SharedObject

Sharing R objects across multiple R processes without memory duplication

Bioconductor version: Release (3.17)

This package is developed for facilitating parallel computing in R. It is capable to create an R object in the shared memory space and share the data across multiple R processes. It avoids the overhead of memory dulplication and data transfer, which make sharing big data object across many clusters possible.

Author: Jiefei Wang [aut, cre], Martin Morgan [aut]

Maintainer: Jiefei Wang <szwjf08 at gmail.com>

Citation (from within R, enter citation("SharedObject")):

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SharedObject")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation


Reference Manual	PDF

Details

biocViews	Infrastructure, Software
Version	1.14.0
In Bioconductor since	BioC 3.10 (R-3.6) (4 years)
License	GPL-3
Depends	R (>= 3.6.0)
Imports	Rcpp, methods, stats, BiocGenerics
Linking To	BH, Rcpp
Suggests	testthat, parallel, knitr, rmarkdown, BiocStyle
System Requirements	GNU make, C++11
Enhances
URL
Bug Reports	https://github.com/Jiefei-Wang/SharedObject/issues

Depends On Me
Imports Me	NewWave
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary	SharedObject_1.14.0.zip (64-bit only)
macOS Binary (x86_64)	SharedObject_1.14.0.tgz
macOS Binary (arm64)	SharedObject_1.14.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/SharedObject
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/SharedObject
Bioc Package Browser	https://code.bioconductor.org/browse/SharedObject/
Package Short Url	https://bioconductor.org/packages/SharedObject/
Package Downloads Report	Download Stats