Exploring and Benchmarking High Performance & Scientific Computing using R R HPC Packages and Lower level compiled languages A Comparative Study
Abstract
R is a robust open-source programming language mainly used for statistical computing . Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel/concurrent computing. This paper presents an overview of techniques for parallel computing with R on ACI (a PSU Infrastructure) and benchmark it with C/C++. We review the scalabilty concern of R, and look at the simplicity of using R as a primary language in Coding for HPC. We will look at the various R packages for HPC like Rmpi, Rcpp, snow and snowfall. We utilize a series of algorithms to benchmark and will illustrate each benchmark with a representative graph for ease of understanding. The paper concludes with a better understanding of which language to use when in high performance computing .
Cite
@article{arxiv.1904.03343,
title = {Exploring and Benchmarking High Performance & Scientific Computing using R R HPC Packages and Lower level compiled languages A Comparative Study},
author = {Rahim K. Charania},
journal= {arXiv preprint arXiv:1904.03343},
year = {2019}
}
Comments
Code accompanying this paper's benchmarks can be found here: https://github.com/RahimCharania/HighPerformanceComputing