SvdMicrobenchmark {RHPCBenchmark}

Conducts a single performance trial with the singular value decomposition (SVD) dense matrix kernel

Description

SvdMicrobenchmark conducts a single performance trial of the SVD dense matrix kernel for the matrix given in the kernelParameters parameter. The function times the single function call svd(kernelParameters$A).

Usage

SvdMicrobenchmark(benchmarkParameters, kernelParameters)

Arguments

benchmarkParameters

an object of type DenseMatrixMicrobenchmark specifying various parameters for microbenchmarking the dense matrix kernel

kernelParameters

a list of matrices or vectors to be used as input to the dense matrix kernel

Examples

## Not run: 
# Allocate input to the singular value decomposition microbenchmark for the
# first matrix size to be tested
microbenchmarks <- GetDenseMatrixDefaultMicrobenchmarks()
kernelParameters <- SvdAllocator(microbenchmarks[["svd"]], 1)
# Execute the microbenchmark
timings <- SvdMicrobenchmark(microbenchmarks[["svd"]], kernelParameters)

## End(Not run)