GlobalLinSysPETSc.cpp

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///////////////////////////////////////////////////////////////////////////////
//
// File: GlobalLinSysPETSc.cpp
//
// For more information, please see: http://www.nektar.info
//
// The MIT License
//
// Copyright (c) 2006 Division of Applied Mathematics, Brown University (USA),
// Department of Aeronautics, Imperial College London (UK), and Scientific
// Computing and Imaging Institute, University of Utah (USA).
//
// Permission is hereby granted, free of charge, to any person obtaining a
// copy of this software and associated documentation files (the "Software"),
// to deal in the Software without restriction, including without limitation
// the rights to use, copy, modify, merge, publish, distribute, sublicense,
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// Software is furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included
// in all copies or substantial portions of the Software.
//
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// OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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//
// Description: GlobalLinSysPETSc definition
//
///////////////////////////////////////////////////////////////////////////////
 
#include <MultiRegions/GlobalLinSysPETSc.h>
#include <MultiRegions/Preconditioner.h>
 
#include "petscis.h"
#include "petscversion.h"
 
using namespace std;
 
namespace Nektar
{
namespace MultiRegions
{
std::string GlobalLinSysPETSc::matMult =
    LibUtilities::SessionReader::RegisterDefaultSolverInfo("PETScMatMult",
                                                           "Sparse");
std::string GlobalLinSysPETSc::matMultIds[] = {
    LibUtilities::SessionReader::RegisterEnumValue(
        "PETScMatMult", "Sparse", MultiRegions::ePETScMatMultSparse),
    LibUtilities::SessionReader::RegisterEnumValue(
        "PETScMatMult", "Shell", MultiRegions::ePETScMatMultShell)};
 
/**
 * @class GlobalLinSysPETSc
 *
 * Solves a linear system using PETSc.
 */
GlobalLinSysPETSc::GlobalLinSysPETSc(
    const GlobalLinSysKey &pKey, const std::weak_ptr<ExpList> &pExp,
    const std::shared_ptr<AssemblyMap> &pLocToGloMap)
    : GlobalLinSys(pKey, pExp, pLocToGloMap)
{
    // Determine whether to use standard sparse matrix approach or
    // shell.
    m_matMult = pExp.lock()->GetSession()->GetSolverInfoAsEnum<PETScMatMult>(
        "PETScMatMult");
 
    // Check PETSc is initialized. For some reason, this is needed on
    // OS X as logging is not initialized properly in the call within
    // CommMpi.
    PetscBool isInitialized;
    PetscInitialized(&isInitialized);
    if (!isInitialized)
    {
#ifdef NEKTAR_USE_MPI
        std::string commType =
            m_expList.lock()->GetSession()->GetComm()->GetType();
        if (commType.find("MPI") != std::string::npos)
        {
            LibUtilities::CommMpiSharedPtr comm =
                std::static_pointer_cast<LibUtilities::CommMpi>(
                    m_expList.lock()->GetSession()->GetComm());
            PETSC_COMM_WORLD = comm->GetComm();
        }
#endif
        PetscInitializeNoArguments();
    }
 
    // Create matrix
    MatCreate(PETSC_COMM_WORLD, &m_matrix);
}
 
/**
 * @brief Clean up PETSc objects.
 *
 * Note that if SessionReader::Finalize is called before the end of the
 * program, PETSc may have been finalized already, at which point we
 * cannot deallocate our objects. If that's the case we do nothing and
 * let the kernel clear up after us.
 */
GlobalLinSysPETSc::~GlobalLinSysPETSc()
{
    PetscBool isFinalized;
    PetscFinalized(&isFinalized);
 
    // Sometimes, PetscFinalized returns false when (in fact) CommMpi's
    // Finalise routine has been called. We therefore also need to check
    // whether MPI has been finalised. This might arise from the
    // additional call to PetscInitializeNoArguments in the constructor
    // above.
#ifdef NEKTAR_USE_MPI
    int mpiFinal = 0;
    MPI_Finalized(&mpiFinal);
    isFinalized = isFinalized || mpiFinal ? PETSC_TRUE : PETSC_FALSE;
#endif
 
    if (!isFinalized)
    {
        KSPDestroy(&m_ksp);
        PCDestroy(&m_pc);
        MatDestroy(&m_matrix);
        VecDestroy(&m_x);
        VecDestroy(&m_b);
        VecDestroy(&m_locVec);
    }
}
 
/**
 * @brief Solve linear system using PETSc.
 *
 * The general strategy being a PETSc solve is to:
 *
 * - Copy values into the PETSc vector #m_b
 * - Solve the system #m_ksp and place result into #m_x.
 * - Scatter results back into #m_locVec using #m_ctx scatter object.
 * - Copy from #m_locVec to output array #pOutput.
 */
void GlobalLinSysPETSc::v_SolveLinearSystem(
    const int pNumRows, const Array<OneD, const NekDouble> &pInput,
    Array<OneD, NekDouble> &pOutput, const AssemblyMapSharedPtr &locToGloMap,
    const int pNumDir)
{
    const int nHomDofs = pNumRows - pNumDir;
 
    if (!m_precon && m_matMult == ePETScMatMultShell)
    {
        m_precon = CreatePrecon(locToGloMap);
        m_precon->BuildPreconditioner();
    }
 
    Array<OneD, NekDouble> Glo(pNumRows);
    locToGloMap->Assemble(pInput, Glo);
 
    // Populate RHS vector from input
    VecSetValues(m_b, nHomDofs, &m_reorderedMap[0], &Glo[pNumDir],
                 INSERT_VALUES);
 
    // Assemble RHS vector
    VecAssemblyBegin(m_b);
    VecAssemblyEnd(m_b);
 
    // Do system solve
    KSPSolve(m_ksp, m_b, m_x);
 
    KSPConvergedReason reason;
    KSPGetConvergedReason(m_ksp, &reason);
    ASSERTL0(reason > 0, "PETSc solver diverged, reason is: " +
                             std::string(KSPConvergedReasons[reason]));
 
    // Scatter results to local vector
    VecScatterBegin(m_ctx, m_x, m_locVec, INSERT_VALUES, SCATTER_FORWARD);
    VecScatterEnd(m_ctx, m_x, m_locVec, INSERT_VALUES, SCATTER_FORWARD);
 
    // Copy results into output vector
    PetscScalar *tmp;
    VecGetArray(m_locVec, &tmp);
    Vmath::Vcopy(nHomDofs, tmp, 1, &Glo[pNumDir], 1);
    Vmath::Zero(pNumDir, Glo, 1);
    locToGloMap->GlobalToLocal(Glo, pOutput);
    VecRestoreArray(m_locVec, &tmp);
}
 
/**
 * @brief Set up PETSc local (equivalent to Nektar++ global) and global
 * (equivalent to universal) scatter maps.
 *
 * These maps are used in GlobalLinSysPETSc::v_SolveLinearSystem to
 * scatter the solution vector back to each process.
 */
void GlobalLinSysPETSc::SetUpScatter()
{
    const int nHomDofs = m_reorderedMap.size();
 
    // Create local and global numbering systems for vector
    IS isGlobal, isLocal;
    ISCreateGeneral(PETSC_COMM_SELF, nHomDofs, &m_reorderedMap[0],
                    PETSC_COPY_VALUES, &isGlobal);
    ISCreateStride(PETSC_COMM_SELF, nHomDofs, 0, 1, &isLocal);
 
    // Create local vector for output
    VecCreate(PETSC_COMM_SELF, &m_locVec);
    VecSetSizes(m_locVec, nHomDofs, PETSC_DECIDE);
    VecSetFromOptions(m_locVec);
 
    // Create scatter context
    VecScatterCreate(m_x, isGlobal, m_locVec, isLocal, &m_ctx);
 
    // Clean up
    ISDestroy(&isGlobal);
    ISDestroy(&isLocal);
}
 
/**
 * @brief Calculate a reordering of universal IDs for PETSc.
 *
 * PETSc requires a unique, contiguous index of all global and universal
 * degrees of freedom which represents its position inside the
 * matrix. Presently Gs does not guarantee this, so this routine
 * constructs a new universal mapping.
 *
 * @param glo2uniMap    Global to universal map
 * @param glo2unique    Global to unique map
 * @param pLocToGloMap  Assembly map for this system
 */
void GlobalLinSysPETSc::CalculateReordering(
    const Array<OneD, const int> &glo2uniMap,
    const Array<OneD, const int> &glo2unique,
    const AssemblyMapSharedPtr &pLocToGloMap)
{
    LibUtilities::CommSharedPtr vComm =
        m_expList.lock()->GetSession()->GetComm();
 
    const int nDirDofs = pLocToGloMap->GetNumGlobalDirBndCoeffs();
    const int nHomDofs = glo2uniMap.size() - nDirDofs;
    const int nProc    = vComm->GetSize();
    const int rank     = vComm->GetRank();
 
    int n, cnt;
 
    // Count number of unique degrees of freedom on each process.
    m_nLocal = Vmath::Vsum(nHomDofs, glo2unique + nDirDofs, 1);
    m_reorderedMap.resize(nHomDofs);
 
    // Reduce coefficient counts across all processors.
    Array<OneD, int> localCounts(nProc, 0), localOffset(nProc, 0);
    localCounts[rank] = nHomDofs;
    vComm->AllReduce(localCounts, LibUtilities::ReduceSum);
 
    for (n = 1; n < nProc; ++n)
    {
        localOffset[n] = localOffset[n - 1] + localCounts[n - 1];
    }
 
    int totHomDofs = Vmath::Vsum(nProc, localCounts, 1);
    vector<unsigned int> allUniIds(totHomDofs, 0);
 
    // Assemble list of universal IDs
    for (n = 0; n < nHomDofs; ++n)
    {
        int gid                          = n + nDirDofs;
        allUniIds[n + localOffset[rank]] = glo2uniMap[gid];
    }
 
    // Reduce this across processors so that each process has a list of
    // all universal IDs.
    vComm->AllReduce(allUniIds, LibUtilities::ReduceSum);
    std::sort(allUniIds.begin(), allUniIds.end());
    map<int, int> uniIdReorder;
 
    // Renumber starting from 0.
    for (cnt = n = 0; n < allUniIds.size(); ++n)
    {
        if (uniIdReorder.count(allUniIds[n]) > 0)
        {
            continue;
        }
 
        uniIdReorder[allUniIds[n]] = cnt++;
    }
 
    // Populate reordering map.
    for (n = 0; n < nHomDofs; ++n)
    {
        int gid   = n + nDirDofs;
        int uniId = glo2uniMap[gid];
        ASSERTL0(uniIdReorder.count(uniId) > 0, "Error in ordering");
        m_reorderedMap[n] = uniIdReorder[uniId];
    }
}
 
/**
 * @brief Construct PETSc matrix and vector handles.
 *
 * @todo Preallocation should be done at this point, since presently
 *       matrix allocation takes a significant amount of time.
 *
 * @param nGlobal  Number of global degrees of freedom in the system (on
 *                 this processor)
 * @param nDir     Number of Dirichlet degrees of freedom (on this
 *                 processor).
 */
void GlobalLinSysPETSc::SetUpMatVec(int nGlobal, int nDir)
{
    // CREATE VECTORS
    VecCreate(PETSC_COMM_WORLD, &m_x);
    VecSetSizes(m_x, m_nLocal, PETSC_DECIDE);
    VecSetFromOptions(m_x);
    VecDuplicate(m_x, &m_b);
 
    // CREATE MATRICES
    if (m_matMult == ePETScMatMultShell)
    {
        // Create ShellCtx context object which will store the matrix
        // size and a pointer to the linear system. We do this so that
        // we can call a member function to the matrix-vector and
        // preconditioning multiplication in a subclass.
        ShellCtx *ctx1 = new ShellCtx(), *ctx2 = new ShellCtx();
        ctx1->nGlobal = ctx2->nGlobal = nGlobal;
        ctx1->nDir = ctx2->nDir = nDir;
        ctx1->linSys = ctx2->linSys = this;
 
        // Set up MatShell object.
        MatCreateShell(PETSC_COMM_WORLD, m_nLocal, m_nLocal, PETSC_DETERMINE,
                       PETSC_DETERMINE, (void *)ctx1, &m_matrix);
        MatShellSetOperation(m_matrix, MATOP_MULT,
                             (void (*)(void))DoMatrixMultiply);
        MatShellSetOperation(m_matrix, MATOP_DESTROY,
                             (void (*)(void))DoDestroyMatCtx);
 
        // Create a PCShell to go alongside the MatShell.
        PCCreate(PETSC_COMM_WORLD, &m_pc);
#if PETSC_VERSION_GE(3, 5, 0)
        PCSetOperators(m_pc, m_matrix, m_matrix);
#else
        PCSetOperators(m_pc, m_matrix, m_matrix, SAME_NONZERO_PATTERN);
#endif
        PCSetType(m_pc, PCSHELL);
        PCShellSetApply(m_pc, DoPreconditioner);
        PCShellSetDestroy(m_pc, DoDestroyPCCtx);
        PCShellSetContext(m_pc, ctx2);
    }
    else
    {
        // Otherwise we create a PETSc matrix and use MatSetFromOptions
        // so that we can set various options on the command line.
        MatCreate(PETSC_COMM_WORLD, &m_matrix);
        MatSetType(m_matrix, MATAIJ);
        MatSetSizes(m_matrix, m_nLocal, m_nLocal, PETSC_DETERMINE,
                    PETSC_DETERMINE);
        MatSetFromOptions(m_matrix);
        MatSetUp(m_matrix);
    }
}
 
/**
 * @brief Perform either matrix multiplication or preconditioning using
 * Nektar++ routines.
 *
 * This static function uses Nektar++ routines to calculate the
 * matrix-vector product of @p M with @p in, storing the output in @p
 * out.
 *
 * @todo There's a lot of scatters and copies that might possibly be
 *       eliminated to make this more efficient.
 *
 * @param in      Input vector.
 * @param out     Output vector.
 * @param ctx     ShellCtx object that points to our instance of
 *                GlobalLinSysPETSc.
 * @param precon  If true, we apply a preconditioner, if false, we
 *                perform a matrix multiplication.
 */
void GlobalLinSysPETSc::DoNekppOperation(Vec &in, Vec &out, ShellCtx *ctx,
                                         bool precon)
{
    const int nGlobal         = ctx->nGlobal;
    const int nDir            = ctx->nDir;
    const int nHomDofs        = nGlobal - nDir;
    GlobalLinSysPETSc *linSys = ctx->linSys;
 
    // Scatter from PETSc ordering to our local ordering. It's actually
    // unclear whether this step might also do some communication in
    // parallel, which is probably not ideal.
    VecScatterBegin(linSys->m_ctx, in, linSys->m_locVec, INSERT_VALUES,
                    SCATTER_FORWARD);
    VecScatterEnd(linSys->m_ctx, in, linSys->m_locVec, INSERT_VALUES,
                  SCATTER_FORWARD);
 
    // Temporary storage to pass to Nektar++
    Array<OneD, NekDouble> tmpIn(nHomDofs), tmpOut(nHomDofs);
 
    // Get values from input vector and copy to tmpIn.
    PetscScalar *tmpLocIn;
    VecGetArray(linSys->m_locVec, &tmpLocIn);
    Vmath::Vcopy(nHomDofs, tmpLocIn, 1, &tmpIn[0], 1);
    VecRestoreArray(linSys->m_locVec, &tmpLocIn);
 
    // Do matrix multiply in Nektar++, store in tmpOut.
    if (precon)
    {
        linSys->m_precon->DoPreconditioner(tmpIn, tmpOut);
    }
    else
    {
        linSys->v_DoMatrixMultiply(tmpIn, tmpOut);
    }
 
    // Scatter back to PETSc ordering and put in out.
    VecSetValues(out, nHomDofs, &linSys->m_reorderedMap[0], &tmpOut[0],
                 INSERT_VALUES);
    VecAssemblyBegin(out);
    VecAssemblyEnd(out);
}
 
/**
 * @brief Perform matrix multiplication using Nektar++ routines.
 *
 * This static function uses Nektar++ routines to calculate the
 * matrix-vector product of @p M with @p in, storing the output in @p
 * out.
 *
 * @param M    Original MatShell matrix, which stores the ShellCtx
 *             object.
 * @param in   Input vector.
 * @param out  Output vector.
 */
PetscErrorCode GlobalLinSysPETSc::DoMatrixMultiply(Mat M, Vec in, Vec out)
{
    // Grab our shell context from M.
    void *ptr;
    MatShellGetContext(M, &ptr);
    ShellCtx *ctx = (ShellCtx *)ptr;
 
    DoNekppOperation(in, out, ctx, false);
 
    // Must return 0, otherwise PETSc complains.
    return 0;
}
 
/**
 * @brief Apply preconditioning using Nektar++ routines.
 *
 * This static function uses Nektar++ routines to apply the
 * preconditioner stored in GlobalLinSysPETSc::m_precon from the context
 * of @p pc to the vector @p in, storing the output in @p out.
 *
 * @param pc   Preconditioner object that stores the ShellCtx.
 * @param in   Input vector.
 * @param out  Output vector.
 */
PetscErrorCode GlobalLinSysPETSc::DoPreconditioner(PC pc, Vec in, Vec out)
{
    // Grab our PCShell context from pc.
    void *ptr;
    PCShellGetContext(pc, &ptr);
    ShellCtx *ctx = (ShellCtx *)ptr;
 
    DoNekppOperation(in, out, ctx, true);
 
    // Must return 0, otherwise PETSc complains.
    return 0;
}
 
/**
 * @brief Destroy matrix shell context object.
 *
 * Note the matrix shell and preconditioner share a common context so
 * this might have already been deallocated below, in which case we do
 * nothing.
 *
 * @param M  Matrix shell object
 */
PetscErrorCode GlobalLinSysPETSc::DoDestroyMatCtx(Mat M)
{
    void *ptr;
    MatShellGetContext(M, &ptr);
    ShellCtx *ctx = (ShellCtx *)ptr;
    delete ctx;
    return 0;
}
 
/**
 * @brief Destroy preconditioner context object.
 *
 * Note the matrix shell and preconditioner share a common context so
 * this might have already been deallocated above, in which case we do
 * nothing.
 *
 * @param pc  Preconditioner object
 */
PetscErrorCode GlobalLinSysPETSc::DoDestroyPCCtx(PC pc)
{
    void *ptr;
    PCShellGetContext(pc, &ptr);
    ShellCtx *ctx = (ShellCtx *)ptr;
    delete ctx;
    return 0;
}
 
/**
 * @brief Set up KSP solver object.
 *
 * This is reasonably generic setup -- most solver types can be changed
 * using the .petscrc file.
 *
 * @param tolerance  Residual tolerance to converge to.
 */
void GlobalLinSysPETSc::SetUpSolver(NekDouble tolerance)
{
    KSPCreate(PETSC_COMM_WORLD, &m_ksp);
    KSPSetTolerances(m_ksp, tolerance, PETSC_DEFAULT, PETSC_DEFAULT,
                     PETSC_DEFAULT);
    KSPSetFromOptions(m_ksp);
#if PETSC_VERSION_GE(3, 5, 0)
    KSPSetOperators(m_ksp, m_matrix, m_matrix);
#else
    KSPSetOperators(m_ksp, m_matrix, m_matrix, SAME_NONZERO_PATTERN);
#endif
 
    if (m_matMult == ePETScMatMultShell)
    {
        KSPSetPC(m_ksp, m_pc);
    }
}
} // namespace MultiRegions
} // namespace Nektar