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WilsonMG: Move tests for Wilson & WilsonClover into the same file
This commit is contained in:
Daniel Richtmann
parent
bbe1d5b49e
commit
3c3ec4e267
@ -1,614 +0,0 @@
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/*************************************************************************************
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Grid physics library, www.github.com/paboyle/Grid
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Source file: ./tests/solver/Test_wilson_mg.cc
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Copyright (C) 2017
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Author: Daniel Richtmann <daniel.richtmann@ur.de>
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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 directory
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*************************************************************************************/
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/* END LEGAL */
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#include <Grid/Grid.h>
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#include <Grid/algorithms/iterative/PrecGeneralisedConjugateResidual.h>
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using namespace std;
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using namespace Grid;
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using namespace Grid::QCD;
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template<class Field, int nbasis> class TestVectorAnalyzer {
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public:
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void operator()(LinearOperatorBase<Field> &Linop, std::vector<Field> const &vectors, int nn = nbasis) {
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auto positiveOnes = 0;
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std::vector<Field> tmp(4, vectors[0]._grid);
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Gamma g5(Gamma::Algebra::Gamma5);
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std::cout << GridLogMessage << "Test vector analysis:" << std::endl;
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for(auto i = 0; i < nn; ++i) {
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Linop.Op(vectors[i], tmp[3]);
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tmp[0] = g5 * tmp[3];
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auto lambda = innerProduct(vectors[i], tmp[0]) / innerProduct(vectors[i], vectors[i]);
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tmp[1] = tmp[0] - lambda * vectors[i];
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auto mu = ::sqrt(norm2(tmp[1]) / norm2(vectors[i]));
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auto nrm = ::sqrt(norm2(vectors[i]));
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if(real(lambda) > 0)
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positiveOnes++;
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std::cout << GridLogMessage << std::scientific << std::setprecision(2) << std::setw(2) << std::showpos << "vector " << i << ": "
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<< "singular value: " << lambda << ", singular vector precision: " << mu << ", norm: " << nrm << std::endl;
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}
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std::cout << GridLogMessage << std::scientific << std::setprecision(2) << std::setw(2) << std::showpos << positiveOnes << " out of "
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<< nn << " vectors were positive" << std::endl;
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}
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};
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// clang-format off
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struct MultigridParams : Serializable {
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public:
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GRID_SERIALIZABLE_CLASS_MEMBERS(MultigridParams,
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int, nLevels,
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std::vector<std::vector<int>>, blockSizes);
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MultigridParams(){};
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};
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MultigridParams mgParams;
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// clang-format on
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struct LevelInfo {
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public:
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std::vector<std::vector<int>> Seeds;
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std::vector<GridCartesian *> Grids;
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std::vector<GridParallelRNG> PRNGs;
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LevelInfo(GridCartesian *FineGrid, MultigridParams const &Params) {
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auto nCoarseLevels = Params.blockSizes.size();
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assert(nCoarseLevels == Params.nLevels - 1);
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// set up values for finest grid
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Grids.push_back(FineGrid);
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Seeds.push_back({1, 2, 3, 4});
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PRNGs.push_back(GridParallelRNG(Grids.back()));
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PRNGs.back().SeedFixedIntegers(Seeds.back());
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// set up values for coarser grids
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for(int level = 1; level < Params.nLevels; ++level) {
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auto Nd = Grids[level - 1]->_ndimension;
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auto tmp = Grids[level - 1]->_fdimensions;
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assert(tmp.size() == Nd);
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Seeds.push_back(std::vector<int>(Nd));
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for(int d = 0; d < Nd; ++d) {
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tmp[d] /= Params.blockSizes[level - 1][d];
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Seeds[level][d] = (level)*Nd + d + 1;
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}
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Grids.push_back(SpaceTimeGrid::makeFourDimGrid(tmp, GridDefaultSimd(Nd, vComplex::Nsimd()), GridDefaultMpi()));
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PRNGs.push_back(GridParallelRNG(Grids[level]));
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PRNGs[level].SeedFixedIntegers(Seeds[level]);
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}
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std::cout << GridLogMessage << "Constructed " << Params.nLevels << " levels" << std::endl;
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// The construction above corresponds to the finest level having level == 0
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// (simply because it's not as ugly to implement), but we need it the
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// other way round (i.e., the coarsest level to have level == 0) for the MG
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// Preconditioner -> reverse the vectors
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std::reverse(Seeds.begin(), Seeds.end());
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std::reverse(Grids.begin(), Grids.end());
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std::reverse(PRNGs.begin(), PRNGs.end());
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for(int level = 0; level < Params.nLevels; ++level) {
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std::cout << GridLogMessage << "level = " << level << ":" << std::endl;
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Grids[level]->show_decomposition();
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}
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}
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};
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template<class Field> void testLinearOperator(LinearOperatorBase<Field> &LinOp, GridBase *Grid, std::string const &name = "") {
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std::vector<int> seeds({1, 2, 3, 4});
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GridParallelRNG RNG(Grid);
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RNG.SeedFixedIntegers(seeds);
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{
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std::cout << GridLogMessage << "Testing that Mdiag + Σ_μ Mdir_μ == M for operator " << name << ":" << std::endl;
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// clang-format off
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Field src(Grid); random(RNG, src);
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Field ref(Grid); ref = zero;
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Field result(Grid); result = zero;
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Field diag(Grid); diag = zero;
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Field sumDir(Grid); sumDir = zero;
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Field tmp(Grid);
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Field err(Grid);
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// clang-format on
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std::cout << setprecision(9);
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std::cout << GridLogMessage << " norm2(src)\t\t\t\t= " << norm2(src) << std::endl;
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LinOp.OpDiag(src, diag);
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std::cout << GridLogMessage << " norm2(Mdiag * src)\t\t\t= " << norm2(diag) << std::endl;
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for(int dir = 0; dir < 4; dir++) {
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for(auto disp : {+1, -1}) {
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LinOp.OpDir(src, tmp, dir, disp);
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std::cout << GridLogMessage << " norm2(Mdir_{" << dir << "," << disp << "} * src)\t\t= " << norm2(tmp) << std::endl;
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sumDir = sumDir + tmp;
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}
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}
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std::cout << GridLogMessage << " norm2(Σ_μ Mdir_μ * src)\t\t= " << norm2(sumDir) << std::endl;
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result = diag + sumDir;
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std::cout << GridLogMessage << " norm2((Mdiag + Σ_μ Mdir_μ) * src)\t= " << norm2(result) << std::endl;
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LinOp.Op(src, ref);
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std::cout << GridLogMessage << " norm2(M * src)\t\t\t= " << norm2(ref) << std::endl;
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err = ref - result;
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std::cout << GridLogMessage << " Absolute deviation\t\t\t= " << norm2(err) << std::endl;
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std::cout << GridLogMessage << " Relative deviation\t\t\t= " << norm2(err) / norm2(ref) << std::endl;
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}
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{
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std::cout << GridLogMessage << "Testing hermiticity stochastically for operator " << name << ":" << std::endl;
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// clang-format off
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Field phi(Grid); random(RNG, phi);
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Field chi(Grid); random(RNG, chi);
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Field MPhi(Grid);
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Field MdagChi(Grid);
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// clang-format on
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LinOp.Op(phi, MPhi);
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LinOp.AdjOp(chi, MdagChi);
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ComplexD chiMPhi = innerProduct(chi, MPhi);
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ComplexD phiMdagChi = innerProduct(phi, MdagChi);
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ComplexD phiMPhi = innerProduct(phi, MPhi);
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ComplexD chiMdagChi = innerProduct(chi, MdagChi);
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std::cout << GridLogMessage << " chiMPhi = " << chiMPhi << " phiMdagChi = " << phiMdagChi
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<< " difference = " << chiMPhi - conjugate(phiMdagChi) << std::endl;
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std::cout << GridLogMessage << " phiMPhi = " << phiMPhi << " chiMdagChi = " << chiMdagChi << " <- should be real if hermitian"
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<< std::endl;
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}
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{
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std::cout << GridLogMessage << "Testing linearity for operator " << name << ":" << std::endl;
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// clang-format off
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Field phi(Grid); random(RNG, phi);
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Field chi(Grid); random(RNG, chi);
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Field phiPlusChi(Grid);
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Field MPhi(Grid);
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Field MChi(Grid);
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Field MPhiPlusChi(Grid);
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Field linearityError(Grid);
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// clang-format on
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LinOp.Op(phi, MPhi);
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LinOp.Op(chi, MChi);
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phiPlusChi = phi + chi;
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LinOp.Op(phiPlusChi, MPhiPlusChi);
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linearityError = MPhiPlusChi - MPhi;
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linearityError = linearityError - MChi;
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std::cout << GridLogMessage << " norm2(linearityError) = " << norm2(linearityError) << std::endl;
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}
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}
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template<class Fobj, class CoarseScalar, int nCoarseSpins, int nBasis, int level, class Matrix>
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class MultiGridPreconditioner : public LinearFunction<Lattice<Fobj>> {
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public:
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/////////////////////////////////////////////
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// Type Definitions
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/////////////////////////////////////////////
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typedef Aggregation<Fobj, CoarseScalar, nBasis> Aggregates;
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typedef CoarsenedMatrix<Fobj, CoarseScalar, nBasis> CoarseMatrix;
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typedef typename Aggregates::CoarseVector CoarseVector;
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typedef typename Aggregates::siteVector CoarseSiteVector;
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typedef Matrix FineMatrix;
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typedef typename Aggregates::FineField FineVector;
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typedef MultiGridPreconditioner<CoarseSiteVector, CoarseScalar, nCoarseSpins, nBasis, level - 1, CoarseMatrix> NextPreconditionerLevel;
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/////////////////////////////////////////////
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// Member Data
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/////////////////////////////////////////////
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LevelInfo & _LevelInfo;
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FineMatrix & _FineMatrix;
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FineMatrix & _SmootherMatrix;
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Aggregates _Aggregates;
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CoarseMatrix _CoarseMatrix;
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std::unique_ptr<NextPreconditionerLevel> _NextPreconditionerLevel;
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/////////////////////////////////////////////
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// Member Functions
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/////////////////////////////////////////////
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MultiGridPreconditioner(LevelInfo &LvlInfo, FineMatrix &FineMat, FineMatrix &SmootherMat)
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: _LevelInfo(LvlInfo)
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, _FineMatrix(FineMat)
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, _SmootherMatrix(SmootherMat)
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, _Aggregates(_LevelInfo.Grids[level - 1], _LevelInfo.Grids[level], 0)
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, _CoarseMatrix(*_LevelInfo.Grids[level - 1]) {
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_NextPreconditionerLevel = std::unique_ptr<NextPreconditionerLevel>(
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new NextPreconditionerLevel(_LevelInfo, _CoarseMatrix, _CoarseMatrix));
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}
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void setup() {
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Gamma g5(Gamma::Algebra::Gamma5);
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MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
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_Aggregates.CreateSubspace(_LevelInfo.PRNGs[level], fineMdagMOp /*, nb */); // NOTE: Don't specify nb to see the orthogonalization check
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// TestVectorAnalyzer<FineVector, nbasis> fineTVA;
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// fineTVA(fineMdagMOp, _Aggregates.subspace);
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static_assert((nBasis & 0x1) == 0, "MG Preconditioner only supports an even number of basis vectors");
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int nb = nBasis / 2;
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for(
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int n = 0; n < nb;
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n++) { // TODO: to get this to work for more than two levels, I would need to either implement coarse spins or have a template specialization of this class also for the finest level
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_Aggregates.subspace[n + nb] = g5 * _Aggregates.subspace[n];
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}
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_CoarseMatrix.CoarsenOperator(_LevelInfo.Grids[level], fineMdagMOp, _Aggregates);
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_NextPreconditionerLevel->setup();
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}
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virtual void operator()(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
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// TODO: implement a W-cycle and a toggle to switch between the cycling strategies
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vCycle(in, out);
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// kCycle(in, out);
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}
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void vCycle(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
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RealD inputNorm = norm2(in);
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CoarseVector coarseSrc(_LevelInfo.Grids[level - 1]);
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CoarseVector coarseSol(_LevelInfo.Grids[level - 1]);
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coarseSol = zero;
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FineVector fineTmp(in._grid);
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TrivialPrecon<FineVector> fineTrivialPreconditioner;
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FlexibleGeneralisedMinimalResidual<FineVector> fineFGMRES(1.0e-14, 1, fineTrivialPreconditioner, 1, false);
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MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
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MdagMLinearOperator<FineMatrix, FineVector> fineSmootherMdagMOp(_SmootherMatrix);
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_Aggregates.ProjectToSubspace(coarseSrc, in);
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(*_NextPreconditionerLevel)(coarseSrc, coarseSol);
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_Aggregates.PromoteFromSubspace(coarseSol, out);
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fineMdagMOp.Op(out, fineTmp);
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fineTmp = in - fineTmp;
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auto r = norm2(fineTmp);
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auto residualAfterCoarseGridCorrection = std::sqrt(r / inputNorm);
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fineFGMRES(fineSmootherMdagMOp, in, out);
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fineMdagMOp.Op(out, fineTmp);
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fineTmp = in - fineTmp;
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r = norm2(fineTmp);
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auto residualAfterPostSmoother = std::sqrt(r / inputNorm);
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std::cout << GridLogMG << " Level " << level << ": Input norm = " << std::sqrt(inputNorm)
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<< " Coarse residual = " << residualAfterCoarseGridCorrection << " Post-Smoother residual = " << residualAfterPostSmoother
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<< std::endl;
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}
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void kCycle(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
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RealD inputNorm = norm2(in);
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CoarseVector coarseSrc(_LevelInfo.Grids[level - 1]);
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CoarseVector coarseSol(_LevelInfo.Grids[level - 1]);
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coarseSol = zero;
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FineVector fineTmp(in._grid);
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TrivialPrecon<FineVector> fineTrivialPreconditioner;
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FlexibleGeneralisedMinimalResidual<FineVector> fineFGMRES(1.0e-14, 1, fineTrivialPreconditioner, 1, false);
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FlexibleGeneralisedMinimalResidual<CoarseVector> coarseFGMRES(1.0e-14, 1, *_NextPreconditionerLevel, 1, false);
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MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
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MdagMLinearOperator<FineMatrix, FineVector> fineSmootherMdagMOp(_SmootherMatrix);
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MdagMLinearOperator<CoarseMatrix, CoarseVector> coarseMdagMOp(_CoarseMatrix);
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_Aggregates.ProjectToSubspace(coarseSrc, in);
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coarseFGMRES(coarseMdagMOp, coarseSrc, coarseSol);
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_Aggregates.PromoteFromSubspace(coarseSol, out);
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fineMdagMOp.Op(out, fineTmp);
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fineTmp = in - fineTmp;
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auto r = norm2(fineTmp);
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auto residualAfterCoarseGridCorrection = std::sqrt(r / inputNorm);
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fineFGMRES(fineSmootherMdagMOp, in, out);
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fineMdagMOp.Op(out, fineTmp);
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fineTmp = in - fineTmp;
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r = norm2(fineTmp);
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auto residualAfterPostSmoother = std::sqrt(r / inputNorm);
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std::cout << GridLogMG << " Level " << level << ": Input norm = " << std::sqrt(inputNorm)
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<< " Coarse residual = " << residualAfterCoarseGridCorrection << " Post-Smoother residual = " << residualAfterPostSmoother
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<< std::endl;
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}
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void runChecks() {
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auto tolerance = 1e-13; // TODO: this obviously depends on the precision we use, current value is for double
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auto coarseLevel = level - 1;
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std::vector<FineVector> fineTmps(2, _LevelInfo.Grids[level]);
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std::vector<CoarseVector> coarseTmps(4, _LevelInfo.Grids[level - 1]);
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MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
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MdagMLinearOperator<CoarseMatrix, CoarseVector> coarseMdagMOp(_CoarseMatrix);
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std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
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std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == (1 - P R) v" << std::endl;
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std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
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for(auto i = 0; i < _Aggregates.subspace.size(); ++i) {
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_Aggregates.ProjectToSubspace(coarseTmps[0], _Aggregates.subspace[i]); // R v_i
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_Aggregates.PromoteFromSubspace(coarseTmps[0], fineTmps[0]); // P R v_i
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fineTmps[1] = _Aggregates.subspace[i] - fineTmps[0]; // v_i - P R v_i
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auto deviation = std::sqrt(norm2(fineTmps[1]) / norm2(_Aggregates.subspace[i]));
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std::cout << GridLogMG << " Level " << level << ": Vector " << i << ": norm2(v_i) = " << norm2(_Aggregates.subspace[i])
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<< " | norm2(R v_i) = " << norm2(coarseTmps[0]) << " | norm2(P R v_i) = " << norm2(fineTmps[0])
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<< " | relative deviation = " << deviation;
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if(deviation > tolerance) {
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std::cout << " > " << tolerance << " -> check failed" << std::endl;
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// abort();
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} else {
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std::cout << " < " << tolerance << " -> check passed" << std::endl;
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}
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}
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std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
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std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == (1 - R P) v_c" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
|
||||
random(_LevelInfo.PRNGs[coarseLevel], coarseTmps[0]);
|
||||
|
||||
_Aggregates.PromoteFromSubspace(coarseTmps[0], fineTmps[0]); // P v_c
|
||||
_Aggregates.ProjectToSubspace(coarseTmps[1], fineTmps[0]); // R P v_c
|
||||
|
||||
coarseTmps[2] = coarseTmps[0] - coarseTmps[1]; // v_c - R P v_c
|
||||
auto deviation = std::sqrt(norm2(coarseTmps[2]) / norm2(coarseTmps[0]));
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": norm2(v_c) = " << norm2(coarseTmps[0])
|
||||
<< " | norm2(R P v_c) = " << norm2(coarseTmps[1]) << " | norm2(P v_c) = " << norm2(fineTmps[0])
|
||||
<< " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
std::cout << " > " << tolerance << " -> check failed" << std::endl;
|
||||
// abort();
|
||||
} else {
|
||||
std::cout << " < " << tolerance << " -> check passed" << std::endl;
|
||||
}
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == (R D P - D_c) v_c" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
|
||||
random(_LevelInfo.PRNGs[coarseLevel], coarseTmps[0]);
|
||||
|
||||
_Aggregates.PromoteFromSubspace(coarseTmps[0], fineTmps[0]); // P v_c
|
||||
fineMdagMOp.Op(fineTmps[0], fineTmps[1]); // D P v_c
|
||||
_Aggregates.ProjectToSubspace(coarseTmps[1], fineTmps[1]); // R D P v_c
|
||||
|
||||
coarseMdagMOp.Op(coarseTmps[0], coarseTmps[2]); // D_c v_c
|
||||
|
||||
coarseTmps[3] = coarseTmps[1] - coarseTmps[2]; // R D P v_c - D_c v_c
|
||||
deviation = std::sqrt(norm2(coarseTmps[3]) / norm2(coarseTmps[1]));
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": norm2(R D P v_c) = " << norm2(coarseTmps[1])
|
||||
<< " | norm2(D_c v_c) = " << norm2(coarseTmps[2]) << " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
std::cout << " > " << tolerance << " -> check failed" << std::endl;
|
||||
// abort();
|
||||
} else {
|
||||
std::cout << " < " << tolerance << " -> check passed" << std::endl;
|
||||
}
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == |(Im(v_c^dag D_c^dag D_c v_c)|" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
|
||||
random(_LevelInfo.PRNGs[coarseLevel], coarseTmps[0]);
|
||||
|
||||
coarseMdagMOp.Op(coarseTmps[0], coarseTmps[1]); // D_c v_c
|
||||
coarseMdagMOp.AdjOp(coarseTmps[1], coarseTmps[2]); // D_c^dag D_c v_c
|
||||
|
||||
auto dot = innerProduct(coarseTmps[0], coarseTmps[2]); //v_c^dag D_c^dag D_c v_c
|
||||
deviation = abs(imag(dot)) / abs(real(dot));
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": Re(v_c^dag D_c^dag D_c v_c) = " << real(dot)
|
||||
<< " | Im(v_c^dag D_c^dag D_c v_c) = " << imag(dot) << " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
std::cout << " > " << tolerance << " -> check failed" << std::endl;
|
||||
// abort();
|
||||
} else {
|
||||
std::cout << " < " << tolerance << " -> check passed"
|
||||
<< std::endl; // TODO: this check will work only when I got Mdag in CoarsenedMatrix to work
|
||||
}
|
||||
|
||||
_NextPreconditionerLevel->runChecks();
|
||||
}
|
||||
};
|
||||
|
||||
// Specialize the coarsest level, this corresponds to counting downwards with level: coarsest = 0, finest = N
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
class MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 0, Matrix> : public LinearFunction<Lattice<Fobj>> {
|
||||
public:
|
||||
/////////////////////////////////////////////
|
||||
// Type Definitions
|
||||
/////////////////////////////////////////////
|
||||
|
||||
typedef Matrix FineMatrix;
|
||||
typedef Lattice<Fobj> FineVector;
|
||||
|
||||
/////////////////////////////////////////////
|
||||
// Member Data
|
||||
/////////////////////////////////////////////
|
||||
|
||||
LevelInfo & _LevelInfo;
|
||||
FineMatrix &_FineMatrix;
|
||||
FineMatrix &_SmootherMatrix;
|
||||
|
||||
/////////////////////////////////////////////
|
||||
// Member Functions
|
||||
/////////////////////////////////////////////
|
||||
|
||||
MultiGridPreconditioner(LevelInfo &LvlInfo, FineMatrix &FineMat, FineMatrix &SmootherMat)
|
||||
: _LevelInfo(LvlInfo), _FineMatrix(FineMat), _SmootherMatrix(SmootherMat) {}
|
||||
|
||||
void setup() {}
|
||||
|
||||
virtual void operator()(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
|
||||
|
||||
TrivialPrecon<FineVector> fineTrivialPreconditioner;
|
||||
FlexibleGeneralisedMinimalResidual<FineVector> fineFGMRES(1.0e-14, 1, fineTrivialPreconditioner, 1, false);
|
||||
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
|
||||
|
||||
fineFGMRES(fineMdagMOp, in, out);
|
||||
}
|
||||
|
||||
void runChecks() {}
|
||||
};
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
using FourLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 4 - 1, Matrix>;
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
using ThreeLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 3 - 1, Matrix>;
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
using TwoLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 2 - 1, Matrix>;
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, int nlevel, class Matrix>
|
||||
using NLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, nlevel - 1, Matrix>;
|
||||
|
||||
int main(int argc, char **argv) {
|
||||
|
||||
Grid_init(&argc, &argv);
|
||||
|
||||
GridCartesian *FGrid = SpaceTimeGrid::makeFourDimGrid(GridDefaultLatt(), GridDefaultSimd(Nd, vComplex::Nsimd()), GridDefaultMpi());
|
||||
GridRedBlackCartesian *FrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(FGrid);
|
||||
|
||||
std::vector<int> fSeeds({1, 2, 3, 4});
|
||||
GridParallelRNG fPRNG(FGrid);
|
||||
fPRNG.SeedFixedIntegers(fSeeds);
|
||||
|
||||
Gamma g5(Gamma::Algebra::Gamma5);
|
||||
|
||||
// clang-format off
|
||||
LatticeFermion src(FGrid); gaussian(fPRNG, src);
|
||||
LatticeFermion result(FGrid); result = zero;
|
||||
LatticeGaugeField Umu(FGrid); SU3::HotConfiguration(fPRNG, Umu);
|
||||
// clang-format on
|
||||
|
||||
RealD mass = 0.5;
|
||||
const int nbasis = 20;
|
||||
|
||||
WilsonFermionR Dw(Umu, *FGrid, *FrbGrid, mass);
|
||||
|
||||
// mgParams.blockSizes = {{2, 2, 2, 2}, {2, 2, 1, 1}, {1, 1, 2, 1}};
|
||||
// mgParams.blockSizes = {{2, 2, 2, 2}, {2, 2, 1, 1}};
|
||||
mgParams.blockSizes = {{2, 2, 2, 2}};
|
||||
mgParams.nLevels = mgParams.blockSizes.size() + 1;
|
||||
|
||||
std::cout << mgParams << std::endl;
|
||||
|
||||
LevelInfo levelInfo(FGrid, mgParams);
|
||||
|
||||
MdagMLinearOperator<WilsonFermionR, LatticeFermion> FineMdagMOp(Dw);
|
||||
|
||||
TrivialPrecon<LatticeFermion> TrivialPrecon;
|
||||
TwoLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonFermionR> TwoLevelMGPrecon(levelInfo, Dw, Dw);
|
||||
// ThreeLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonFermionR> ThreeLevelMGPrecon(levelInfo, Dw, Dw);
|
||||
// FourLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonFermionR> FourLevelMGPrecon(levelInfo, Dw, Dw);
|
||||
// NLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, 4, WilsonFermionR> FourLevelMGPrecon(levelInfo, Dw, Dw);
|
||||
|
||||
TwoLevelMGPrecon.setup();
|
||||
TwoLevelMGPrecon.runChecks();
|
||||
|
||||
// ThreeLevelMGPrecon.setup();
|
||||
// ThreeLevelMGPrecon.runChecks();
|
||||
|
||||
// FourLevelMGPrecon.setup();
|
||||
// FourLevelMGPrecon.runChecks();
|
||||
|
||||
// NLevelMGPrecon.setup();
|
||||
// NLevelMGPrecon.runChecks();
|
||||
|
||||
std::vector<std::unique_ptr<OperatorFunction<LatticeFermion>>> solvers;
|
||||
|
||||
solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, TrivialPrecon, 1000, false));
|
||||
solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, TwoLevelMGPrecon, 1000, false));
|
||||
// solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, ThreeLevelMGPrecon, 1000, false));
|
||||
// solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, FourLevelMGPrecon, 1000, false));
|
||||
// solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, NLevelMGPrecon, 1000, false));
|
||||
|
||||
for(auto const &solver : solvers) {
|
||||
std::cout << "Starting with a new solver" << std::endl;
|
||||
result = zero;
|
||||
(*solver)(FineMdagMOp, src, result);
|
||||
std::cout << std::endl;
|
||||
}
|
||||
|
||||
Grid_finalize();
|
||||
}
|
||||
@ -69,55 +69,68 @@ public:
|
||||
}
|
||||
};
|
||||
|
||||
class myclass : Serializable {
|
||||
// clang-format off
|
||||
struct MultigridParams : Serializable {
|
||||
public:
|
||||
// clang-format off
|
||||
GRID_SERIALIZABLE_CLASS_MEMBERS(myclass,
|
||||
int, domaindecompose,
|
||||
int, domainsize,
|
||||
int, coarsegrids,
|
||||
int, order,
|
||||
int, Ls,
|
||||
double, mq,
|
||||
double, lo,
|
||||
double, hi,
|
||||
int, steps);
|
||||
// clang-format on
|
||||
myclass(){};
|
||||
GRID_SERIALIZABLE_CLASS_MEMBERS(MultigridParams,
|
||||
int, nLevels,
|
||||
std::vector<std::vector<int>>, blockSizes);
|
||||
MultigridParams(){};
|
||||
};
|
||||
myclass params;
|
||||
MultigridParams mgParams;
|
||||
// clang-format on
|
||||
|
||||
template<int nbasis> struct CoarseGrids {
|
||||
struct LevelInfo {
|
||||
public:
|
||||
std::vector<std::vector<int>> LattSizes;
|
||||
std::vector<std::vector<int>> Seeds;
|
||||
std::vector<GridCartesian *> Grids;
|
||||
std::vector<GridParallelRNG> PRNGs;
|
||||
|
||||
CoarseGrids(std::vector<std::vector<int>> const &blockSizes, int coarsegrids) {
|
||||
LevelInfo(GridCartesian *FineGrid, MultigridParams const &Params) {
|
||||
|
||||
assert(blockSizes.size() == coarsegrids);
|
||||
auto nCoarseLevels = Params.blockSizes.size();
|
||||
|
||||
std::cout << GridLogMessage << "Constructing " << coarsegrids << " CoarseGrids" << std::endl;
|
||||
assert(nCoarseLevels == Params.nLevels - 1);
|
||||
|
||||
for(int cl = 0; cl < coarsegrids; ++cl) { // may be a bit ugly and slow but not perf critical
|
||||
// need to differentiate between first and other coarse levels in size calculation
|
||||
LattSizes.push_back({cl == 0 ? GridDefaultLatt() : LattSizes[cl - 1]});
|
||||
Seeds.push_back(std::vector<int>(LattSizes[cl].size()));
|
||||
// set up values for finest grid
|
||||
Grids.push_back(FineGrid);
|
||||
Seeds.push_back({1, 2, 3, 4});
|
||||
PRNGs.push_back(GridParallelRNG(Grids.back()));
|
||||
PRNGs.back().SeedFixedIntegers(Seeds.back());
|
||||
|
||||
for(int d = 0; d < LattSizes[cl].size(); ++d) {
|
||||
LattSizes[cl][d] = LattSizes[cl][d] / blockSizes[cl][d];
|
||||
Seeds[cl][d] = (cl + 1) * LattSizes[cl].size() + d + 1;
|
||||
// calculation unimportant, just to get. e.g., {5, 6, 7, 8} for first coarse level and so on
|
||||
// set up values for coarser grids
|
||||
for(int level = 1; level < Params.nLevels; ++level) {
|
||||
auto Nd = Grids[level - 1]->_ndimension;
|
||||
auto tmp = Grids[level - 1]->_fdimensions;
|
||||
assert(tmp.size() == Nd);
|
||||
|
||||
Seeds.push_back(std::vector<int>(Nd));
|
||||
|
||||
for(int d = 0; d < Nd; ++d) {
|
||||
tmp[d] /= Params.blockSizes[level - 1][d];
|
||||
Seeds[level][d] = (level)*Nd + d + 1;
|
||||
}
|
||||
|
||||
Grids.push_back(SpaceTimeGrid::makeFourDimGrid(LattSizes[cl], GridDefaultSimd(Nd, vComplex::Nsimd()), GridDefaultMpi()));
|
||||
PRNGs.push_back(GridParallelRNG(Grids[cl]));
|
||||
Grids.push_back(SpaceTimeGrid::makeFourDimGrid(tmp, GridDefaultSimd(Nd, vComplex::Nsimd()), GridDefaultMpi()));
|
||||
PRNGs.push_back(GridParallelRNG(Grids[level]));
|
||||
|
||||
PRNGs[cl].SeedFixedIntegers(Seeds[cl]);
|
||||
PRNGs[level].SeedFixedIntegers(Seeds[level]);
|
||||
}
|
||||
|
||||
std::cout << GridLogMessage << "cl = " << cl << ": LattSize = " << LattSizes[cl] << std::endl;
|
||||
std::cout << GridLogMessage << "cl = " << cl << ": Seeds = " << Seeds[cl] << std::endl;
|
||||
std::cout << GridLogMessage << "Constructed " << Params.nLevels << " levels" << std::endl;
|
||||
|
||||
// The construction above corresponds to the finest level having level == 0
|
||||
// (simply because it's not as ugly to implement), but we need it the
|
||||
// other way round (i.e., the coarsest level to have level == 0) for the MG
|
||||
// Preconditioner -> reverse the vectors
|
||||
|
||||
std::reverse(Seeds.begin(), Seeds.end());
|
||||
std::reverse(Grids.begin(), Grids.end());
|
||||
std::reverse(PRNGs.begin(), PRNGs.end());
|
||||
|
||||
for(int level = 0; level < Params.nLevels; ++level) {
|
||||
std::cout << GridLogMessage << "level = " << level << ":" << std::endl;
|
||||
Grids[level]->show_decomposition();
|
||||
}
|
||||
}
|
||||
};
|
||||
@ -221,116 +234,177 @@ template<class Field> void testLinearOperator(LinearOperatorBase<Field> &LinOp,
|
||||
}
|
||||
}
|
||||
|
||||
// template < class Fobj, class CComplex, int coarseSpins, int nbasis, class Matrix >
|
||||
// class MultiGridPreconditioner : public LinearFunction< Lattice< Fobj > > {
|
||||
template<class Fobj, class CComplex, int nbasis, class Matrix> class MultiGridPreconditioner : public LinearFunction<Lattice<Fobj>> {
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nBasis, int level, class Matrix>
|
||||
class MultiGridPreconditioner : public LinearFunction<Lattice<Fobj>> {
|
||||
public:
|
||||
typedef Aggregation<Fobj, CComplex, nbasis> Aggregates;
|
||||
typedef CoarsenedMatrix<Fobj, CComplex, nbasis> CoarseOperator;
|
||||
/////////////////////////////////////////////
|
||||
// Type Definitions
|
||||
/////////////////////////////////////////////
|
||||
|
||||
typedef typename Aggregation<Fobj, CComplex, nbasis>::siteVector siteVector;
|
||||
typedef typename Aggregation<Fobj, CComplex, nbasis>::CoarseScalar CoarseScalar;
|
||||
typedef typename Aggregation<Fobj, CComplex, nbasis>::CoarseVector CoarseVector;
|
||||
typedef typename Aggregation<Fobj, CComplex, nbasis>::CoarseMatrix CoarseMatrix;
|
||||
typedef typename Aggregation<Fobj, CComplex, nbasis>::FineField FineField;
|
||||
typedef LinearOperatorBase<FineField> FineOperator;
|
||||
typedef Aggregation<Fobj, CoarseScalar, nBasis> Aggregates;
|
||||
typedef CoarsenedMatrix<Fobj, CoarseScalar, nBasis> CoarseMatrix;
|
||||
typedef typename Aggregates::CoarseVector CoarseVector;
|
||||
typedef typename Aggregates::siteVector CoarseSiteVector;
|
||||
typedef Matrix FineMatrix;
|
||||
typedef typename Aggregates::FineField FineVector;
|
||||
typedef MultiGridPreconditioner<CoarseSiteVector, CoarseScalar, nCoarseSpins, nBasis, level - 1, CoarseMatrix> NextPreconditionerLevel;
|
||||
|
||||
Aggregates & _Aggregates;
|
||||
CoarseOperator &_CoarseOperator;
|
||||
Matrix & _FineMatrix;
|
||||
FineOperator & _FineOperator;
|
||||
Matrix & _SmootherMatrix;
|
||||
FineOperator & _SmootherOperator;
|
||||
/////////////////////////////////////////////
|
||||
// Member Data
|
||||
/////////////////////////////////////////////
|
||||
|
||||
// Constructor
|
||||
MultiGridPreconditioner(Aggregates & Agg,
|
||||
CoarseOperator &Coarse,
|
||||
FineOperator & Fine,
|
||||
Matrix & FineMatrix,
|
||||
FineOperator & Smooth,
|
||||
Matrix & SmootherMatrix)
|
||||
: _Aggregates(Agg)
|
||||
, _CoarseOperator(Coarse)
|
||||
, _FineOperator(Fine)
|
||||
, _FineMatrix(FineMatrix)
|
||||
, _SmootherOperator(Smooth)
|
||||
, _SmootherMatrix(SmootherMatrix) {}
|
||||
LevelInfo & _LevelInfo;
|
||||
FineMatrix & _FineMatrix;
|
||||
FineMatrix & _SmootherMatrix;
|
||||
Aggregates _Aggregates;
|
||||
CoarseMatrix _CoarseMatrix;
|
||||
std::unique_ptr<NextPreconditionerLevel> _NextPreconditionerLevel;
|
||||
|
||||
void operator()(const FineField &in, FineField &out) {
|
||||
/////////////////////////////////////////////
|
||||
// Member Functions
|
||||
/////////////////////////////////////////////
|
||||
|
||||
CoarseVector coarseSrc(_CoarseOperator.Grid());
|
||||
CoarseVector coarseTmp(_CoarseOperator.Grid());
|
||||
CoarseVector coarseSol(_CoarseOperator.Grid());
|
||||
coarseSol = zero;
|
||||
|
||||
GeneralisedMinimalResidual<CoarseVector> coarseGMRES(5.0e-2, 100, 25, false);
|
||||
GeneralisedMinimalResidual<FineField> fineGMRES(5.0e-2, 100, 25, false);
|
||||
|
||||
HermitianLinearOperator<CoarseOperator, CoarseVector> coarseHermOp(_CoarseOperator);
|
||||
MdagMLinearOperator<CoarseOperator, CoarseVector> coarseMdagMOp(_CoarseOperator);
|
||||
MdagMLinearOperator<Matrix, FineField> fineMdagMOp(_SmootherMatrix);
|
||||
|
||||
FineField fineTmp1(in._grid);
|
||||
FineField fineTmp2(in._grid);
|
||||
|
||||
RealD Ni = norm2(in);
|
||||
|
||||
// no pre smoothing for now
|
||||
auto preSmootherNorm = 0;
|
||||
auto preSmootherResidual = 0;
|
||||
RealD r;
|
||||
|
||||
// Project to coarse grid, solve, project back to fine grid
|
||||
_Aggregates.ProjectToSubspace(coarseSrc, in);
|
||||
coarseGMRES(coarseMdagMOp, coarseSrc, coarseSol);
|
||||
_Aggregates.PromoteFromSubspace(coarseSol, out);
|
||||
|
||||
// Recompute error
|
||||
_FineOperator.Op(out, fineTmp1);
|
||||
fineTmp1 = in - fineTmp1;
|
||||
r = norm2(fineTmp1);
|
||||
auto coarseResidual = std::sqrt(r / Ni);
|
||||
|
||||
// Apply smoother, use GMRES for the moment
|
||||
fineGMRES(fineMdagMOp, in, out);
|
||||
|
||||
// Recompute error
|
||||
_FineOperator.Op(out, fineTmp1);
|
||||
fineTmp1 = in - fineTmp1;
|
||||
r = norm2(fineTmp1);
|
||||
auto postSmootherResidual = std::sqrt(r / Ni);
|
||||
|
||||
std::cout << GridLogIterative << "Input norm = " << Ni << " Pre-Smoother norm " << preSmootherNorm
|
||||
<< " Pre-Smoother residual = " << preSmootherResidual << " Coarse residual = " << coarseResidual
|
||||
<< " Post-Smoother residual = " << postSmootherResidual << std::endl;
|
||||
MultiGridPreconditioner(LevelInfo &LvlInfo, FineMatrix &FineMat, FineMatrix &SmootherMat)
|
||||
: _LevelInfo(LvlInfo)
|
||||
, _FineMatrix(FineMat)
|
||||
, _SmootherMatrix(SmootherMat)
|
||||
, _Aggregates(_LevelInfo.Grids[level - 1], _LevelInfo.Grids[level], 0)
|
||||
, _CoarseMatrix(*_LevelInfo.Grids[level - 1]) {
|
||||
_NextPreconditionerLevel
|
||||
= std::unique_ptr<NextPreconditionerLevel>(new NextPreconditionerLevel(_LevelInfo, _CoarseMatrix, _CoarseMatrix));
|
||||
}
|
||||
|
||||
void runChecks(CoarseGrids<nbasis> &cGrids, int whichCoarseGrid) {
|
||||
void setup() {
|
||||
|
||||
/////////////////////////////////////////////
|
||||
// Some stuff we need for the checks below //
|
||||
/////////////////////////////////////////////
|
||||
auto tolerance = 1e-13; // TODO: this obviously depends on the precision we use, current value is for double
|
||||
Gamma g5(Gamma::Algebra::Gamma5);
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
|
||||
|
||||
std::vector<CoarseVector> cTmps(4, _CoarseOperator.Grid());
|
||||
std::vector<FineField> fTmps(2, _Aggregates.subspace[0]._grid); // atm only for one coarser grid
|
||||
_Aggregates.CreateSubspace(_LevelInfo.PRNGs[level], fineMdagMOp /*, nb */); // NOTE: Don't specify nb to see the orthogonalization check
|
||||
|
||||
// need to construct an operator, since _CoarseOperator is not a LinearOperator but only a matrix (the name is a bit misleading)
|
||||
MdagMLinearOperator<CoarseOperator, CoarseVector> MdagMOp(_CoarseOperator);
|
||||
// TestVectorAnalyzer<FineVector, nbasis> fineTVA;
|
||||
// fineTVA(fineMdagMOp, _Aggregates.subspace);
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "MG correctness check: 0 == (1 - P R) v" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
static_assert((nBasis & 0x1) == 0, "MG Preconditioner only supports an even number of basis vectors");
|
||||
int nb = nBasis / 2;
|
||||
|
||||
for(
|
||||
int n = 0; n < nb;
|
||||
n++) { // TODO: to get this to work for more than two levels, I would need to either implement coarse spins or have a template specialization of this class also for the finest level
|
||||
_Aggregates.subspace[n + nb] = g5 * _Aggregates.subspace[n];
|
||||
}
|
||||
|
||||
_CoarseMatrix.CoarsenOperator(_LevelInfo.Grids[level], fineMdagMOp, _Aggregates);
|
||||
|
||||
_NextPreconditionerLevel->setup();
|
||||
}
|
||||
|
||||
virtual void operator()(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
|
||||
|
||||
// TODO: implement a W-cycle and a toggle to switch between the cycling strategies
|
||||
vCycle(in, out);
|
||||
// kCycle(in, out);
|
||||
}
|
||||
|
||||
void vCycle(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
|
||||
|
||||
RealD inputNorm = norm2(in);
|
||||
|
||||
CoarseVector coarseSrc(_LevelInfo.Grids[level - 1]);
|
||||
CoarseVector coarseSol(_LevelInfo.Grids[level - 1]);
|
||||
coarseSol = zero;
|
||||
|
||||
FineVector fineTmp(in._grid);
|
||||
|
||||
TrivialPrecon<FineVector> fineTrivialPreconditioner;
|
||||
FlexibleGeneralisedMinimalResidual<FineVector> fineFGMRES(1.0e-14, 1, fineTrivialPreconditioner, 1, false);
|
||||
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineSmootherMdagMOp(_SmootherMatrix);
|
||||
|
||||
_Aggregates.ProjectToSubspace(coarseSrc, in);
|
||||
(*_NextPreconditionerLevel)(coarseSrc, coarseSol);
|
||||
_Aggregates.PromoteFromSubspace(coarseSol, out);
|
||||
|
||||
fineMdagMOp.Op(out, fineTmp);
|
||||
fineTmp = in - fineTmp;
|
||||
auto r = norm2(fineTmp);
|
||||
auto residualAfterCoarseGridCorrection = std::sqrt(r / inputNorm);
|
||||
|
||||
fineFGMRES(fineSmootherMdagMOp, in, out);
|
||||
|
||||
fineMdagMOp.Op(out, fineTmp);
|
||||
fineTmp = in - fineTmp;
|
||||
r = norm2(fineTmp);
|
||||
auto residualAfterPostSmoother = std::sqrt(r / inputNorm);
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": V-cycle: Input norm = " << std::sqrt(inputNorm)
|
||||
<< " Coarse residual = " << residualAfterCoarseGridCorrection << " Post-Smoother residual = " << residualAfterPostSmoother
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
void kCycle(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
|
||||
|
||||
RealD inputNorm = norm2(in);
|
||||
|
||||
CoarseVector coarseSrc(_LevelInfo.Grids[level - 1]);
|
||||
CoarseVector coarseSol(_LevelInfo.Grids[level - 1]);
|
||||
coarseSol = zero;
|
||||
|
||||
FineVector fineTmp(in._grid);
|
||||
|
||||
TrivialPrecon<FineVector> fineTrivialPreconditioner;
|
||||
FlexibleGeneralisedMinimalResidual<FineVector> fineFGMRES(1.0e-14, 1, fineTrivialPreconditioner, 1, false);
|
||||
FlexibleGeneralisedMinimalResidual<CoarseVector> coarseFGMRES(1.0e-14, 1, *_NextPreconditionerLevel, 1, false);
|
||||
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineSmootherMdagMOp(_SmootherMatrix);
|
||||
MdagMLinearOperator<CoarseMatrix, CoarseVector> coarseMdagMOp(_CoarseMatrix);
|
||||
|
||||
_Aggregates.ProjectToSubspace(coarseSrc, in);
|
||||
coarseFGMRES(coarseMdagMOp, coarseSrc, coarseSol);
|
||||
_Aggregates.PromoteFromSubspace(coarseSol, out);
|
||||
|
||||
fineMdagMOp.Op(out, fineTmp);
|
||||
fineTmp = in - fineTmp;
|
||||
auto r = norm2(fineTmp);
|
||||
auto residualAfterCoarseGridCorrection = std::sqrt(r / inputNorm);
|
||||
|
||||
fineFGMRES(fineSmootherMdagMOp, in, out);
|
||||
|
||||
fineMdagMOp.Op(out, fineTmp);
|
||||
fineTmp = in - fineTmp;
|
||||
r = norm2(fineTmp);
|
||||
auto residualAfterPostSmoother = std::sqrt(r / inputNorm);
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": K-cycle: Input norm = " << std::sqrt(inputNorm)
|
||||
<< " Coarse residual = " << residualAfterCoarseGridCorrection << " Post-Smoother residual = " << residualAfterPostSmoother
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
void runChecks() {
|
||||
|
||||
auto tolerance = 1e-13; // TODO: this obviously depends on the precision we use, current value is for double
|
||||
auto coarseLevel = level - 1;
|
||||
|
||||
std::vector<FineVector> fineTmps(2, _LevelInfo.Grids[level]);
|
||||
std::vector<CoarseVector> coarseTmps(4, _LevelInfo.Grids[level - 1]);
|
||||
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
|
||||
MdagMLinearOperator<CoarseMatrix, CoarseVector> coarseMdagMOp(_CoarseMatrix);
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == (1 - P R) v" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
|
||||
for(auto i = 0; i < _Aggregates.subspace.size(); ++i) {
|
||||
_Aggregates.ProjectToSubspace(cTmps[0], _Aggregates.subspace[i]); // R v_i
|
||||
_Aggregates.PromoteFromSubspace(cTmps[0], fTmps[0]); // P R v_i
|
||||
_Aggregates.ProjectToSubspace(coarseTmps[0], _Aggregates.subspace[i]); // R v_i
|
||||
_Aggregates.PromoteFromSubspace(coarseTmps[0], fineTmps[0]); // P R v_i
|
||||
|
||||
fTmps[1] = _Aggregates.subspace[i] - fTmps[0]; // v_i - P R v_i
|
||||
auto deviation = std::sqrt(norm2(fTmps[1]) / norm2(_Aggregates.subspace[i]));
|
||||
fineTmps[1] = _Aggregates.subspace[i] - fineTmps[0]; // v_i - P R v_i
|
||||
auto deviation = std::sqrt(norm2(fineTmps[1]) / norm2(_Aggregates.subspace[i]));
|
||||
|
||||
std::cout << GridLogMessage << "Vector " << i << ": norm2(v_i) = " << norm2(_Aggregates.subspace[i])
|
||||
<< " | norm2(R v_i) = " << norm2(cTmps[0]) << " | norm2(P R v_i) = " << norm2(fTmps[0])
|
||||
std::cout << GridLogMG << " Level " << level << ": Vector " << i << ": norm2(v_i) = " << norm2(_Aggregates.subspace[i])
|
||||
<< " | norm2(R v_i) = " << norm2(coarseTmps[0]) << " | norm2(P R v_i) = " << norm2(fineTmps[0])
|
||||
<< " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
@ -341,44 +415,20 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "MG correctness check: 0 == (1 - R P) v_c" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == (1 - R P) v_c" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
|
||||
random(cGrids.PRNGs[whichCoarseGrid], cTmps[0]);
|
||||
random(_LevelInfo.PRNGs[coarseLevel], coarseTmps[0]);
|
||||
|
||||
_Aggregates.PromoteFromSubspace(cTmps[0], fTmps[0]); // P v_c
|
||||
_Aggregates.ProjectToSubspace(cTmps[1], fTmps[0]); // R P v_c
|
||||
_Aggregates.PromoteFromSubspace(coarseTmps[0], fineTmps[0]); // P v_c
|
||||
_Aggregates.ProjectToSubspace(coarseTmps[1], fineTmps[0]); // R P v_c
|
||||
|
||||
cTmps[2] = cTmps[0] - cTmps[1]; // v_c - R P v_c
|
||||
auto deviation = std::sqrt(norm2(cTmps[2]) / norm2(cTmps[0]));
|
||||
coarseTmps[2] = coarseTmps[0] - coarseTmps[1]; // v_c - R P v_c
|
||||
auto deviation = std::sqrt(norm2(coarseTmps[2]) / norm2(coarseTmps[0]));
|
||||
|
||||
std::cout << GridLogMessage << "norm2(v_c) = " << norm2(cTmps[0]) << " | norm2(R P v_c) = " << norm2(cTmps[1])
|
||||
<< " | norm2(P v_c) = " << norm2(fTmps[0]) << " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
std::cout << " > " << tolerance << " -> check failed" << std::endl;
|
||||
// abort();
|
||||
} else {
|
||||
std::cout << " < " << tolerance << " -> check passed" << std::endl;
|
||||
}
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "MG correctness check: 0 == (R D P - D_c) v_c" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
random(cGrids.PRNGs[whichCoarseGrid], cTmps[0]);
|
||||
|
||||
_Aggregates.PromoteFromSubspace(cTmps[0], fTmps[0]); // P v_c
|
||||
_FineOperator.Op(fTmps[0], fTmps[1]); // D P v_c
|
||||
_Aggregates.ProjectToSubspace(cTmps[1], fTmps[1]); // R D P v_c
|
||||
|
||||
MdagMOp.Op(cTmps[0], cTmps[2]); // D_c v_c
|
||||
|
||||
cTmps[3] = cTmps[1] - cTmps[2]; // R D P v_c - D_c v_c
|
||||
deviation = std::sqrt(norm2(cTmps[3]) / norm2(cTmps[1]));
|
||||
|
||||
std::cout << GridLogMessage << "norm2(R D P v_c) = " << norm2(cTmps[1]) << " | norm2(D_c v_c) = " << norm2(cTmps[2])
|
||||
std::cout << GridLogMG << " Level " << level << ": norm2(v_c) = " << norm2(coarseTmps[0])
|
||||
<< " | norm2(R P v_c) = " << norm2(coarseTmps[1]) << " | norm2(P v_c) = " << norm2(fineTmps[0])
|
||||
<< " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
@ -388,57 +438,117 @@ public:
|
||||
std::cout << " < " << tolerance << " -> check passed" << std::endl;
|
||||
}
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "MG correctness check: 0 == |(Im(v_c^dag D_c^dag D_c v_c)|" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == (R D P - D_c) v_c" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
|
||||
random(cGrids.PRNGs[whichCoarseGrid], cTmps[0]);
|
||||
random(_LevelInfo.PRNGs[coarseLevel], coarseTmps[0]);
|
||||
|
||||
MdagMOp.Op(cTmps[0], cTmps[1]); // D_c v_c
|
||||
MdagMOp.AdjOp(cTmps[1], cTmps[2]); // D_c^dag D_c v_c
|
||||
_Aggregates.PromoteFromSubspace(coarseTmps[0], fineTmps[0]); // P v_c
|
||||
fineMdagMOp.Op(fineTmps[0], fineTmps[1]); // D P v_c
|
||||
_Aggregates.ProjectToSubspace(coarseTmps[1], fineTmps[1]); // R D P v_c
|
||||
|
||||
auto dot = innerProduct(cTmps[0], cTmps[2]); //v_c^dag D_c^dag D_c v_c
|
||||
coarseMdagMOp.Op(coarseTmps[0], coarseTmps[2]); // D_c v_c
|
||||
|
||||
coarseTmps[3] = coarseTmps[1] - coarseTmps[2]; // R D P v_c - D_c v_c
|
||||
deviation = std::sqrt(norm2(coarseTmps[3]) / norm2(coarseTmps[1]));
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": norm2(R D P v_c) = " << norm2(coarseTmps[1])
|
||||
<< " | norm2(D_c v_c) = " << norm2(coarseTmps[2]) << " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
std::cout << " > " << tolerance << " -> check failed" << std::endl;
|
||||
// abort();
|
||||
} else {
|
||||
std::cout << " < " << tolerance << " -> check passed" << std::endl;
|
||||
}
|
||||
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": MG correctness check: 0 == |(Im(v_c^dag D_c^dag D_c v_c)|" << std::endl;
|
||||
std::cout << GridLogMG << " Level " << level << ": **************************************************" << std::endl;
|
||||
|
||||
random(_LevelInfo.PRNGs[coarseLevel], coarseTmps[0]);
|
||||
|
||||
coarseMdagMOp.Op(coarseTmps[0], coarseTmps[1]); // D_c v_c
|
||||
coarseMdagMOp.AdjOp(coarseTmps[1], coarseTmps[2]); // D_c^dag D_c v_c
|
||||
|
||||
auto dot = innerProduct(coarseTmps[0], coarseTmps[2]); //v_c^dag D_c^dag D_c v_c
|
||||
deviation = abs(imag(dot)) / abs(real(dot));
|
||||
|
||||
std::cout << GridLogMessage << "Re(v_c^dag D_c^dag D_c v_c) = " << real(dot) << " | Im(v_c^dag D_c^dag D_c v_c) = " << imag(dot)
|
||||
<< " | relative deviation = " << deviation;
|
||||
std::cout << GridLogMG << " Level " << level << ": Re(v_c^dag D_c^dag D_c v_c) = " << real(dot)
|
||||
<< " | Im(v_c^dag D_c^dag D_c v_c) = " << imag(dot) << " | relative deviation = " << deviation;
|
||||
|
||||
if(deviation > tolerance) {
|
||||
std::cout << " > " << tolerance << " -> check failed" << std::endl;
|
||||
// abort();
|
||||
} else {
|
||||
std::cout << " < " << tolerance << " -> check passed" << std::endl;
|
||||
std::cout << " < " << tolerance << " -> check passed"
|
||||
<< std::endl; // TODO: this check will work only when I got Mdag in CoarsenedMatrix to work
|
||||
}
|
||||
|
||||
_NextPreconditionerLevel->runChecks();
|
||||
}
|
||||
};
|
||||
|
||||
// Specialize the coarsest level, this corresponds to counting downwards with level: coarsest = 0, finest = N
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
class MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 0, Matrix> : public LinearFunction<Lattice<Fobj>> {
|
||||
public:
|
||||
/////////////////////////////////////////////
|
||||
// Type Definitions
|
||||
/////////////////////////////////////////////
|
||||
|
||||
typedef Matrix FineMatrix;
|
||||
typedef Lattice<Fobj> FineVector;
|
||||
|
||||
/////////////////////////////////////////////
|
||||
// Member Data
|
||||
/////////////////////////////////////////////
|
||||
|
||||
LevelInfo & _LevelInfo;
|
||||
FineMatrix &_FineMatrix;
|
||||
FineMatrix &_SmootherMatrix;
|
||||
|
||||
/////////////////////////////////////////////
|
||||
// Member Functions
|
||||
/////////////////////////////////////////////
|
||||
|
||||
MultiGridPreconditioner(LevelInfo &LvlInfo, FineMatrix &FineMat, FineMatrix &SmootherMat)
|
||||
: _LevelInfo(LvlInfo), _FineMatrix(FineMat), _SmootherMatrix(SmootherMat) {}
|
||||
|
||||
void setup() {}
|
||||
|
||||
virtual void operator()(Lattice<Fobj> const &in, Lattice<Fobj> &out) {
|
||||
|
||||
TrivialPrecon<FineVector> fineTrivialPreconditioner;
|
||||
FlexibleGeneralisedMinimalResidual<FineVector> fineFGMRES(1.0e-14, 1, fineTrivialPreconditioner, 1, false);
|
||||
|
||||
MdagMLinearOperator<FineMatrix, FineVector> fineMdagMOp(_FineMatrix);
|
||||
|
||||
fineFGMRES(fineMdagMOp, in, out);
|
||||
}
|
||||
|
||||
void runChecks() {}
|
||||
};
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
using FourLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 4 - 1, Matrix>;
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
using ThreeLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 3 - 1, Matrix>;
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, class Matrix>
|
||||
using TwoLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, 2 - 1, Matrix>;
|
||||
|
||||
template<class Fobj, class CoarseScalar, int nCoarseSpins, int nbasis, int nlevel, class Matrix>
|
||||
using NLevelMGPreconditioner = MultiGridPreconditioner<Fobj, CoarseScalar, nCoarseSpins, nbasis, nlevel - 1, Matrix>;
|
||||
|
||||
int main(int argc, char **argv) {
|
||||
|
||||
Grid_init(&argc, &argv);
|
||||
|
||||
params.domainsize = 1;
|
||||
params.coarsegrids = 1;
|
||||
params.domaindecompose = 0;
|
||||
params.order = 30;
|
||||
params.Ls = 1;
|
||||
params.mq = -0.5;
|
||||
params.lo = 0.5;
|
||||
params.hi = 70.0;
|
||||
params.steps = 1;
|
||||
|
||||
typedef typename WilsonCloverFermionR::FermionField FermionField;
|
||||
typename WilsonCloverFermionR::ImplParams wcImplparams;
|
||||
WilsonAnisotropyCoefficients wilsonAnisCoeff;
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Params: " << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::cout << params << std::endl;
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Set up some fine level stuff: " << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
typename WilsonCloverFermionR::ImplParams wcImplparams;
|
||||
WilsonAnisotropyCoefficients wilsonAnisCoeff;
|
||||
|
||||
GridCartesian *FGrid = SpaceTimeGrid::makeFourDimGrid(GridDefaultLatt(), GridDefaultSimd(Nd, vComplex::Nsimd()), GridDefaultMpi());
|
||||
GridRedBlackCartesian *FrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(FGrid);
|
||||
@ -450,319 +560,107 @@ int main(int argc, char **argv) {
|
||||
Gamma g5(Gamma::Algebra::Gamma5);
|
||||
|
||||
// clang-format off
|
||||
FermionField src(FGrid); gaussian(fPRNG, src);
|
||||
FermionField result(FGrid); result = zero;
|
||||
LatticeFermion src(FGrid); gaussian(fPRNG, src);
|
||||
LatticeFermion result(FGrid); result = zero;
|
||||
LatticeGaugeField Umu(FGrid); SU3::HotConfiguration(fPRNG, Umu);
|
||||
// clang-format on
|
||||
|
||||
RealD mass = params.mq;
|
||||
RealD mass = 0.5;
|
||||
RealD csw_r = 1.0;
|
||||
RealD csw_t = 1.0;
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Set up some coarser levels stuff: " << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
const int nbasis = 20;
|
||||
|
||||
const int nbasis = 20; // fix the number of test vector to the same
|
||||
// number on every level for now
|
||||
|
||||
//////////////////////////////////////////
|
||||
// toggle to run two/three level method
|
||||
//////////////////////////////////////////
|
||||
|
||||
// two-level algorithm
|
||||
std::vector<std::vector<int>> blockSizes({{2, 2, 2, 2}});
|
||||
CoarseGrids<nbasis> coarseGrids(blockSizes, 1);
|
||||
|
||||
// // three-level algorithm
|
||||
// std::vector<std::vector<int>> blockSizes({{2, 2, 2, 2}, {2, 2, 1, 1}});
|
||||
// CoarseGrids<nbasis> coarseGrids(blockSizes, 2);
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Some typedefs" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
// typedefs for transition from fine to first coarsened grid
|
||||
typedef vSpinColourVector FineSiteVector;
|
||||
typedef vTComplex CoarseSiteScalar;
|
||||
typedef Aggregation<FineSiteVector, CoarseSiteScalar, nbasis> Subspace;
|
||||
typedef CoarsenedMatrix<FineSiteVector, CoarseSiteScalar, nbasis> CoarseOperator;
|
||||
typedef CoarseOperator::CoarseVector CoarseVector;
|
||||
typedef CoarseOperator::siteVector CoarseSiteVector;
|
||||
typedef TestVectorAnalyzer<FermionField, nbasis> FineTVA;
|
||||
typedef MultiGridPreconditioner<FineSiteVector, CoarseSiteScalar, nbasis, WilsonCloverFermionR> FineMGPreconditioner;
|
||||
typedef TrivialPrecon<FermionField> FineTrivialPreconditioner;
|
||||
|
||||
// typedefs for transition from a coarse to the next coarser grid (some defs remain the same)
|
||||
typedef Aggregation<CoarseSiteVector, CoarseSiteScalar, nbasis> SubSubSpace;
|
||||
typedef CoarsenedMatrix<CoarseSiteVector, CoarseSiteScalar, nbasis> CoarseCoarseOperator;
|
||||
typedef CoarseCoarseOperator::CoarseVector CoarseCoarseVector;
|
||||
typedef CoarseCoarseOperator::siteVector CoarseCoarseSiteVector;
|
||||
typedef TestVectorAnalyzer<CoarseVector, nbasis> CoarseTVA;
|
||||
typedef MultiGridPreconditioner<CoarseSiteVector, CoarseSiteScalar, nbasis, CoarseOperator> CoarseMGPreconditioner;
|
||||
typedef TrivialPrecon<CoarseVector> CoarseTrivialPreconditioner;
|
||||
|
||||
static_assert(std::is_same<CoarseVector, CoarseCoarseVector>::value, "CoarseVector and CoarseCoarseVector must be of the same type");
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Building the wilson clover operator on the fine grid" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
RealD csw_r = 1.0;
|
||||
RealD csw_t = 1.0;
|
||||
WilsonFermionR Dw(Umu, *FGrid, *FrbGrid, mass);
|
||||
WilsonCloverFermionR Dwc(Umu, *FGrid, *FrbGrid, mass, csw_r, csw_t, wilsonAnisCoeff, wcImplparams);
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Setting up linear operators" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// mgParams.blockSizes = {{2, 2, 2, 2}, {2, 2, 1, 1}, {1, 1, 2, 1}};
|
||||
// mgParams.blockSizes = {{2, 2, 2, 2}, {2, 2, 1, 1}};
|
||||
mgParams.blockSizes = {{2, 2, 2, 2}};
|
||||
mgParams.nLevels = mgParams.blockSizes.size() + 1;
|
||||
|
||||
MdagMLinearOperator<WilsonCloverFermionR, FermionField> FineMdagMOp(Dwc);
|
||||
std::cout << mgParams << std::endl;
|
||||
|
||||
LevelInfo levelInfo(FGrid, mgParams);
|
||||
|
||||
static_assert(std::is_same<LatticeFermion, typename WilsonFermionR::FermionField>::value, "");
|
||||
static_assert(std::is_same<LatticeFermion, typename WilsonCloverFermionR::FermionField>::value, "");
|
||||
|
||||
MdagMLinearOperator<WilsonFermionR, LatticeFermion> MdagMOpDw(Dw);
|
||||
MdagMLinearOperator<WilsonCloverFermionR, LatticeFermion> MdagMOpDwc(Dwc);
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Calling Aggregation class to build subspaces" << std::endl;
|
||||
std::cout << GridLogMessage << "Testing Multigrid for Wilson" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
Subspace FineAggregates(coarseGrids.Grids[0], FGrid, 0);
|
||||
TrivialPrecon<LatticeFermion> TrivialPrecon;
|
||||
TwoLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonFermionR> TwoLevelMGPreconDw(levelInfo, Dw, Dw);
|
||||
// ThreeLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonFermionR> ThreeLevelMGPreconDw(levelInfo, Dw, Dw);
|
||||
// FourLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonFermionR> FourLevelMGPreconDw(levelInfo, Dw, Dw);
|
||||
// NLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, 4, WilsonFermionR> NLevelMGPreconDw(levelInfo, Dw, Dw);
|
||||
|
||||
assert((nbasis & 0x1) == 0);
|
||||
int nb = nbasis / 2;
|
||||
std::cout << GridLogMessage << " nbasis/2 = " << nb << std::endl;
|
||||
TwoLevelMGPreconDw.setup();
|
||||
TwoLevelMGPreconDw.runChecks();
|
||||
|
||||
FineAggregates.CreateSubspace(fPRNG, FineMdagMOp /*, nb */); // Don't specify nb to see the orthogonalization check
|
||||
// ThreeLevelMGPreconDw.setup();
|
||||
// ThreeLevelMGPreconDw.runChecks();
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Test vector analysis after initial creation of subspace" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// FourLevelMGPreconDw.setup();
|
||||
// FourLevelMGPreconDw.runChecks();
|
||||
|
||||
FineTVA fineTVA;
|
||||
fineTVA(FineMdagMOp, FineAggregates.subspace);
|
||||
// NLevelMGPreconDw.setup();
|
||||
// NLevelMGPreconDw.runChecks();
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Projecting subspace to definite chirality" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::vector<std::unique_ptr<OperatorFunction<LatticeFermion>>> solversDw;
|
||||
|
||||
for(int n = 0; n < nb; n++) {
|
||||
FineAggregates.subspace[n + nb] = g5 * FineAggregates.subspace[n];
|
||||
}
|
||||
solversDw.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, TrivialPrecon, 1000, false));
|
||||
solversDw.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, TwoLevelMGPreconDw, 1000, false));
|
||||
// solversDw.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, ThreeLevelMGPreconDw, 1000, false));
|
||||
// solversDw.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, FourLevelMGPreconDw, 1000, false));
|
||||
// solversDw.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, NLevelMGPreconDw, 1000, false));
|
||||
|
||||
auto coarseSites = 1;
|
||||
for(auto const &elem : coarseGrids.LattSizes[0]) coarseSites *= elem;
|
||||
|
||||
std::cout << GridLogMessage << "Norms of MG test vectors after chiral projection (coarse sites = " << coarseSites << ")" << std::endl;
|
||||
for(int n = 0; n < nbasis; n++) {
|
||||
std::cout << GridLogMessage << "vec[" << n << "] = " << norm2(FineAggregates.subspace[n]) << std::endl;
|
||||
}
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Building coarse representation of Dirac operator" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
CoarseOperator Dc(*coarseGrids.Grids[0]);
|
||||
|
||||
Dc.CoarsenOperator(FGrid, FineMdagMOp, FineAggregates);
|
||||
|
||||
MdagMLinearOperator<CoarseOperator, CoarseVector> CoarseMdagMOp(Dc);
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Test vector analysis after construction of coarse Dirac operator" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
fineTVA(FineMdagMOp, FineAggregates.subspace);
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Testing the linear operators" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
// clang-format off
|
||||
testLinearOperator(FineMdagMOp, FGrid, "FineMdagMOp"); std::cout << GridLogMessage << std::endl;
|
||||
testLinearOperator(CoarseMdagMOp, coarseGrids.Grids[0], "CoarseMdagMOp"); std::cout << GridLogMessage << std::endl;
|
||||
// clang-format on
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Building coarse vectors" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
CoarseVector coarseSource(coarseGrids.Grids[0]);
|
||||
CoarseVector coarseResult(coarseGrids.Grids[0]);
|
||||
gaussian(coarseGrids.PRNGs[0], coarseSource);
|
||||
coarseResult = zero;
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Building some coarse space solvers" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::vector<std::unique_ptr<OperatorFunction<CoarseVector>>> dummyCoarseSolvers;
|
||||
dummyCoarseSolvers.emplace_back(new GeneralisedMinimalResidual<CoarseVector>(5.0e-2, 100, 8, false));
|
||||
dummyCoarseSolvers.emplace_back(new MinimalResidual<CoarseVector>(5.0e-2, 100, 0.8, false));
|
||||
dummyCoarseSolvers.emplace_back(new ConjugateGradient<CoarseVector>(5.0e-2, 100, false));
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Testing some coarse space solvers" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::cout << GridLogMessage << "checking norm of coarse src " << norm2(coarseSource) << std::endl;
|
||||
|
||||
for(auto const &solver : dummyCoarseSolvers) {
|
||||
coarseResult = zero;
|
||||
(*solver)(CoarseMdagMOp, coarseSource, coarseResult);
|
||||
}
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Building a multigrid preconditioner" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
FineMGPreconditioner FineMGPrecon(FineAggregates, Dc, FineMdagMOp, Dwc, FineMdagMOp, Dwc);
|
||||
FineTrivialPreconditioner FineSimplePrecon;
|
||||
|
||||
FineMGPrecon.runChecks(coarseGrids, 0);
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Building krylov subspace solvers w/ & w/o MG Preconditioner" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::vector<std::unique_ptr<OperatorFunction<FermionField>>> solvers;
|
||||
solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<FermionField>(1.0e-12, 4000000, FineSimplePrecon, 25, false));
|
||||
solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<FermionField>(1.0e-12, 100, FineMGPrecon, 25, false));
|
||||
solvers.emplace_back(new PrecGeneralisedConjugateResidual<FermionField>(1.0e-12, 4000000, FineSimplePrecon, 25, 25));
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Testing the (un)?preconditioned solvers" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
for(auto const &solver : solvers) {
|
||||
std::cout << GridLogMessage << "checking norm of fine src " << norm2(src) << std::endl;
|
||||
for(auto const &solver : solversDw) {
|
||||
std::cout << "Starting with a new solver" << std::endl;
|
||||
result = zero;
|
||||
(*solver)(FineMdagMOp, src, result);
|
||||
(*solver)(MdagMOpDw, src, result);
|
||||
std::cout << std::endl;
|
||||
}
|
||||
|
||||
#if 0
|
||||
if(coarseGrids.LattSizes.size() == 2) {
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Testing Multigrid for Wilson Clover" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::cout << GridLogMessage << "Some testing for construction of a second coarse level" << std::endl;
|
||||
std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
TwoLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonCloverFermionR> TwoLevelMGPreconDwc(levelInfo, Dwc, Dwc);
|
||||
// ThreeLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonCloverFermionR> ThreeLevelMGPreconDwc(levelInfo, Dwc, Dwc);
|
||||
// FourLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, WilsonCloverFermionR> FourLevelMGPreconDwc(levelInfo, Dwc, Dwc);
|
||||
// NLevelMGPreconditioner<vSpinColourVector, vTComplex, 1, nbasis, 4, WilsonCloverFermionR> NLevelMGPreconDwc(levelInfo, Dwc, Dwc);
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Calling Aggregation class to build subspaces" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
TwoLevelMGPreconDwc.setup();
|
||||
TwoLevelMGPreconDwc.runChecks();
|
||||
|
||||
SubSubSpace CoarseAggregates(coarseGrids.Grids[1], coarseGrids.Grids[0], 0);
|
||||
CoarseAggregates.CreateSubspace(coarseGrids.PRNGs[0], CoarseMdagMOp);
|
||||
// ThreeLevelMGPreconDwc.setup();
|
||||
// ThreeLevelMGPreconDwc.runChecks();
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Test vector analysis after initial creation of subspace" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// FourLevelMGPreconDwc.setup();
|
||||
// FourLevelMGPreconDwc.runChecks();
|
||||
|
||||
// // this doesn't work because this function applies g5 to a vector, which
|
||||
// // doesn't work for coarse vectors atm -> FIXME
|
||||
// CoarseTVA coarseTVA;
|
||||
// coarseTVA(CoarseMdagMOp, CoarseAggregates.subspace);
|
||||
// NLevelMGPreconDwc.setup();
|
||||
// NLevelMGPreconDwc.runChecks();
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Projecting subspace to definite chirality" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
std::vector<std::unique_ptr<OperatorFunction<LatticeFermion>>> solversDwc;
|
||||
|
||||
// // cannot apply g5 to coarse vectors atm -> FIXME
|
||||
// for(int n=0;n<nb;n++){
|
||||
// CoarseAggregates.subspace[n+nb] = g5 * CoarseAggregates.subspace[n];
|
||||
// std::cout<<GridLogMessage<<n<<" subspace "<<norm2(CoarseAggregates.subspace[n+nb])<<" "<<norm2(CoarseAggregates.subspace[n]) <<std::endl;
|
||||
// }
|
||||
|
||||
auto coarseCoarseSites = 1;
|
||||
for(auto const &elem : coarseGrids.LattSizes[1]) coarseCoarseSites *= elem;
|
||||
|
||||
std::cout << GridLogMessage << "Norms of MG test vectors after chiral projection (coarse coarse sites = " << coarseCoarseSites << ")"
|
||||
<< std::endl;
|
||||
for(int n = 0; n < nbasis; n++) {
|
||||
std::cout << GridLogMessage << "vec[" << n << "] = " << norm2(CoarseAggregates.subspace[n]) << std::endl;
|
||||
}
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Building coarse coarse representation of Dirac operator" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
CoarseCoarseOperator Dcc(*coarseGrids.Grids[1]);
|
||||
|
||||
Dcc.CoarsenOperator(coarseGrids.Grids[0], CoarseMdagMOp, CoarseAggregates);
|
||||
|
||||
MdagMLinearOperator<CoarseCoarseOperator, CoarseCoarseVector> CoarseCoarseMdagMOp(Dcc);
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Test vector analysis after construction of coarse Dirac operator" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
// // this doesn't work because this function applies g5 to a vector, which
|
||||
// // doesn't work for coarse vectors atm -> FIXME
|
||||
// coarseTVA(CoarseMdagMOp, CoarseAggregates.subspace);
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Testing the linear operators" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
// clang-format off
|
||||
testLinearOperator(CoarseMdagMOp, coarseGrids.Grids[0], "CoarseMdagMOp");
|
||||
testLinearOperator(CoarseCoarseMdagMOp, coarseGrids.Grids[1], "CoarseCoarseMdagMOp");
|
||||
// clang-format on
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Building coarse coarse vectors" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
CoarseCoarseVector coarseCoarseSource(coarseGrids.Grids[1]);
|
||||
CoarseCoarseVector coarseCoarseResult(coarseGrids.Grids[1]);
|
||||
gaussian(coarseGrids.PRNGs[1], coarseCoarseSource);
|
||||
coarseCoarseResult = zero;
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Building some coarse space solvers" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::vector<std::unique_ptr<OperatorFunction<CoarseCoarseVector>>> dummyCoarseCoarseSolvers;
|
||||
dummyCoarseCoarseSolvers.emplace_back(new GeneralisedMinimalResidual<CoarseCoarseVector>(5.0e-2, 100, 8, false));
|
||||
dummyCoarseCoarseSolvers.emplace_back(new MinimalResidual<CoarseCoarseVector>(5.0e-2, 100, 0.8, false));
|
||||
dummyCoarseCoarseSolvers.emplace_back(new ConjugateGradient<CoarseCoarseVector>(5.0e-2, 100, false));
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Testing some coarse coarse space solvers" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::cout << GridLogMessage << "checking norm of coarse coarse src " << norm2(coarseCoarseSource) << std::endl;
|
||||
|
||||
for(auto const &solver : dummyCoarseCoarseSolvers) {
|
||||
coarseCoarseResult = zero;
|
||||
(*solver)(CoarseCoarseMdagMOp, coarseCoarseSource, coarseCoarseResult);
|
||||
}
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Building a multigrid preconditioner" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
CoarseMGPreconditioner CoarseMGPrecon(CoarseAggregates, Dcc, CoarseMdagMOp, Dc, CoarseMdagMOp, Dc);
|
||||
CoarseTrivialPreconditioner CoarseSimplePrecon;
|
||||
|
||||
CoarseMGPrecon.runChecks(coarseGrids, 1);
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Building krylov subspace solvers w/ & w/o MG Preconditioner" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
std::vector<std::unique_ptr<OperatorFunction<CoarseVector>>> solvers;
|
||||
solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<CoarseVector>(1.0e-12, 4000000, CoarseSimplePrecon, 25, false));
|
||||
solvers.emplace_back(new FlexibleGeneralisedMinimalResidual<CoarseVector>(1.0e-12, 100, CoarseMGPrecon, 25, false));
|
||||
solvers.emplace_back(new PrecGeneralisedConjugateResidual<CoarseVector>(1.0e-12, 4000000, CoarseSimplePrecon, 25, 25));
|
||||
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
// std::cout << GridLogMessage << "Testing the (un)?preconditioned solvers" << std::endl;
|
||||
// std::cout << GridLogMessage << "**************************************************" << std::endl;
|
||||
|
||||
for(auto const &solver : solvers) {
|
||||
std::cout << GridLogMessage << "checking norm of fine src " << norm2(coarseSource) << std::endl;
|
||||
coarseResult = zero;
|
||||
(*solver)(CoarseMdagMOp, coarseSource, coarseResult);
|
||||
std::cout << std::endl;
|
||||
}
|
||||
solversDwc.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, TrivialPrecon, 1000, false));
|
||||
solversDwc.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, TwoLevelMGPreconDwc, 1000, false));
|
||||
// solversDwc.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, ThreeLevelMGPreconDwc, 1000, false));
|
||||
// solversDwc.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, FourLevelMGPreconDwc, 1000, false));
|
||||
// solversDwc.emplace_back(new FlexibleGeneralisedMinimalResidual<LatticeFermion>(1.0e-12, 50000, NLevelMGPreconDwc, 1000, false));
|
||||
|
||||
for(auto const &solver : solversDwc) {
|
||||
std::cout << "Starting with a new solver" << std::endl;
|
||||
result = zero;
|
||||
(*solver)(MdagMOpDwc, src, result);
|
||||
std::cout << std::endl;
|
||||
}
|
||||
#endif
|
||||
|
||||
Grid_finalize();
|
||||
}
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user