README.md
In berndbischl/rscimark: SciMark 2.0 Benchmark for Scientific and Numerical Computing
rscimark
This package offers a single function rscimark, which is a simple wrapper
around the ANSI C version of the SciMark2 benchmark. SciMark is a benchmark for numerical computing and scientific computing. Concicely the
performance measurements for the computational kernels Fast Fourier Transformation (FFT), Gauss-Seidel relaxation, Sparse matrix-multiply, Monte Carlo integration, and dense LU factorization are used as indicators for the performance.
Installation
Run the following command in R to install the current GitHub version. For further installation instructions take a glance at our guide.
devtools::install_github("berndbischl/rscimark")
HowTo
To run the SciMark 2.0 benchmark from within R just open a R session and type
the following:
library(rscimark)
rscimark()
To address performance of the memory subsystem with problems sizes which to not fit in the cache set the large parameter to TRUE.
rscimark(large = TRUE)
berndbischl/rscimark documentation built on May 12, 2019, 7:24 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
rscimark
This package offers a single function rscimark, which is a simple wrapper
around the ANSI C version of the SciMark2 benchmark. SciMark is a benchmark for numerical computing and scientific computing. Concicely the
performance measurements for the computational kernels Fast Fourier Transformation (FFT), Gauss-Seidel relaxation, Sparse matrix-multiply, Monte Carlo integration, and dense LU factorization are used as indicators for the performance.
Installation
Run the following command in R to install the current GitHub version. For further installation instructions take a glance at our guide.
devtools::install_github("berndbischl/rscimark")
HowTo
To run the SciMark 2.0 benchmark from within R just open a R session and type the following:
library(rscimark)
rscimark()
To address performance of the memory subsystem with problems sizes which to not fit in the cache set the large parameter to TRUE.
rscimark(large = TRUE)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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