The preconditioner-export program

The preconditioner export example..

This example depends on simple-solver.

Table of contents
Introduction About the example The commented program	Results Comments about programming and debugging The plain program

Introduction

About the example

This example shows how to explicitly generate and store preconditioners for a given matrix. It can also be used to inspect and debug the preconditioner generation.

The commented program

#include <ginkgo/ginkgo.hpp>
 
 
#include <fstream>
#include <functional>
#include <iostream>
#include <map>
#include <memory>
#include <string>
 
 
const std::map<std::string, std::function<std::shared_ptr<gko::Executor>()>>
    executors{{"reference", [] { return gko::ReferenceExecutor::create(); }},
              {"omp", [] { return gko::OmpExecutor::create(); }},
              {"cuda",
               [] {
                   return gko::CudaExecutor::create(
                       0, gko::ReferenceExecutor::create());
               }},
              {"hip",
               [] {
                   return gko::HipExecutor::create(
                       0, gko::ReferenceExecutor::create());
               }},
              {"dpcpp", [] {
                   return gko::DpcppExecutor::create(
                       0, gko::ReferenceExecutor::create());
               }}};
 
 
void output(gko::ptr_param<const gko::WritableToMatrixData<double, int>> mtx,
            std::string name)
{
    std::ofstream stream{name};
    std::cerr << "Writing " << name << std::endl;
    gko::write(stream, mtx, gko::layout_type::coordinate);
}
 
 
template <typename Function>
auto try_generate(Function fun) -> decltype(fun())
{
    decltype(fun()) result;
    try {
        result = fun();
    } catch (const gko::Error& err) {
        std::cerr << "Error: " << err.what() << '\n';
        std::exit(-1);
    }
    return result;
}
 
 
int main(int argc, char* argv[])
{

print usage message

if (argc < 2 || executors.find(argv[1]) == executors.end()) {
    std::cerr << "Usage: executable"
              << " <reference|omp|cuda|hip|dpcpp> [<matrix-file>] "
                 "[<jacobi|ilu|parilu|parilut|ilu-isai|parilu-isai|parilut-"
                 "isai] [<preconditioner args>]\n";
    std::cerr << "Jacobi parameters: [<max-block-size>] [<accuracy>] "
                 "[<storage-optimization:auto|0|1|2>]\n";
    std::cerr << "ParILU parameters: [<iteration-count>]\n";
    std::cerr
        << "ParILUT parameters: [<iteration-count>] [<fill-in-limit>]\n";
    std::cerr << "ILU-ISAI parameters: [<sparsity-power>]\n";
    std::cerr << "ParILU-ISAI parameters: [<iteration-count>] "
                 "[<sparsity-power>]\n";
    std::cerr << "ParILUT-ISAI parameters: [<iteration-count>] "
                 "[<fill-in-limit>] [<sparsity-power>]\n";
    return -1;
}

generate executor based on first argument

auto exec = try_generate([&] { return executors.at(argv[1])(); });

set matrix and preconditioner name with default values

std::string matrix = argc < 3 ? "data/A.mtx" : argv[2];
std::string precond = argc < 4 ? "jacobi" : argv[3];

load matrix file into Csr format

auto mtx = gko::share(try_generate([&] {
    std::ifstream mtx_stream{matrix};
    if (!mtx_stream) {
        throw GKO_STREAM_ERROR("Unable to open matrix file");
    }
    std::cerr << "Reading " << matrix << std::endl;
    return gko::read<gko::matrix::Csr<>>(mtx_stream, exec);
}));

concatenate remaining arguments for filename

std::string output_suffix;
for (auto i = 4; i < argc; ++i) {
    output_suffix = output_suffix + "-" + argv[i];
}

handle different preconditioners

if (precond == "jacobi") {

jacobi: max_block_size, accuracy, storage_optimization

    auto factory_parameter = gko::preconditioner::Jacobi<>::build();
    if (argc >= 5) {
        factory_parameter.with_max_block_size(
            static_cast<gko::uint32>(std::stoi(argv[4])));
    }
    if (argc >= 6) {
        factory_parameter.with_accuracy(std::stod(argv[5]));
    }
    if (argc >= 7) {
        factory_parameter.with_storage_optimization(
            std::string{argv[6]} == "auto"
                ? gko::precision_reduction::autodetect()
                : gko::precision_reduction(0, std::stoi(argv[6])));
    }
    auto factory = factory_parameter.on(exec);
    auto jacobi = try_generate([&] { return factory->generate(mtx); });
    output(jacobi, matrix + ".jacobi" + output_suffix);
} else if (precond == "ilu") {

ilu: no parameters

    auto ilu = gko::as<gko::Composition<>>(try_generate([&] {
        return gko::factorization::Ilu<>::build().on(exec)->generate(mtx);
    }));
    output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[0]),
           matrix + ".ilu-l");
    output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[1]),
           matrix + ".ilu-u");
} else if (precond == "parilu") {

parilu: iterations

    auto factory_parameter = gko::factorization::ParIlu<>::build();
    if (argc >= 5) {
        factory_parameter.with_iterations(
            static_cast<gko::size_type>(std::stoi(argv[4])));
    }
    auto factory = factory_parameter.on(exec);
    auto ilu = gko::as<gko::Composition<>>(
        try_generate([&] { return factory->generate(mtx); }));
    output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[0]),
           matrix + ".parilu" + output_suffix + "-l");
    output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[1]),
           matrix + ".parilu" + output_suffix + "-u");
} else if (precond == "parilut") {

parilut: iterations, fill-in limit

    auto factory_parameter = gko::factorization::ParIlut<>::build();
    if (argc >= 5) {
        factory_parameter.with_iterations(
            static_cast<gko::size_type>(std::stoi(argv[4])));
    }
    if (argc >= 6) {
        factory_parameter.with_fill_in_limit(std::stod(argv[5]));
    }
    auto factory = factory_parameter.on(exec);
    auto ilut = gko::as<gko::Composition<>>(
        try_generate([&] { return factory->generate(mtx); }));
    output(gko::as<gko::matrix::Csr<>>(ilut->get_operators()[0]),
           matrix + ".parilut" + output_suffix + "-l");
    output(gko::as<gko::matrix::Csr<>>(ilut->get_operators()[1]),
           matrix + ".parilut" + output_suffix + "-u");
} else if (precond == "ilu-isai") {

ilu-isai: sparsity power

    auto fact_factory =
        gko::share(gko::factorization::Ilu<>::build().on(exec));
    int sparsity_power = 1;
    if (argc >= 5) {
        sparsity_power = std::stoi(argv[4]);
    }
    auto factory =
        gko::preconditioner::Ilu<gko::preconditioner::LowerIsai<>,
                                 gko::preconditioner::UpperIsai<>>::build()
            .with_factorization(fact_factory)
            .with_l_solver(gko::preconditioner::LowerIsai<>::build()
                               .with_sparsity_power(sparsity_power))
            .with_u_solver(gko::preconditioner::UpperIsai<>::build()
                               .with_sparsity_power(sparsity_power))
            .on(exec);
    auto ilu_isai = try_generate([&] { return factory->generate(mtx); });
    output(ilu_isai->get_l_solver()->get_approximate_inverse(),
           matrix + ".ilu-isai" + output_suffix + "-l");
    output(ilu_isai->get_u_solver()->get_approximate_inverse(),
           matrix + ".ilu-isai" + output_suffix + "-u");
} else if (precond == "parilu-isai") {

parilu-isai: iterations, sparsity power

    auto fact_parameter = gko::factorization::ParIlu<>::build();
    int sparsity_power = 1;
    if (argc >= 5) {
        fact_parameter.with_iterations(
            static_cast<gko::size_type>(std::stoi(argv[4])));
    }
    if (argc >= 6) {
        sparsity_power = std::stoi(argv[5]);
    }
    auto fact_factory = gko::share(fact_parameter.on(exec));
    auto factory =
        gko::preconditioner::Ilu<gko::preconditioner::LowerIsai<>,
                                 gko::preconditioner::UpperIsai<>>::build()
            .with_factorization(fact_factory)
            .with_l_solver(gko::preconditioner::LowerIsai<>::build()
                               .with_sparsity_power(sparsity_power))
            .with_u_solver(gko::preconditioner::UpperIsai<>::build()
                               .with_sparsity_power(sparsity_power))
            .on(exec);
    auto ilu_isai = try_generate([&] { return factory->generate(mtx); });
    output(ilu_isai->get_l_solver()->get_approximate_inverse(),
           matrix + ".parilu-isai" + output_suffix + "-l");
    output(ilu_isai->get_u_solver()->get_approximate_inverse(),
           matrix + ".parilu-isai" + output_suffix + "-u");
} else if (precond == "parilut-isai") {

parilut-isai: iterations, fill-in limit, sparsity power

        auto fact_parameter = gko::factorization::ParIlut<>::build();
        int sparsity_power = 1;
        if (argc >= 5) {
            fact_parameter.with_iterations(
                static_cast<gko::size_type>(std::stoi(argv[4])));
        }
        if (argc >= 6) {
            fact_parameter.with_fill_in_limit(std::stod(argv[5]));
        }
        if (argc >= 7) {
            sparsity_power = std::stoi(argv[6]);
        }
        auto fact_factory = gko::share(fact_parameter.on(exec));
        auto factory =
            gko::preconditioner::Ilu<gko::preconditioner::LowerIsai<>,
                                     gko::preconditioner::UpperIsai<>>::build()
                .with_factorization(fact_factory)
                .with_l_solver(gko::preconditioner::LowerIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .with_u_solver(gko::preconditioner::UpperIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .on(exec);
        auto ilu_isai = try_generate([&] { return factory->generate(mtx); });
        output(ilu_isai->get_l_solver()->get_approximate_inverse(),
               matrix + ".parilut-isai" + output_suffix + "-l");
        output(ilu_isai->get_u_solver()->get_approximate_inverse(),
               matrix + ".parilut-isai" + output_suffix + "-u");
    }
}

Results

This is the expected output:

Usage: ./preconditioner-export <reference|omp|cuda|hip|dpcpp> [<matrix-file>] [<jacobi|ilu|parilu|parilut|ilu-isai|parilu-isai|parilut-isai] [<preconditioner args>]
Jacobi parameters: [<max-block-size>] [<accuracy>] [<storage-optimization:auto|0|1|2>]
ParILU parameters: [<iteration-count>]
ParILUT parameters: [<iteration-count>] [<fill-in-limit>]
ILU-ISAI parameters: [<sparsity-power>]
ParILU-ISAI parameters: [<iteration-count>] [<sparsity-power>]
ParILUT-ISAI parameters: [<iteration-count>] [<fill-in-limit>] [<sparsity-power>]

When specifying an executor:

Reading data/A.mtx
Writing data/A.mtx.jacobi

Comments about programming and debugging

The plain program

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#include <ginkgo/ginkgo.hpp>
 
 
#include <fstream>
#include <functional>
#include <iostream>
#include <map>
#include <memory>
#include <string>
 
 
const std::map<std::string, std::function<std::shared_ptr<gko::Executor>()>>
    executors{{"reference", [] { return gko::ReferenceExecutor::create(); }},
              {"omp", [] { return gko::OmpExecutor::create(); }},
              {"cuda",
               [] {
                   return gko::CudaExecutor::create(
                       0, gko::ReferenceExecutor::create());
               }},
              {"hip",
               [] {
                   return gko::HipExecutor::create(
                       0, gko::ReferenceExecutor::create());
               }},
              {"dpcpp", [] {
                   return gko::DpcppExecutor::create(
                       0, gko::ReferenceExecutor::create());
               }}};
 
 
void output(gko::ptr_param<const gko::WritableToMatrixData<double, int>> mtx,
            std::string name)
{
    std::ofstream stream{name};
    std::cerr << "Writing " << name << std::endl;
    gko::write(stream, mtx, gko::layout_type::coordinate);
}
 
 
template <typename Function>
auto try_generate(Function fun) -> decltype(fun())
{
    decltype(fun()) result;
    try {
        result = fun();
    } catch (const gko::Error& err) {
        std::cerr << "Error: " << err.what() << '\n';
        std::exit(-1);
    }
    return result;
}
 
 
int main(int argc, char* argv[])
{
    if (argc < 2 || executors.find(argv[1]) == executors.end()) {
        std::cerr << "Usage: executable"
                  << " <reference|omp|cuda|hip|dpcpp> [<matrix-file>] "
                     "[<jacobi|ilu|parilu|parilut|ilu-isai|parilu-isai|parilut-"
                     "isai] [<preconditioner args>]\n";
        std::cerr << "Jacobi parameters: [<max-block-size>] [<accuracy>] "
                     "[<storage-optimization:auto|0|1|2>]\n";
        std::cerr << "ParILU parameters: [<iteration-count>]\n";
        std::cerr
            << "ParILUT parameters: [<iteration-count>] [<fill-in-limit>]\n";
        std::cerr << "ILU-ISAI parameters: [<sparsity-power>]\n";
        std::cerr << "ParILU-ISAI parameters: [<iteration-count>] "
                     "[<sparsity-power>]\n";
        std::cerr << "ParILUT-ISAI parameters: [<iteration-count>] "
                     "[<fill-in-limit>] [<sparsity-power>]\n";
        return -1;
    }
 
    auto exec = try_generate([&] { return executors.at(argv[1])(); });
 
    std::string matrix = argc < 3 ? "data/A.mtx" : argv[2];
    std::string precond = argc < 4 ? "jacobi" : argv[3];
 
    auto mtx = gko::share(try_generate([&] {
        std::ifstream mtx_stream{matrix};
        if (!mtx_stream) {
            throw GKO_STREAM_ERROR("Unable to open matrix file");
        }
        std::cerr << "Reading " << matrix << std::endl;
        return gko::read<gko::matrix::Csr<>>(mtx_stream, exec);
    }));
 
    std::string output_suffix;
    for (auto i = 4; i < argc; ++i) {
        output_suffix = output_suffix + "-" + argv[i];
    }
 
    if (precond == "jacobi") {
        auto factory_parameter = gko::preconditioner::Jacobi<>::build();
        if (argc >= 5) {
            factory_parameter.with_max_block_size(
                static_cast<gko::uint32>(std::stoi(argv[4])));
        }
        if (argc >= 6) {
            factory_parameter.with_accuracy(std::stod(argv[5]));
        }
        if (argc >= 7) {
            factory_parameter.with_storage_optimization(
                std::string{argv[6]} == "auto"
                    ? gko::precision_reduction::autodetect()
                    : gko::precision_reduction(0, std::stoi(argv[6])));
        }
        auto factory = factory_parameter.on(exec);
        auto jacobi = try_generate([&] { return factory->generate(mtx); });
        output(jacobi, matrix + ".jacobi" + output_suffix);
    } else if (precond == "ilu") {
        auto ilu = gko::as<gko::Composition<>>(try_generate([&] {
            return gko::factorization::Ilu<>::build().on(exec)->generate(mtx);
        }));
        output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[0]),
               matrix + ".ilu-l");
        output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[1]),
               matrix + ".ilu-u");
    } else if (precond == "parilu") {
        auto factory_parameter = gko::factorization::ParIlu<>::build();
        if (argc >= 5) {
            factory_parameter.with_iterations(
                static_cast<gko::size_type>(std::stoi(argv[4])));
        }
        auto factory = factory_parameter.on(exec);
        auto ilu = gko::as<gko::Composition<>>(
            try_generate([&] { return factory->generate(mtx); }));
        output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[0]),
               matrix + ".parilu" + output_suffix + "-l");
        output(gko::as<gko::matrix::Csr<>>(ilu->get_operators()[1]),
               matrix + ".parilu" + output_suffix + "-u");
    } else if (precond == "parilut") {
        auto factory_parameter = gko::factorization::ParIlut<>::build();
        if (argc >= 5) {
            factory_parameter.with_iterations(
                static_cast<gko::size_type>(std::stoi(argv[4])));
        }
        if (argc >= 6) {
            factory_parameter.with_fill_in_limit(std::stod(argv[5]));
        }
        auto factory = factory_parameter.on(exec);
        auto ilut = gko::as<gko::Composition<>>(
            try_generate([&] { return factory->generate(mtx); }));
        output(gko::as<gko::matrix::Csr<>>(ilut->get_operators()[0]),
               matrix + ".parilut" + output_suffix + "-l");
        output(gko::as<gko::matrix::Csr<>>(ilut->get_operators()[1]),
               matrix + ".parilut" + output_suffix + "-u");
    } else if (precond == "ilu-isai") {
        auto fact_factory =
            gko::share(gko::factorization::Ilu<>::build().on(exec));
        int sparsity_power = 1;
        if (argc >= 5) {
            sparsity_power = std::stoi(argv[4]);
        }
        auto factory =
            gko::preconditioner::Ilu<gko::preconditioner::LowerIsai<>,
                                     gko::preconditioner::UpperIsai<>>::build()
                .with_factorization(fact_factory)
                .with_l_solver(gko::preconditioner::LowerIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .with_u_solver(gko::preconditioner::UpperIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .on(exec);
        auto ilu_isai = try_generate([&] { return factory->generate(mtx); });
        output(ilu_isai->get_l_solver()->get_approximate_inverse(),
               matrix + ".ilu-isai" + output_suffix + "-l");
        output(ilu_isai->get_u_solver()->get_approximate_inverse(),
               matrix + ".ilu-isai" + output_suffix + "-u");
    } else if (precond == "parilu-isai") {
        auto fact_parameter = gko::factorization::ParIlu<>::build();
        int sparsity_power = 1;
        if (argc >= 5) {
            fact_parameter.with_iterations(
                static_cast<gko::size_type>(std::stoi(argv[4])));
        }
        if (argc >= 6) {
            sparsity_power = std::stoi(argv[5]);
        }
        auto fact_factory = gko::share(fact_parameter.on(exec));
        auto factory =
            gko::preconditioner::Ilu<gko::preconditioner::LowerIsai<>,
                                     gko::preconditioner::UpperIsai<>>::build()
                .with_factorization(fact_factory)
                .with_l_solver(gko::preconditioner::LowerIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .with_u_solver(gko::preconditioner::UpperIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .on(exec);
        auto ilu_isai = try_generate([&] { return factory->generate(mtx); });
        output(ilu_isai->get_l_solver()->get_approximate_inverse(),
               matrix + ".parilu-isai" + output_suffix + "-l");
        output(ilu_isai->get_u_solver()->get_approximate_inverse(),
               matrix + ".parilu-isai" + output_suffix + "-u");
    } else if (precond == "parilut-isai") {
        auto fact_parameter = gko::factorization::ParIlut<>::build();
        int sparsity_power = 1;
        if (argc >= 5) {
            fact_parameter.with_iterations(
                static_cast<gko::size_type>(std::stoi(argv[4])));
        }
        if (argc >= 6) {
            fact_parameter.with_fill_in_limit(std::stod(argv[5]));
        }
        if (argc >= 7) {
            sparsity_power = std::stoi(argv[6]);
        }
        auto fact_factory = gko::share(fact_parameter.on(exec));
        auto factory =
            gko::preconditioner::Ilu<gko::preconditioner::LowerIsai<>,
                                     gko::preconditioner::UpperIsai<>>::build()
                .with_factorization(fact_factory)
                .with_l_solver(gko::preconditioner::LowerIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .with_u_solver(gko::preconditioner::UpperIsai<>::build()
                                   .with_sparsity_power(sparsity_power))
                .on(exec);
        auto ilu_isai = try_generate([&] { return factory->generate(mtx); });
        output(ilu_isai->get_l_solver()->get_approximate_inverse(),
               matrix + ".parilut-isai" + output_suffix + "-l");
        output(ilu_isai->get_u_solver()->get_approximate_inverse(),
               matrix + ".parilut-isai" + output_suffix + "-u");
    }
}