RHPCBenchmark: Benchmarks for High-Performance Computing Environments

Microbenchmarks for determining the run time performance of aspects of the R programming environment and packages relevant to high-performance computation. The benchmarks are divided into three categories: dense matrix linear algebra kernels, sparse matrix linear algebra kernels, and machine learning functionality.

Version: 0.1.0
Depends: R (≥ 3.3.1), methods
Imports: utils, mvtnorm, cluster, Matrix
Suggests: knitr, rmarkdown
Published: 2017-05-23
Author: James McCombs [aut, cre]
Maintainer: James McCombs <jmccombs at iu.edu>
License: Apache License 2.0 | file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: RHPCBenchmark results

Documentation:

Reference manual: RHPCBenchmark.pdf
Vignettes: R HPC Benchmark

Downloads:

Package source: RHPCBenchmark_0.1.0.tar.gz
Windows binaries: r-devel: RHPCBenchmark_0.1.0.zip, r-release: RHPCBenchmark_0.1.0.zip, r-oldrel: RHPCBenchmark_0.1.0.zip
macOS binaries: r-release (arm64): RHPCBenchmark_0.1.0.tgz, r-oldrel (arm64): RHPCBenchmark_0.1.0.tgz, r-release (x86_64): RHPCBenchmark_0.1.0.tgz, r-oldrel (x86_64): RHPCBenchmark_0.1.0.tgz

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