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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 |
| Reference manual: | RHPCBenchmark.pdf |
| Vignettes: |
R HPC Benchmark |
| 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 |
Please use the canonical form https://CRAN.R-project.org/package=RHPCBenchmark to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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