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Daniel Richtmann 2017-11-06 17:05:25 +01:00
parent 8363edfcdb
commit 9e3c187a4d
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1 changed files with 191 additions and 2 deletions
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193
lib/algorithms/iterative/GeneralisedMinimalResidual.h
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@ -203,7 +203,7 @@ class GeneralisedMinimalResidual : public OperatorFunction<Field> {
LinOp.Op(psi, Dpsi);
r = src - Dpsi;
RealD cp = norm2(r); // cp = beta in DD-αAMG nomenclature
RealD cp = norm2(r); // cp = beta in WMG nomenclature, in WMG there is no norm2 but a sqrt(norm2) here
gamma[0] = cp;
std::cout << GridLogIterative << "cp " << cp << std::endl;
@ -223,13 +223,17 @@ class GeneralisedMinimalResidual : public OperatorFunction<Field> {
<< "GeneralizedMinimalResidual: k=0 residual " << cp << " target " << rsd_sq << std::endl;
GridStopWatch SolverTimer;
GridStopWatch MatrixTimer;
SolverTimer.Start();
for(auto j = 0; j < m; ++j) {
// std::cout << GridLogIterative << "GeneralizedMinimalResidual: Start of outer loop with index j = " << j << std::endl;
MatrixTimer.Start();
LinOp.Op(v[j], Dv);
MatrixTimer.Stop();
w = Dv;
for(auto i = 0; i <= j; ++i) {
@ -280,7 +284,192 @@ class GeneralisedMinimalResidual : public OperatorFunction<Field> {
std::cout << GridLogMessage << "Time breakdown " << std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() << std::endl;
// std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() << std::endl;
// std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() << std::endl;
IterationsToComplete = j;
break;
}
}
// backward substitution
computeSolution(y, gamma, H, v, psi, IterationsToComplete);
std::cout << GridLogIterative << "GeneralizedMinimalResidual: End of operator()" << std::endl;
}
void alternativeOperatorImplementation()(LinearOperatorBase<Field> &LinOp, const Field &src, Field &psi) {
psi.checkerboard = src.checkerboard;
psi(conformable, src);
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD cp;
RealD ssq = norm2(src);
RealD rsd_sq = Tolerance * Tolerance * ssq;
Field r(src._grid);
Field Dpsi(src._grid);
PrecTimer.Reset();
MatTimer.Reset();
LinalgTimer.Reset();
GridStopWatch SolverTimer;
SolverTimer.Start();
int iterations = 0;
for (int k=0; k<MaxIterations; k++) {
cp = outerLoopBody();
// Stopping condition
if (cp <= rsd_sq) {
SolverTimer.Stop();
Linop.Op(psi, Dpsi); // maybe can improve these two lines
r = src - Dpsi; // by technique used in VPGCR
RealD srcnorm = sqrt(ssq);
RealD resnorm = sqrt(norm2(r));
RealD true_residual = resnorm / srcnorm;
std::cout << GridLogMessage << "GeneralizedMinimalResidual: Converged on iteration " << k << std::endl;
std::cout << GridLogMessage << "\tComputed residual " << sqrt(cp / ssq) << std::endl;
std::cout << GridLogMessage << "\tTrue residual " << true_residual << std::endl;
std::cout << GridLogMessage << "\tTarget " << Tolerance << std::endl;
std::cout << GridLogMessage << "GeneralizedMinimalResidual Time breakdown" << std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tPrecon " << PrecTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() << std::endl;
return;
}
}
std::cout << GridLogMessage << "GeneralizedMinimalResidual did NOT converge" << std::endl;
if (ErrorOnNoConverge)
assert(0);
}
RealD outerLoopBody() {
}
void Step() {
int m = MaxIterations;
Field r(src);
Field w(src);
Field Dpsi(src);
Field Dv(src);
std::vector<Field> v(m + 1, src);
Eigen::MatrixXcd H = Eigen::MatrixXcd::Zero(m + 1, m);
std::vector<std::complex<double>> y(m + 1, 0.);
std::vector<std::complex<double>> gamma(m + 1, 0.);
std::vector<std::complex<double>> c(m + 1, 0.);
std::vector<std::complex<double>> s(m + 1, 0.);
// Initial residual computation & set up
RealD guess = norm2(psi);
assert(std::isnan(guess) == 0);
RealD ssq = norm2(src); // flopcount.addSiteFlops(4*Nc*Ns,s); // stands for "source squared"
RealD rsd_sq = Tolerance * Tolerance * ssq; // flopcount.addSiteFlops(4*Nc*Ns,s); // stands for "residual squared"
LinOp.Op(psi, Dpsi);
r = src - Dpsi;
RealD cp = norm2(r); // cp = beta in WMG nomenclature, in WMG there is no norm2 but a sqrt(norm2) here
gamma[0] = cp;
std::cout << GridLogIterative << "cp " << cp << std::endl;
v[0] = (1. / cp) * r;
std::cout << GridLogIterative << std::setprecision(4) << "GeneralizedMinimalResidual: guess " << guess << std::endl;
std::cout << GridLogIterative << std::setprecision(4) << "GeneralizedMinimalResidual: src " << ssq << std::endl;
// std::cout << GridLogIterative << std::setprecision(4) << "GeneralizedMinimalResidual: mp " << d << std::endl;
std::cout << GridLogIterative << std::setprecision(4) << "GeneralizedMinimalResidual: cp,r " << cp << std::endl;
if (cp <= rsd_sq) {
return;
}
std::cout << GridLogIterative << std::setprecision(4)
<< "GeneralizedMinimalResidual: k=0 residual " << cp << " target " << rsd_sq << std::endl;
GridStopWatch SolverTimer;
GridStopWatch MatrixTimer;
SolverTimer.Start();
for(auto j = 0; j < m; ++j) {
// std::cout << GridLogIterative << "GeneralizedMinimalResidual: Start of outer loop with index j = " << j << std::endl;
MatrixTimer.Start();
LinOp.Op(v[j], Dv);
MatrixTimer.Stop();
w = Dv;
for(auto i = 0; i <= j; ++i) {
H(i, j) = innerProduct(v[i], w);
w = w - H(i, j) * v[i];
}
H(j + 1, j) = norm2(w);
v[j + 1] = (1. / H(j + 1, j)) * w;
// end of arnoldi process, begin of givens rotations
// apply old Givens rotation
for(auto i = 0; i < j ; ++i) {
auto tmp = -s[i] * H(i, j) + c[i] * H(i + 1, j);
H(i, j) = std::conj(c[i]) * H(i, j) + std::conj(s[i]) * H(i + 1, j);
H(i + 1, j) = tmp;
}
// compute new Givens Rotation
ComplexD nu = sqrt(std::norm(H(j, j)) + std::norm(H(j + 1, j)));
c[j] = H(j, j) / nu;
s[j] = H(j + 1, j) / nu;
std::cout << GridLogIterative << "GeneralizedMinimalResidual: nu" << nu << std::endl;
std::cout << GridLogIterative << "GeneralizedMinimalResidual: H("<<j<<","<<j<<")" << H(j,j) << std::endl;
std::cout << GridLogIterative << "GeneralizedMinimalResidual: H("<<j+1<<","<<j<<")" << H(j+1,j) << std::endl;
// apply new Givens rotation
H(j, j) = nu;
H(j + 1, j) = 0.;
/* ORDERING??? */
gamma[j + 1] = -s[j] * gamma[j];
gamma[j] = std::conj(c[j]) * gamma[j];
/* for(auto k = 0; k <= j+1 ; ++k) */
/* std::cout << GridLogIterative << "k " << k << "nu " << nu << " c["<<k<<"]" << c[k]<< " s["<<k<<"]" << s[k] << " gamma["<<k<<"]" << gamma[k] << std::endl; */
std::cout << GridLogIterative << "GeneralisedMinimalResidual: Iteration "
<< j << " residual " << std::abs(gamma[j + 1]) << std::endl; //" target "
/* << TargetResSq << std::endl; */
if(std::abs(gamma[j + 1]) / sqrt(cp) < Tolerance) {
SolverTimer.Stop();
std::cout << GridLogMessage << "GeneralizedMinimalResidual Converged on iteration " << j << std::endl;
// std::cout << GridLogMessage << "\tComputed residual " << sqrt(cp / ssq) << std::endl;
// std::cout << GridLogMessage << "\tTrue residual " << true_residual << std::endl;
std::cout << GridLogMessage << "\tTarget " << Tolerance << std::endl;
std::cout << GridLogMessage << "Time breakdown " << std::endl;
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() << std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() << std::endl;
// std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() << std::endl;
IterationsToComplete = j;