Teamwork4R/Teamwork4R: Easy to Use Distributed Computing System
Version 0.2.0

The R package provides an easy-to-use method for Distributed computing. There are several parallel frameworks can make good use of CPU cores and GPUs of a computer. But we still are stuck with one computer. This package propose an easy way to run R code on multiple computers in parallel. It’s easy for developers. The interface is designed use S3 methodology which R developer should be familiar with, no complicate concepts involved. It’s easy to bring in extra computing resources. To contribute computing resources, all one has to do is to run a one-line script which can be stopped at any time. In another word, any one/computer can join and contribute at any time easily and freely. All kinds of computers are welcomed, servers, office computers, personal computers, even Paspberry PI. This is possible because connections between computers (nodes/clusters) are designed to be weak. Damages caused by unstable network connections and unpredictable behaviors of joining computers will be detected and fixed automatically.

Getting started

Package details

AuthorGuocai Chen Developer [aut, cre], Wei Zhang Developer [aut]
MaintainerGuocai Chen<[email protected]>
LicenseLicense: GPL-2
Version0.2.0
URL https://github.com/Teamwork4R/Teamwork4R
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("Teamwork4R/Teamwork4R")
Teamwork4R/Teamwork4R documentation built on May 10, 2017, 4:40 p.m.