SvdMicrobenchmark: Conducts a single performance trial with the singular value...

In RHPCBenchmark: Benchmarks for High-Performance Computing Environments

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)

RHPCBenchmark documentation built on May 2, 2019, 6:40 a.m.