mirror of
https://github.com/paboyle/Grid.git
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d9cd4f0273
Code stalls and resumes on KNL at cambridge. Curious. CG iterations 23ms each, then 3200 ms pauses. Mean bandwidth reports as 200MB/s. Comms dominant in the report. However, the time behaviour suggests it is *bursty*.... Could be swap to disk?
601 lines
20 KiB
C++
601 lines
20 KiB
C++
/*************************************************************************************
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Grid physics library, www.github.com/paboyle/Grid
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Source file: ./lib/algorithms/iterative/BlockConjugateGradient.h
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Copyright (C) 2017
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Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
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Author: Peter Boyle <paboyle@ph.ed.ac.uk>
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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
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directory
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*************************************************************************************/
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/* END LEGAL */
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#ifndef GRID_BLOCK_CONJUGATE_GRADIENT_H
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#define GRID_BLOCK_CONJUGATE_GRADIENT_H
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namespace Grid {
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enum BlockCGtype { BlockCG, BlockCGrQ, CGmultiRHS };
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//////////////////////////////////////////////////////////////////////////
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// Block conjugate gradient. Dimension zero should be the block direction
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//////////////////////////////////////////////////////////////////////////
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template <class Field>
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class BlockConjugateGradient : public OperatorFunction<Field> {
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public:
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typedef typename Field::scalar_type scomplex;
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int blockDim ;
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int Nblock;
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BlockCGtype CGtype;
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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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BlockConjugateGradient(BlockCGtype cgtype,int _Orthog,RealD tol, Integer maxit, bool err_on_no_conv = true)
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: Tolerance(tol), CGtype(cgtype), blockDim(_Orthog), MaxIterations(maxit), ErrorOnNoConverge(err_on_no_conv)
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{};
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// Thin QR factorisation (google it)
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////////////////////////////////////////////////////////////////////////////////////////////////////
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void ThinQRfact (Eigen::MatrixXcd &m_rr,
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Eigen::MatrixXcd &C,
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Eigen::MatrixXcd &Cinv,
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Field & Q,
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const Field & R)
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{
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int Orthog = blockDim; // First dimension is block dim; this is an assumption
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////////////////////////////////////////////////////////////////////////////////////////////////////
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//Dimensions
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// R_{ferm x Nblock} = Q_{ferm x Nblock} x C_{Nblock x Nblock} -> ferm x Nblock
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//
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// Rdag R = m_rr = Herm = L L^dag <-- Cholesky decomposition (LLT routine in Eigen)
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//
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// Q C = R => Q = R C^{-1}
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//
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// Want Ident = Q^dag Q = C^{-dag} R^dag R C^{-1} = C^{-dag} L L^dag C^{-1} = 1_{Nblock x Nblock}
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//
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// Set C = L^{dag}, and then Q^dag Q = ident
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//
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// Checks:
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// Cdag C = Rdag R ; passes.
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// QdagQ = 1 ; passes
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////////////////////////////////////////////////////////////////////////////////////////////////////
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sliceInnerProductMatrix(m_rr,R,R,Orthog);
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// Cholesky from Eigen
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// There exists a ldlt that is documented as more stable
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////////////////////////////////////////////////////////////////////////////////////////////////////
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Eigen::MatrixXcd L = m_rr.llt().matrixL();
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C = L.adjoint();
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Cinv = C.inverse();
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// Q = R C^{-1}
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//
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// Q_j = R_i Cinv(i,j)
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//
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// NB maddMatrix conventions are Right multiplication X[j] a[j,i] already
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// FIXME:: make a sliceMulMatrix to avoid zero vector
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sliceMulMatrix(Q,Cinv,R,Orthog);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// Call one of several implementations
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////////////////////////////////////////////////////////////////////////////////////////////////////
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void operator()(LinearOperatorBase<Field> &Linop, const Field &Src, Field &Psi)
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{
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if ( CGtype == BlockCGrQ ) {
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BlockCGrQsolve(Linop,Src,Psi);
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} else if (CGtype == BlockCG ) {
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BlockCGsolve(Linop,Src,Psi);
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} else if (CGtype == CGmultiRHS ) {
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CGmultiRHSsolve(Linop,Src,Psi);
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} else {
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assert(0);
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}
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}
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////////////////////////////////////////////////////////////////////////////
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// BlockCGrQ implementation:
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//--------------------------
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// X is guess/Solution
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// B is RHS
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// Solve A X_i = B_i ; i refers to Nblock index
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////////////////////////////////////////////////////////////////////////////
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void BlockCGrQsolve(LinearOperatorBase<Field> &Linop, const Field &B, Field &X)
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{
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int Orthog = blockDim; // First dimension is block dim; this is an assumption
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Nblock = B._grid->_fdimensions[Orthog];
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std::cout<<GridLogMessage<<" Block Conjugate Gradient : Orthog "<<Orthog<<" Nblock "<<Nblock<<std::endl;
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X.checkerboard = B.checkerboard;
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conformable(X, B);
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Field tmp(B);
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Field Q(B);
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Field D(B);
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Field Z(B);
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Field AD(B);
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Eigen::MatrixXcd m_DZ = Eigen::MatrixXcd::Identity(Nblock,Nblock);
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Eigen::MatrixXcd m_M = Eigen::MatrixXcd::Identity(Nblock,Nblock);
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Eigen::MatrixXcd m_rr = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_C = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_Cinv = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_S = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_Sinv = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_tmp = Eigen::MatrixXcd::Identity(Nblock,Nblock);
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Eigen::MatrixXcd m_tmp1 = Eigen::MatrixXcd::Identity(Nblock,Nblock);
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// Initial residual computation & set up
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std::vector<RealD> residuals(Nblock);
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std::vector<RealD> ssq(Nblock);
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sliceNorm(ssq,B,Orthog);
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RealD sssum=0;
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for(int b=0;b<Nblock;b++) sssum+=ssq[b];
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sliceNorm(residuals,B,Orthog);
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for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
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sliceNorm(residuals,X,Orthog);
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for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
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/************************************************************************
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* Block conjugate gradient rQ (Sebastien Birk Thesis, after Dubrulle 2001)
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************************************************************************
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* Dimensions:
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*
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* X,B==(Nferm x Nblock)
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* A==(Nferm x Nferm)
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*
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* Nferm = Nspin x Ncolour x Ncomplex x Nlattice_site
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*
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* QC = R = B-AX, D = Q ; QC => Thin QR factorisation (google it)
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* for k:
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* Z = AD
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* M = [D^dag Z]^{-1}
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* X = X + D MC
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* QS = Q - ZM
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* D = Q + D S^dag
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* C = S C
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*/
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///////////////////////////////////////
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// Initial block: initial search dir is guess
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///////////////////////////////////////
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std::cout << GridLogMessage<<"BlockCGrQ algorithm initialisation " <<std::endl;
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//1. QC = R = B-AX, D = Q ; QC => Thin QR factorisation (google it)
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Linop.HermOp(X, AD);
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tmp = B - AD;
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//std::cout << GridLogMessage << " initial tmp " << norm2(tmp)<< std::endl;
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ThinQRfact (m_rr, m_C, m_Cinv, Q, tmp);
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//std::cout << GridLogMessage << " initial Q " << norm2(Q)<< std::endl;
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//std::cout << GridLogMessage << " m_rr " << m_rr<<std::endl;
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//std::cout << GridLogMessage << " m_C " << m_C<<std::endl;
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//std::cout << GridLogMessage << " m_Cinv " << m_Cinv<<std::endl;
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D=Q;
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std::cout << GridLogMessage<<"BlockCGrQ computed initial residual and QR fact " <<std::endl;
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///////////////////////////////////////
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// Timers
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///////////////////////////////////////
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GridStopWatch sliceInnerTimer;
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GridStopWatch sliceMaddTimer;
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GridStopWatch QRTimer;
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GridStopWatch MatrixTimer;
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GridStopWatch SolverTimer;
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SolverTimer.Start();
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int k;
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for (k = 1; k <= MaxIterations; k++) {
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//3. Z = AD
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MatrixTimer.Start();
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Linop.HermOp(D, Z);
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MatrixTimer.Stop();
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//std::cout << GridLogMessage << " norm2 Z " <<norm2(Z)<<std::endl;
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//4. M = [D^dag Z]^{-1}
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sliceInnerTimer.Start();
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sliceInnerProductMatrix(m_DZ,D,Z,Orthog);
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sliceInnerTimer.Stop();
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m_M = m_DZ.inverse();
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//std::cout << GridLogMessage << " m_DZ " <<m_DZ<<std::endl;
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//5. X = X + D MC
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m_tmp = m_M * m_C;
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sliceMaddTimer.Start();
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sliceMaddMatrix(X,m_tmp, D,X,Orthog);
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sliceMaddTimer.Stop();
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//6. QS = Q - ZM
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sliceMaddTimer.Start();
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sliceMaddMatrix(tmp,m_M,Z,Q,Orthog,-1.0);
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sliceMaddTimer.Stop();
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QRTimer.Start();
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ThinQRfact (m_rr, m_S, m_Sinv, Q, tmp);
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QRTimer.Stop();
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//7. D = Q + D S^dag
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m_tmp = m_S.adjoint();
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sliceMaddTimer.Start();
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sliceMaddMatrix(D,m_tmp,D,Q,Orthog);
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sliceMaddTimer.Stop();
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//8. C = S C
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m_C = m_S*m_C;
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/*********************
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* convergence monitor
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*********************
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*/
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m_rr = m_C.adjoint() * m_C;
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RealD max_resid=0;
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RealD rrsum=0;
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RealD rr;
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for(int b=0;b<Nblock;b++) {
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rrsum+=real(m_rr(b,b));
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rr = real(m_rr(b,b))/ssq[b];
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if ( rr > max_resid ) max_resid = rr;
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}
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std::cout << GridLogIterative << "\titeration "<<k<<" rr_sum "<<rrsum<<" ssq_sum "<< sssum
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<<" ave "<<std::sqrt(rrsum/sssum) << " max "<< max_resid <<std::endl;
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if ( max_resid < Tolerance*Tolerance ) {
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SolverTimer.Stop();
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std::cout << GridLogMessage<<"BlockCGrQ converged in "<<k<<" iterations"<<std::endl;
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for(int b=0;b<Nblock;b++){
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std::cout << GridLogMessage<< "\t\tblock "<<b<<" computed resid "
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<< std::sqrt(real(m_rr(b,b))/ssq[b])<<std::endl;
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}
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std::cout << GridLogMessage<<"\tMax residual is "<<std::sqrt(max_resid)<<std::endl;
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Linop.HermOp(X, AD);
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AD = AD-B;
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std::cout << GridLogMessage <<"\t True residual is " << std::sqrt(norm2(AD)/norm2(B)) <<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 << "\tInnerProd " << sliceInnerTimer.Elapsed() <<std::endl;
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std::cout << GridLogMessage << "\tMaddMatrix " << sliceMaddTimer.Elapsed() <<std::endl;
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std::cout << GridLogMessage << "\tThinQRfact " << QRTimer.Elapsed() <<std::endl;
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IterationsToComplete = k;
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return;
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}
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}
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std::cout << GridLogMessage << "BlockConjugateGradient(rQ) did NOT converge" << std::endl;
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if (ErrorOnNoConverge) assert(0);
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IterationsToComplete = k;
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}
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//////////////////////////////////////////////////////////////////////////
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// Block conjugate gradient; Original O'Leary Dimension zero should be the block direction
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//////////////////////////////////////////////////////////////////////////
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void BlockCGsolve(LinearOperatorBase<Field> &Linop, const Field &Src, Field &Psi)
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{
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int Orthog = blockDim; // First dimension is block dim; this is an assumption
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Nblock = Src._grid->_fdimensions[Orthog];
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std::cout<<GridLogMessage<<" Block Conjugate Gradient : Orthog "<<Orthog<<" Nblock "<<Nblock<<std::endl;
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Psi.checkerboard = Src.checkerboard;
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conformable(Psi, Src);
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Field P(Src);
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Field AP(Src);
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Field R(Src);
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Eigen::MatrixXcd m_pAp = Eigen::MatrixXcd::Identity(Nblock,Nblock);
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Eigen::MatrixXcd m_pAp_inv= Eigen::MatrixXcd::Identity(Nblock,Nblock);
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Eigen::MatrixXcd m_rr = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_rr_inv = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_alpha = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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Eigen::MatrixXcd m_beta = Eigen::MatrixXcd::Zero(Nblock,Nblock);
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// Initial residual computation & set up
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std::vector<RealD> residuals(Nblock);
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std::vector<RealD> ssq(Nblock);
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sliceNorm(ssq,Src,Orthog);
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RealD sssum=0;
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for(int b=0;b<Nblock;b++) sssum+=ssq[b];
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sliceNorm(residuals,Src,Orthog);
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for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
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sliceNorm(residuals,Psi,Orthog);
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for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
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// Initial search dir is guess
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Linop.HermOp(Psi, AP);
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/************************************************************************
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* Block conjugate gradient (Stephen Pickles, thesis 1995, pp 71, O Leary 1980)
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************************************************************************
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* O'Leary : R = B - A X
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* O'Leary : P = M R ; preconditioner M = 1
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* O'Leary : alpha = PAP^{-1} RMR
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* O'Leary : beta = RMR^{-1}_old RMR_new
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* O'Leary : X=X+Palpha
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* O'Leary : R_new=R_old-AP alpha
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* O'Leary : P=MR_new+P beta
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*/
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R = Src - AP;
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P = R;
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sliceInnerProductMatrix(m_rr,R,R,Orthog);
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GridStopWatch sliceInnerTimer;
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GridStopWatch sliceMaddTimer;
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GridStopWatch MatrixTimer;
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GridStopWatch SolverTimer;
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SolverTimer.Start();
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int k;
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for (k = 1; k <= MaxIterations; k++) {
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RealD rrsum=0;
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for(int b=0;b<Nblock;b++) rrsum+=real(m_rr(b,b));
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std::cout << GridLogIterative << "\titeration "<<k<<" rr_sum "<<rrsum<<" ssq_sum "<< sssum
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<<" / "<<std::sqrt(rrsum/sssum) <<std::endl;
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MatrixTimer.Start();
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Linop.HermOp(P, AP);
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MatrixTimer.Stop();
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// Alpha
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sliceInnerTimer.Start();
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sliceInnerProductMatrix(m_pAp,P,AP,Orthog);
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sliceInnerTimer.Stop();
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m_pAp_inv = m_pAp.inverse();
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m_alpha = m_pAp_inv * m_rr ;
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// Psi, R update
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sliceMaddTimer.Start();
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sliceMaddMatrix(Psi,m_alpha, P,Psi,Orthog); // add alpha * P to psi
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sliceMaddMatrix(R ,m_alpha,AP, R,Orthog,-1.0);// sub alpha * AP to resid
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sliceMaddTimer.Stop();
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// Beta
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m_rr_inv = m_rr.inverse();
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sliceInnerTimer.Start();
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sliceInnerProductMatrix(m_rr,R,R,Orthog);
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sliceInnerTimer.Stop();
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m_beta = m_rr_inv *m_rr;
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// Search update
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sliceMaddTimer.Start();
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sliceMaddMatrix(AP,m_beta,P,R,Orthog);
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sliceMaddTimer.Stop();
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P= AP;
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/*********************
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* convergence monitor
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*********************
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*/
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RealD max_resid=0;
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RealD rr;
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for(int b=0;b<Nblock;b++){
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rr = real(m_rr(b,b))/ssq[b];
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if ( rr > max_resid ) max_resid = rr;
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}
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if ( max_resid < Tolerance*Tolerance ) {
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SolverTimer.Stop();
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std::cout << GridLogMessage<<"BlockCG converged in "<<k<<" iterations"<<std::endl;
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for(int b=0;b<Nblock;b++){
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std::cout << GridLogMessage<< "\t\tblock "<<b<<" computed resid "
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<< std::sqrt(real(m_rr(b,b))/ssq[b])<<std::endl;
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}
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std::cout << GridLogMessage<<"\tMax residual is "<<std::sqrt(max_resid)<<std::endl;
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Linop.HermOp(Psi, AP);
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AP = AP-Src;
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std::cout << GridLogMessage <<"\t True residual is " << std::sqrt(norm2(AP)/norm2(Src)) <<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 << "\tInnerProd " << sliceInnerTimer.Elapsed() <<std::endl;
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std::cout << GridLogMessage << "\tMaddMatrix " << sliceMaddTimer.Elapsed() <<std::endl;
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IterationsToComplete = k;
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return;
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}
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}
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std::cout << GridLogMessage << "BlockConjugateGradient did NOT converge" << std::endl;
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if (ErrorOnNoConverge) assert(0);
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IterationsToComplete = k;
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}
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//////////////////////////////////////////////////////////////////////////
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// multiRHS conjugate gradient. Dimension zero should be the block direction
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// Use this for spread out across nodes
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//////////////////////////////////////////////////////////////////////////
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void CGmultiRHSsolve(LinearOperatorBase<Field> &Linop, const Field &Src, Field &Psi)
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{
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int Orthog = blockDim; // First dimension is block dim
|
|
Nblock = Src._grid->_fdimensions[Orthog];
|
|
|
|
std::cout<<GridLogMessage<<"MultiRHS Conjugate Gradient : Orthog "<<Orthog<<" Nblock "<<Nblock<<std::endl;
|
|
|
|
Psi.checkerboard = Src.checkerboard;
|
|
conformable(Psi, Src);
|
|
|
|
Field P(Src);
|
|
Field AP(Src);
|
|
Field R(Src);
|
|
|
|
std::vector<ComplexD> v_pAp(Nblock);
|
|
std::vector<RealD> v_rr (Nblock);
|
|
std::vector<RealD> v_rr_inv(Nblock);
|
|
std::vector<RealD> v_alpha(Nblock);
|
|
std::vector<RealD> v_beta(Nblock);
|
|
|
|
// Initial residual computation & set up
|
|
std::vector<RealD> residuals(Nblock);
|
|
std::vector<RealD> ssq(Nblock);
|
|
|
|
sliceNorm(ssq,Src,Orthog);
|
|
RealD sssum=0;
|
|
for(int b=0;b<Nblock;b++) sssum+=ssq[b];
|
|
|
|
sliceNorm(residuals,Src,Orthog);
|
|
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
|
|
|
|
sliceNorm(residuals,Psi,Orthog);
|
|
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
|
|
|
|
// Initial search dir is guess
|
|
Linop.HermOp(Psi, AP);
|
|
|
|
R = Src - AP;
|
|
P = R;
|
|
sliceNorm(v_rr,R,Orthog);
|
|
|
|
GridStopWatch sliceInnerTimer;
|
|
GridStopWatch sliceMaddTimer;
|
|
GridStopWatch sliceNormTimer;
|
|
GridStopWatch MatrixTimer;
|
|
GridStopWatch SolverTimer;
|
|
|
|
SolverTimer.Start();
|
|
int k;
|
|
for (k = 1; k <= MaxIterations; k++) {
|
|
|
|
RealD rrsum=0;
|
|
for(int b=0;b<Nblock;b++) rrsum+=real(v_rr[b]);
|
|
|
|
std::cout << GridLogIterative << "\titeration "<<k<<" rr_sum "<<rrsum<<" ssq_sum "<< sssum
|
|
<<" / "<<std::sqrt(rrsum/sssum) <<std::endl;
|
|
|
|
MatrixTimer.Start();
|
|
Linop.HermOp(P, AP);
|
|
MatrixTimer.Stop();
|
|
|
|
// Alpha
|
|
sliceInnerTimer.Start();
|
|
sliceInnerProductVector(v_pAp,P,AP,Orthog);
|
|
sliceInnerTimer.Stop();
|
|
for(int b=0;b<Nblock;b++){
|
|
v_alpha[b] = v_rr[b]/real(v_pAp[b]);
|
|
}
|
|
|
|
// Psi, R update
|
|
sliceMaddTimer.Start();
|
|
sliceMaddVector(Psi,v_alpha, P,Psi,Orthog); // add alpha * P to psi
|
|
sliceMaddVector(R ,v_alpha,AP, R,Orthog,-1.0);// sub alpha * AP to resid
|
|
sliceMaddTimer.Stop();
|
|
|
|
// Beta
|
|
for(int b=0;b<Nblock;b++){
|
|
v_rr_inv[b] = 1.0/v_rr[b];
|
|
}
|
|
sliceNormTimer.Start();
|
|
sliceNorm(v_rr,R,Orthog);
|
|
sliceNormTimer.Stop();
|
|
for(int b=0;b<Nblock;b++){
|
|
v_beta[b] = v_rr_inv[b] *v_rr[b];
|
|
}
|
|
|
|
// Search update
|
|
sliceMaddTimer.Start();
|
|
sliceMaddVector(P,v_beta,P,R,Orthog);
|
|
sliceMaddTimer.Stop();
|
|
|
|
/*********************
|
|
* convergence monitor
|
|
*********************
|
|
*/
|
|
RealD max_resid=0;
|
|
for(int b=0;b<Nblock;b++){
|
|
RealD rr = v_rr[b]/ssq[b];
|
|
if ( rr > max_resid ) max_resid = rr;
|
|
}
|
|
|
|
if ( max_resid < Tolerance*Tolerance ) {
|
|
|
|
SolverTimer.Stop();
|
|
|
|
std::cout << GridLogMessage<<"MultiRHS solver converged in " <<k<<" iterations"<<std::endl;
|
|
for(int b=0;b<Nblock;b++){
|
|
std::cout << GridLogMessage<< "\t\tBlock "<<b<<" computed resid "<< std::sqrt(v_rr[b]/ssq[b])<<std::endl;
|
|
}
|
|
std::cout << GridLogMessage<<"\tMax residual is "<<std::sqrt(max_resid)<<std::endl;
|
|
|
|
Linop.HermOp(Psi, AP);
|
|
AP = AP-Src;
|
|
std::cout <<GridLogMessage << "\tTrue residual is " << std::sqrt(norm2(AP)/norm2(Src)) <<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 << "\tInnerProd " << sliceInnerTimer.Elapsed() <<std::endl;
|
|
std::cout << GridLogMessage << "\tNorm " << sliceNormTimer.Elapsed() <<std::endl;
|
|
std::cout << GridLogMessage << "\tMaddMatrix " << sliceMaddTimer.Elapsed() <<std::endl;
|
|
|
|
|
|
IterationsToComplete = k;
|
|
return;
|
|
}
|
|
|
|
}
|
|
std::cout << GridLogMessage << "MultiRHSConjugateGradient did NOT converge" << std::endl;
|
|
|
|
if (ErrorOnNoConverge) assert(0);
|
|
IterationsToComplete = k;
|
|
}
|
|
|
|
};
|
|
|
|
}
|
|
#endif
|