RealD cp, c, a, d, b, ssq, qq, b_pred;
Field p(src);
Field mmp(src);
Field r(src);
// Initial residual computation & set up
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
Linop.HermOpAndNorm(psi, mmp, d, b);
r = src - mmp;
p = r;
a = norm2(p);
cp = a;
ssq = norm2(src);
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: guess " << guess << std::endl;
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: src " << ssq << std::endl;
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: mp " << d << std::endl;
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: mmp " << b << std::endl;
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: cp,r " << cp << std::endl;
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: p " << a << std::endl;
RealD rsq = Tolerance * Tolerance * ssq;
// Check if guess is really REALLY good :)
if (cp <= rsq) {
return;
}
std::cout << GridLogIterative << std::setprecision(4)
<< "ConjugateGradient: k=0 residual " << cp << " target " << rsq
<< std::endl;
GridStopWatch LinalgTimer;
GridStopWatch MatrixTimer;
GridStopWatch SolverTimer;
SolverTimer.Start();
int k;
for (k = 1; k <= MaxIterations; k++) {
c = cp;
MatrixTimer.Start();
Linop.HermOpAndNorm(p, mmp, d, qq);
MatrixTimer.Stop();
LinalgTimer.Start();
// RealD qqck = norm2(mmp);
// ComplexD dck = innerProduct(p,mmp);
a = c / d;
b_pred = a * (a * qq - d) / c;
cp = axpy_norm(r, -a, mmp, r);
b = cp / c;
// Fuse these loops ; should be really easy
psi = a * p + psi;
p = p * b + r;
LinalgTimer.Stop();
std::cout << GridLogIterative << "ConjugateGradient: Iteration " << k
<< " residual " << cp << " target " << rsq << std::endl;
// Stopping condition
if (cp <= rsq) {
SolverTimer.Stop();
Linop.HermOpAndNorm(psi, mmp, d, qq);
p = mmp - src;
RealD mmpnorm = sqrt(norm2(mmp));
RealD psinorm = sqrt(norm2(psi));
RealD srcnorm = sqrt(norm2(src));
RealD resnorm = sqrt(norm2(p));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage
<< "ConjugateGradient: Converged on iteration " << k << std::endl;
std::cout << GridLogMessage << "Computed residual " << sqrt(cp / ssq)
<< " true residual " << true_residual << " target "
<< Tolerance << std::endl;
std::cout << GridLogMessage << "Time elapsed: Iterations "
<< SolverTimer.Elapsed() << " Matrix "
<< MatrixTimer.Elapsed() << " Linalg "
<< LinalgTimer.Elapsed();
std::cout << std::endl;
if (ErrorOnNoConverge) assert(true_residual / Tolerance < 10000.0);
return;
}
}
std::cout << GridLogMessage << "ConjugateGradient did NOT converge"
<< std::endl;
if (ErrorOnNoConverge) assert(0);
}
};
}
#endif