8_benchmark_parallel.cpp

#include <openPMD/openPMD.hpp>
#include <openPMD/benchmark/mpi/MPIBenchmark.hpp>
#include <openPMD/benchmark/mpi/RandomDatasetFiller.hpp>
#include <openPMD/benchmark/mpi/OneDimensionalBlockSlicer.hpp>

#if openPMD_HAVE_MPI
#   include <mpi.h>
#endif

#include <iostream>
#include <string>
#include <vector>


#if openPMD_HAVE_MPI
inline void
print_help( std::string const program_name )
{
    std::cout << "Usage: " << program_name << "\n";
    std::cout << "Run a simple parallel write and read benchmark.\n\n";
    std::cout << "Options:\n";
    std::cout << "    -w, --weak    run a weak scaling (default: strong scaling)\n";
    std::cout << "    -h, --help    display this help and exit\n";
    std::cout << "    -v, --version output version information and exit\n";
    std::cout << "\n";
    std::cout << "Examples:\n";
    std::cout << "    " << program_name << " --weak  # for a weak-scaling\n";
    std::cout << "    " << program_name << "  # for a strong scaling\n";
}

inline void
print_version( std::string const program_name )
{
    std::cout << program_name << " (openPMD-api) "
              << openPMD::getVersion() << "\n";
    std::cout << "Copyright 2017-2021 openPMD contributors\n";
    std::cout << "Authors: Franz Poeschel, Axel Huebl et al.\n";
    std::cout << "License: LGPLv3+\n";
    std::cout << "This is free software: you are free to change and redistribute it.\n"
                 "There is NO WARRANTY, to the extent permitted by law.\n";
}

int main(
    int argc,
    char *argv[]
)
{
    using namespace std;
    MPI_Init(
        &argc,
        &argv
    );

    // CLI parsing
    std::vector< std::string > str_argv;
    for( int i = 0; i < argc; ++i ) str_argv.emplace_back( argv[i] );
    bool weak_scaling = false;

    for (int c = 1; c < int(argc); c++) {
        if (std::string("--help") == argv[c] || std::string("-h") == argv[c]) {
            print_help(argv[0]);
            return 0;
        }
        if (std::string("--version") == argv[c] || std::string("-v") == argv[c]) {
            print_version(argv[0]);
            return 0;
        }
        if (std::string("--weak") == argv[c] || std::string("-w") == argv[c]) {
            weak_scaling = true;
        }
    }

    if (argc > 2) {
        std::cerr << "Too many arguments! See: " << argv[0] << " --help\n";
        return 1;
    }

    // For simplicity, use only one datatype in this benchmark.
    // Note that a single Benchmark object can be used to configure
    // multiple different benchmark runs with different datatypes,
    // given that you provide it with an appropriate DatasetFillerProvider
    // (template parameter of the Benchmark class).
    using type = uint64_t;
#if openPMD_HAVE_ADIOS1 || openPMD_HAVE_ADIOS2 || openPMD_HAVE_HDF5
    openPMD::Datatype dt = openPMD::determineDatatype<type>();
#endif


    int rank, size;
    MPI_Comm_rank( MPI_COMM_WORLD, &rank );
    MPI_Comm_size( MPI_COMM_WORLD, &size );
    const unsigned scale_up = weak_scaling ? unsigned( size ) : 1u;

    // Total (in this case 3D) dataset across all MPI ranks.
    // Will be the same for all configured benchmarks.
    openPMD::Extent total{
        100 * scale_up,
        100,
        1000
    };

    // The blockslicer assigns to each rank its part of the dataset. The rank will
    // write to and read from that part. OneDimensionalBlockSlicer is a simple
    // implementation of the BlockSlicer abstract class that will divide the
    // dataset into hyperslab along one given dimension.
    // If you wish to partition your dataset in a different manner, you can
    // replace this with your own implementation of BlockSlicer.
    auto blockSlicer = std::make_shared<openPMD::OneDimensionalBlockSlicer>(0);

    // Set up the DatasetFiller. The benchmarks will later inquire the DatasetFiller
    // to get data for writing.
    std::uniform_int_distribution<type> distr(
        0,
        200000000
    );
    openPMD::RandomDatasetFiller<decltype(distr)> df{distr};

    // The Benchmark class will in principle allow a user to configure
    // runs that write and read different datatypes.
    // For this, the class is templated with a type called DatasetFillerProvider.
    // This class serves as a factory for DatasetFillers for concrete types and
    // should have a templated operator()<T>() returning a value
    // that can be dynamically casted to a std::shared_ptr<openPMD::DatasetFiller<T>>
    // The openPMD API provides only one implementation of a DatasetFillerProvider,
    // namely the SimpleDatasetFillerProvider being used in this example.
    // Its purpose is to leverage a DatasetFiller for a concrete type (df in this example)
    // to a DatasetFillerProvider whose operator()<T>() will fail during runtime if T does
    // not correspond with the underlying DatasetFiller.
    // Use this implementation if you only wish to run the benchmark for one Datatype,
    // otherwise provide your own implementation of DatasetFillerProvider.
    openPMD::SimpleDatasetFillerProvider<decltype(df)> dfp{df};

    // Create the Benchmark object. The file name (first argument) will be extended
    // with the backends' file extensions.
    openPMD::MPIBenchmark<decltype(dfp)> benchmark{
        "../benchmarks/benchmark",
        total,
        std::dynamic_pointer_cast<openPMD::BlockSlicer>(blockSlicer),
        dfp,
    };

    // Add benchmark runs to be executed. This will only store the configuration and not
    // run the benchmark yet. Each run is configured by:
    // * The compression scheme to use (first two parameters). The first parameter chooses
    //   the compression scheme, the second parameter is the compression level.
    // * The backend (by file extension).
    // * The datatype to use for this run.
    // * The number of iterations. Effectively, the benchmark will be repeated for this many
    //   times.
#if openPMD_HAVE_ADIOS1 || openPMD_HAVE_ADIOS2
    benchmark.addConfiguration(
        R"({"adios2": {"dataset":{"operators":[{"type": "blosc"}]}}})",
        "bp",
        dt,
        10 );
#endif
#if openPMD_HAVE_HDF5
    benchmark.addConfiguration( "{}", "h5", dt, 10 );
#endif

    // Execute all previously configured benchmarks. Will return a MPIBenchmarkReport object
    // with write and read times for each configured run.
    // Take notice that results will be collected into the root rank's report object, the other
    // ranks' reports will be empty. The root rank is specified by the first parameter of runBenchmark,
    // the default being 0.
    auto res =
        benchmark.runBenchmark<std::chrono::high_resolution_clock>();

    if( rank == 0 )
    {
        for( auto it = res.durations.begin();
             it != res.durations.end();
             it++ )
        {
            auto time = it->second;
            std::cout << "on rank " << std::get<res.RANK>(it->first)
                      << "\t with backend "
                      << std::get<res.BACKEND>(it->first)
                      << "\twrite time: "
                      << std::chrono::duration_cast<std::chrono::milliseconds>(
                          time.first
                      ).count() << "\tread time: "
                      << std::chrono::duration_cast<std::chrono::milliseconds>(
                          time.second
                      ).count() << std::endl;
        }
    }

    MPI_Finalize();
}
#else
int main(void)
{
    return 0;
}
#endif