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tpetra/example/PCPG/PCPGTpetraExFile.cpp

This is an example of how to use Belos::PCPGSolMgr with Tpetra.

// @HEADER
// *****************************************************************************
// Belos: Block Linear Solvers Package
//
// Copyright 2004-2016 NTESS and the Belos contributors.
// SPDX-License-Identifier: BSD-3-Clause
// *****************************************************************************
// @HEADER
// Purpose
// The example tests the successive right-hand sides capabilities of ML
// and Belos on a heat flow u_t = u_xx problem.
//
// A sequence of linear systems with the same coefficient matrix and
// different right-hand sides is solved. A seed space is generated dynamically,
// and a deflated linear system is solved. After each solves, the first
// few Krylov vectors are saved, and used to reduce the number of iterations
// for later solves.
// The optimal numbers of vectors to deflate and save are not known.
// Presently, the maximum number of vectors to deflate (seed space dimension)
// and to save are user paraemters.
// The seed space dimension is less than or equal to total number of vectors
// saved. The difference between the seed space dimension and the total number
// of vectors, is the number of vectors used to update the seed space after each
// solve. I guess that a seed space whose dimension is a small fraction of the
// total space will be best.
//
// maxSave=1 and maxDeflate=0 uses no recycling (not tested ).
//
// TODO: Instrument with timers, so that we can tell what is going on besides
// by counting the numbers of iterations.
//
//
// Adapted from PCPGEpetraExFile.cpp by David M. Day (with original comments)
// All preconditioning has been commented out
// Tpetra
#include <TpetraExt_MatrixMatrix.hpp>
#include <Tpetra_Core.hpp>
#include <Tpetra_CrsMatrix_fwd.hpp>
#include <Tpetra_Map_fwd.hpp>
#include <Tpetra_Vector_fwd.hpp>
// MueLu
// #include <MueLu_TpetraOperator.hpp>
// #include <MueLu_CreateTpetraPreconditioner.hpp>
// Teuchos
#include <Teuchos_Comm.hpp>
#include <Teuchos_CommHelpers.hpp>
#include <Teuchos_DefaultComm.hpp>
#include <Teuchos_FancyOStream.hpp>
#include <Teuchos_RCP.hpp>
#include <Teuchos_StandardCatchMacros.hpp>
#include <Teuchos_Tuple.hpp>
#include <Teuchos_VerboseObject.hpp>
// Belos
#include "BelosTpetraAdapter.hpp"
template <typename ScalarType>
int run(int argc, char *argv[]) {
//
// Laplace's equation, homogeneous Dirichlet boundary conditions, [0,1]^2
// regular mesh, Q1 finite elements
//
using Teuchos::RCP;
using Teuchos::rcp;
using Teuchos::tuple;
using ST = typename Tpetra::MultiVector<ScalarType>::scalar_type;
using LO = typename Tpetra::Vector<>::local_ordinal_type;
using GO = typename Tpetra::Vector<>::global_ordinal_type;
using NT = typename Tpetra::Vector<>::node_type;
using V = typename Tpetra::Vector<ST, LO, GO, NT>;
using MV = typename Tpetra::MultiVector<ST, LO, GO, NT>;
using OP = typename Tpetra::Operator<ST, LO, GO, NT>;
using MVT = typename Belos::MultiVecTraits<ST, MV>;
using OPT = typename Belos::OperatorTraits<ST, MV, OP>;
using MAP = typename Tpetra::Map<LO, GO, NT>;
using MAT = typename Tpetra::CrsMatrix<ST, LO, GO, NT>;
using SCT = typename Teuchos::ScalarTraits<ST>;
using MT = typename SCT::magnitudeType;
using LinearProblem = typename Belos::LinearProblem<ST, MV, OP>;
using PCPGSolMgr = ::Belos::PCPGSolMgr<ST, MV, OP>;
Teuchos::GlobalMPISession session(&argc, &argv, NULL);
RCP<const Teuchos::Comm<int>> comm = Tpetra::getDefaultComm();
bool verbose = false;
bool success = true;
try {
bool procVerbose = false;
int frequency = -1; // frequency of status test output.
int blocksize = 1; // blocksize, PCPGIter
int numRhs = 1; // number of right-hand sides to solve for
int maxIters = 30; // maximum number of iterations allowed per linear system
int maxDeflate = 4; // maximum number of vectors deflated from the linear system;
// There is no overhead cost assoc with changing maxDeflate between solves
int maxSave = 8; // maximum number of vectors saved from current and previous .");
// If maxSave changes between solves, then re-initialize (setSize).
// Hypothesis: seed vectors are conjugate.
// Initial versions allowed users to supply a seed space et cetera, but no
// longer.
// The documentation it suitable for certain tasks, like defining a modules
// grammar,
std::string ortho("ICGS"); // The Belos documentation obscures the fact that
// IMGS is Iterated Modified Gram Schmidt,
// ICGS is Iterated Classical Gram Schmidt, and
// DKGS is another Iterated Classical Gram Schmidt.
// Mathematical issues, such as the difference between ICGS and DKGS, are
// not documented at all. UH tells me that Anasazi::SVQBOrthoManager is
// available; I need it for Belos
MT tol = sqrt(std::numeric_limits<ST>::epsilon()); // relative residual tolerance
// How do command line parsers work?
Teuchos::CommandLineProcessor cmdp(false, true);
cmdp.setOption("verbose", "quiet", &verbose, "Print messages and results");
cmdp.setOption("frequency", &frequency, "Solvers frequency for printing residuals (#iters)");
cmdp.setOption("tol", &tol, "Relative residual tolerance used by PCPG solver");
cmdp.setOption("num-rhs", &numRhs, "Number of right-hand sides to be solved for");
cmdp.setOption("max-iters", &maxIters,
"Maximum number of iterations per linear system (-1 = "
"adapted to problem/block size)");
cmdp.setOption("num-deflate", &maxDeflate, "Number of vectors deflated from the linear system");
cmdp.setOption("num-save", &maxSave, "Number of vectors saved from old Krylov subspaces");
cmdp.setOption("ortho-type", &ortho, "Orthogonalization type, either DGKS, ICGS or IMGS");
return -1;
}
if (!verbose)
frequency = -1; // reset frequency if test is not verbose
//
// *************Form the problem****************
//
int numTimeStep = 4;
GO numElePerDirection = 14 * comm->getSize(); // 5 -> 20
size_t numNodes = (numElePerDirection - 1) * (numElePerDirection - 1);
// By the way, either matrix has (3*numElePerDirection - 2)^2 nonzeros.
RCP<MAP> map = rcp(new MAP(numNodes, 0, comm));
RCP<MAT> stiff = rcp(new MAT(map, numNodes));
RCP<MAT> mass = rcp(new MAT(map, numNodes));
RCP<V> vecLHS = rcp(new V(map));
RCP<V> vecRHS = rcp(new V(map));
RCP<MV> LHS, RHS;
ST ko = 8.0 / 3.0, k1 = -1.0 / 3.0;
ST h = 1.0 / static_cast<ST>(numElePerDirection); // x=(iX,iY)h
ST mo = h * h * 4.0 / 9.0, m1 = h * h / 9.0, m2 = h * h / 36.0;
ST pi = 4.0 * atan(1.0), valueLHS;
GO node, iX, iY;
for (LO lid = map->getMinLocalIndex(); lid <= map->getMaxLocalIndex(); lid++) {
node = map->getGlobalElement(lid);
iX = node % (numElePerDirection - 1);
iY = (node - iX) / (numElePerDirection - 1);
GO pos = node;
stiff->insertGlobalValues(node, tuple(pos), tuple(ko));
mass->insertGlobalValues(node, tuple(pos),
tuple(mo)); // init guess violates hom Dir bc
valueLHS = sin(pi * h * ((ST)iX + 1)) * cos(2.0 * pi * h * ((ST)iY + 1));
vecLHS->replaceGlobalValue(1, valueLHS);
if (iY > 0) {
pos = iX + (iY - 1) * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // North
mass->insertGlobalValues(node, tuple(pos), tuple(m1));
}
if (iY < numElePerDirection - 2) {
pos = iX + (iY + 1) * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // South
mass->insertGlobalValues(node, tuple(pos), tuple(m1));
}
if (iX > 0) {
pos = iX - 1 + iY * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // West
mass->insertGlobalValues(node, tuple(pos), tuple(m1));
if (iY > 0) {
pos = iX - 1 + (iY - 1) * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // North West
mass->insertGlobalValues(node, tuple(pos), tuple(m2));
}
if (iY < numElePerDirection - 2) {
pos = iX - 1 + (iY + 1) * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // South West
mass->insertGlobalValues(node, tuple(pos), tuple(m2));
}
}
if (iX < numElePerDirection - 2) {
pos = iX + 1 + iY * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // East
mass->insertGlobalValues(node, tuple(pos), tuple(m1));
if (iY > 0) {
pos = iX + 1 + (iY - 1) * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // North East
mass->insertGlobalValues(node, tuple(pos), tuple(m2));
}
if (iY < numElePerDirection - 2) {
pos = iX + 1 + (iY + 1) * (numElePerDirection - 1);
stiff->insertGlobalValues(node, tuple(pos), tuple(k1)); // South East
mass->insertGlobalValues(node, tuple(pos), tuple(m2));
}
}
}
stiff->fillComplete();
mass->fillComplete();
const ST one = SCT::one();
ST hdt = .00005; // half time step
// A = Mass+Stiff*dt/2
RCP<MAT> A = Tpetra::MatrixMatrix::add(one, false, *mass, hdt, false, *stiff);
// B = Mass-Stiff*dt/2
hdt = -hdt;
RCP<MAT> B = Tpetra::MatrixMatrix::add(one, false, *mass, hdt, false, *stiff);
B->apply(*vecLHS, *vecRHS);
procVerbose = verbose && (comm->getRank() == 0); // Only print on the zero processor
LHS = Teuchos::rcp_implicit_cast<MV>(vecLHS);
RHS = Teuchos::rcp_implicit_cast<MV>(vecRHS);
//
// **********Construct preconditioner***********
//
// Teuchos::ParameterList MLList; // Set MLList for Smoothed Aggregation
// ML_Tpetra::SetDefaults("SA",MLList); // reset parameters ML User's Guide
// MLList.set("smoother: type","CHEBYSHEV"); // Chebyshev smoother ... aztec??
// MLList.set("smoother: sweeps",3);
// MLList.set("smoother: pre or post", "both"); // both pre- and post-smoothing
// #ifdef HAVE_MUELU_AMESOS2
// MueLuList.set("coarse: type", "KLU2"); // solve with serial direct
// solver KLU
// #else
// MLList.set("coarse: type", "Jacobi"); // not recommended
// puts("Warning: Iterative coarse grid solve");
// #endif
//
// RCP<OP> prec = MueLu::CreateTpetraPreconditioner(A, MLList );
// assert(prec != Teuchos::null);
// Create the Belos preconditioned operator from the preconditioner.
// NOTE: This is necessary because Belos expects an operator to apply the
// preconditioner with Apply() NOT ApplyInverse().
// RCP<Belos::EpetraPrecOp> belosPrec = rcp( new Belos::EpetraPrecOp( Prec )
// );
// Create parameter list for the PCPG solver manager
const int numGlobalElements = RHS->getGlobalLength();
if (maxIters == -1)
maxIters = numGlobalElements / blocksize - 1; // maximum number of iterations to run
RCP<ParameterList> belosList = rcp(new ParameterList());
belosList->set("Block Size",
blocksize); // Blocksize to be used by iterative solver
belosList->set("Maximum Iterations",
maxIters); // Maximum number of iterations allowed
belosList->set("Convergence Tolerance",
tol); // Relative convergence tolerance requested
belosList->set("Num Deflated Blocks",
maxDeflate); // Number of vectors in seed space
belosList->set("Num Saved Blocks",
maxSave); // Number of vectors saved from old spaces
belosList->set("Orthogonalization", ortho); // Orthogonalization type
if (numRhs > 1) {
belosList->set("Show Maximum Residual Norm Only",
true); // although numRhs = 1.
}
if (verbose) {
belosList->set("Verbosity", Belos::Errors + Belos::Warnings + Belos::TimingDetails +
if (frequency > 0)
belosList->set("Output Frequency", frequency);
} else
belosList->set("Verbosity", Belos::Errors + Belos::Warnings + Belos::FinalSummary);
// Construct a preconditioned linear problem
RCP<LinearProblem> problem = rcp(new LinearProblem(A, LHS, RHS));
// problem->setLeftPrec( prec );
bool set = problem->setProblem();
if (set == false) {
if (procVerbose)
std::cout << std::endl
<< "ERROR: Belos::LinearProblem failed to set up correctly!" << std::endl;
return -1;
}
// Create an iterative solver manager.
RCP<PCPGSolMgr> solver = rcp(new PCPGSolMgr(problem, belosList));
//
// *******************************************************************
// ************************* Iterate PCPG ****************************
// *******************************************************************
//
if (procVerbose) {
std::cout << std::endl << std::endl;
std::cout << "Dimension of matrix: " << numGlobalElements << std::endl;
std::cout << "Number of right-hand sides: " << numRhs << std::endl;
std::cout << "Block size used by solver: " << blocksize << std::endl;
std::cout << "Maximum number of iterations allowed: " << maxIters << std::endl;
std::cout << "Relative residual tolerance: " << tol << std::endl;
std::cout << std::endl;
}
bool badRes;
for (int timeStep = 0; timeStep < numTimeStep; timeStep++) {
if (timeStep) {
// old epetra B->multiply(false, *vecLHS, *vecRHS); // rhs_new :=
// B*lhs_old,
B->apply(*LHS, *RHS); // rhs_new := B*lhs_old,
set = problem->setProblem(LHS, RHS);
if (set == false) {
if (procVerbose)
std::cout << std::endl
<< "ERROR: Belos::LinearProblem failed to set up correctly!" << std::endl;
return -1;
}
} // if timeStep
std::vector<ST> rhs_norm(numRhs);
MVT::MvNorm(*RHS, rhs_norm);
std::cout << " RHS norm is ... " << rhs_norm[0] << std::endl;
// Perform solve
Belos::ReturnType ret = solver->solve();
// Compute actual residuals.
badRes = false;
std::vector<ST> actual_resids(numRhs);
MV resid(map, numRhs);
OPT::Apply(*A, *LHS, resid);
MVT::MvAddMv(-1.0, resid, 1.0, *RHS, resid);
MVT::MvNorm(resid, actual_resids);
MVT::MvNorm(*RHS, rhs_norm);
std::cout << " RHS norm is ... " << rhs_norm[0] << std::endl;
if (procVerbose) {
std::cout << "---------- Actual Residuals (normalized) ----------" << std::endl
<< std::endl;
for (int i = 0; i < numRhs; i++) {
double actRes = actual_resids[i] / rhs_norm[i];
std::cout << "Problem " << i << " : \t" << actRes << std::endl;
if (actRes > tol)
badRes = true;
}
}
if (ret != Belos::Converged || badRes) {
success = false;
break;
}
} // for timeStep
if (procVerbose) {
if (success)
std::cout << std::endl << "SUCCESS: Belos converged!" << std::endl;
else
std::cout << std::endl << "ERROR: Belos did not converge!" << std::endl;
}
} // end try
TEUCHOS_STANDARD_CATCH_STATEMENTS(verbose, std::cerr, success);
return success ? EXIT_SUCCESS : EXIT_FAILURE;
}
int main(int argc, char *argv[]) {
return run<double>(argc, argv);
// return run<float>(argc, argv); }
}
// end PCPGTpetraExFile.cpp

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