knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
easypar
makes it easy to implement parallel computations in R. If youo have a function that
carries out your desired computation, easypar
will take care of the burden of turning that function into a runnable parallel piece of R code. The package offers two possible solutions for parallelisation. It can generate a parallel function call exploiting the foreach
and
doParallel
paradigms for parallel computing, or can generate a ready-to-use array job for the popular LSF (Platform Load Sharing Facility) and Slurm workload manages for distributed high performance computing. With easypar
, speeding up R computations through parallelism is a trivial task.
# install.packages("devtools") devtools::install_github("caravagnalab/easypar")
Cancer Data Science (CDS) Laboratory, University of Trieste, Italy.
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