memshare: Shared Memory Multithreading

This project extends 'R' with a mechanism for efficient parallel data access by utilizing 'C++' shared memory. Large data objects can be accessed and manipulated directly from 'R' without redundant copying, providing both speed and memory efficiency. Memshare was published in Thrun, M.C., Märte J.: "Memshare: Memory Sharing for Multicore Computation in R with an Application to Feature Selection by Mutual Information using PDE" (2026), R Journal, <doi:10.32614/RJ-2025-043>.

Version: 1.1.1
Depends: R (≥ 4.3.0)
Imports: Rcpp (≥ 1.0.14), parallel
LinkingTo: Rcpp
Suggests: ScatterDensity (≥ 0.1.1), DataVisualizations (≥ 1.1.5), mpmi, rmarkdown (≥ 0.9), knitr (≥ 1.12), testthat (≥ 3.0.0)
Published: 2026-05-04
DOI: 10.32614/CRAN.package.memshare
Author: Julian Märte ORCID iD [aut, ctr], Romain Francois [ctb], Michael Thrun ORCID iD [aut, ths, rev, cph, cre]
Maintainer: Michael Thrun <m.thrun at gmx.net>
BugReports: https://github.com/Mthrun/memshare/issues
License: GPL-3
URL: https://www.iap-gmbh.de
NeedsCompilation: yes
SystemRequirements: C++17
Citation: memshare citation info
Materials: README
CRAN checks: memshare results

Documentation:

Reference manual: memshare.html , memshare.pdf
Vignettes: memshare: Fast Shared-Memory Parallelism in R (source)

Downloads:

Package source: memshare_1.1.1.tar.gz
Windows binaries: r-devel: memshare_1.1.1.zip, r-release: memshare_1.1.0.zip, r-oldrel: memshare_1.1.0.zip
macOS binaries: r-release (arm64): memshare_1.1.1.tgz, r-oldrel (arm64): memshare_1.1.1.tgz, r-release (x86_64): memshare_1.1.1.tgz, r-oldrel (x86_64): memshare_1.1.1.tgz
Old sources: memshare archive

Reverse dependencies:

Reverse imports: PDEnaiveBayes

Linking:

Please use the canonical form https://CRAN.R-project.org/package=memshare to link to this page.