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Grid/lib/algorithms/iterative/PrecGeneralisedConjugateResidual.h

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#ifndef GRID_PREC_GCR_H
#define GRID_PREC_GCR_H
///////////////////////////////////////////////////////////////////////////////////////////////////////
//VPGCR Abe and Zhang, 2005.
//INTERNATIONAL JOURNAL OF NUMERICAL ANALYSIS AND MODELING
//Computing and Information Volume 2, Number 2, Pages 147-161
///////////////////////////////////////////////////////////////////////////////////////////////////////
namespace Grid {
template<class Field>
class PrecGeneralisedConjugateResidual : public OperatorFunction<Field> {
public:
RealD Tolerance;
Integer MaxIterations;
int verbose;
int mmax;
int nstep;
int steps;
LinearFunction<Field> &Preconditioner;
PrecGeneralisedConjugateResidual(RealD tol,Integer maxit,LinearFunction<Field> &Prec,int _mmax,int _nstep) :
Tolerance(tol),
MaxIterations(maxit),
Preconditioner(Prec),
mmax(_mmax),
nstep(_nstep)
{
verbose=1;
};
void operator() (LinearOperatorBase<Field> &Linop,const Field &src, Field &psi){
psi=zero;
RealD cp, ssq,rsq;
ssq=norm2(src);
rsq=Tolerance*Tolerance*ssq;
Field r(src._grid);
steps=0;
for(int k=0;k<MaxIterations;k++){
cp=GCRnStep(Linop,src,psi,rsq);
if ( verbose ) std::cout<<"VPGCR("<<mmax<<","<<nstep<<") "<< steps <<" steps cp = "<<cp<<std::endl;
if(cp<rsq) {
Linop.HermOp(psi,r);
axpy(r,-1.0,src,r);
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RealD tr = norm2(r);
std::cout<<"PrecGeneralisedConjugateResidual: Converged on iteration " <<steps
<< " computed residual "<<sqrt(cp/ssq)
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<< " true residual " <<sqrt(tr/ssq)
<< " target " <<Tolerance <<std::endl;
return;
}
}
std::cout<<"Variable Preconditioned GCR did not converge"<<std::endl;
assert(0);
}
RealD GCRnStep(LinearOperatorBase<Field> &Linop,const Field &src, Field &psi,RealD rsq){
RealD cp;
RealD a, b, c, d;
RealD zAz, zAAz;
RealD rAq, rq;
GridBase *grid = src._grid;
Field r(grid);
Field z(grid);
Field Az(grid);
////////////////////////////////
// history for flexible orthog
////////////////////////////////
std::vector<Field> q(mmax,grid);
std::vector<Field> p(mmax,grid);
std::vector<RealD> qq(mmax);
//////////////////////////////////
// initial guess x0 is taken as nonzero.
// r0=src-A x0 = src
//////////////////////////////////
Linop.HermOpAndNorm(psi,Az,zAz,zAAz);
r=src-Az;
/////////////////////
// p = Prec(r)
/////////////////////
Preconditioner(r,z);
Linop.HermOpAndNorm(z,Az,zAz,zAAz);
//p[0],q[0],qq[0]
p[0]= z;
q[0]= Az;
qq[0]= zAAz;
cp =norm2(r);
for(int k=0;k<nstep;k++){
steps++;
int kp = k+1;
int peri_k = k %mmax;
int peri_kp= kp%mmax;
rq= real(innerProduct(r,q[peri_k])); // what if rAr not real?
a = rq/qq[peri_k];
axpy(psi,a,p[peri_k],psi);
cp = axpy_norm(r,-a,q[peri_k],r);
if((k==nstep-1)||(cp<rsq)){
return cp;
}
Preconditioner(r,z);// solve Az = r
Linop.HermOpAndNorm(z,Az,zAz,zAAz);
q[peri_kp]=Az;
p[peri_kp]=z;
int northog = ((kp)>(mmax-1))?(mmax-1):(kp); // if more than mmax done, we orthog all mmax history.
for(int back=0;back<northog;back++){
int peri_back=(k-back)%mmax; assert((k-back)>=0);
b=-real(innerProduct(q[peri_back],Az))/qq[peri_back];
p[peri_kp]=p[peri_kp]+b*p[peri_back];
q[peri_kp]=q[peri_kp]+b*q[peri_back];
}
qq[peri_kp]=norm2(q[peri_kp]); // could use axpy_norm
}
assert(0); // never reached
return cp;
}
};
}
#endif