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RHPCBenchmark (version 0.1.0)

MicrobenchmarkSparseMatrixKernel: Performs microbenchmarking of a sparse matrix linear algebra kernel

Description

MicrobenchmarkSparseMatrixKernel performs microbenchmarking of a sparse matrix linear algebra kernel for several matrix dimensions

Usage

MicrobenchmarkSparseMatrixKernel(benchmarkParameters, numberOfThreads,
  resultsDirectory, runIdentifier)

Arguments

benchmarkParameters
an object of type SparseMatrixMicrobenchmark specifying the matrix dimensions of matrices to be tested and the number of performance trials to perform for each matrix dimension.
numberOfThreads
the number of threads the microbenchmark is being performed with. The value is for informational purposes only and does not effect the number threads the kernel is executed with.
resultsDirectory
a character string specifying the directory where all of the CSV performance results files will be saved
runIdentifier
a character string specifying the suffix to be appended to the base of the file name of the output CSV format files

Value

a dataframe containing the performance trial times for each matrix tested, that is the raw performance data before averaging. The columns of the data frame are the following:
BenchmarkName
The name of the microbenchmark
NumberOfRows
An integer specifying the expected number of rows in the input sparse matrix
NumberOfColumns
An integer specifying the expected number of columns in the input sparse matrix
UserTime
The amount of time spent in user-mode code within the microbenchmarked code
SystemTime
The amount of time spent in the kernel within the process
WallClockTime
The total time spent to complete the performance trial
DateStarted
The date and time the performance trial was commenced
DateFinished
The date and time the performance trial ended

Details

This function performs microbenchmarking of a sparse matrix linear algebra kernel for several matrix dimensions and a given number of threads. The kernel to be performance tested, the matrix dimensions to be tested, and other parameters specifying how the kernel is to be benchmarked are given in the input object benchmarkParameters which is an instance of the class SparseMatrixMicrobenchmark. For each matrix dimension to be tested, the run time performance of the kernel is averaged over multiple runs. The kernel can also be executed with multiple threads if the kernel supports multithreading. See SparseMatrixMicrobenchmark for more details on the benchmarking parameters.