The R Journal: article published in 2021, volume 13:2

A Unifying Framework for Parallel and Distributed Processing in R using Futures PDF download
Henrik Bengtsson , The R Journal (2021) 13:2, pages 273-291.

Abstract A future is a programming construct designed for concurrent and asynchronous evaluation of code, making it particularly useful for parallel processing. The future package implements the Future API for programming with futures in R. This minimal API provides sufficient constructs for implementing parallel versions of well-established, high-level map-reduce APIs. The future ecosystem supports exception handling, output and condition relaying, parallel random number generation, and automatic identification of globals lowering the threshold to parallelize code. The Future API bridges parallel frontends with parallel backends, following the philosophy that end-users are the ones who choose the parallel backend while the developer focuses on what to parallelize. A variety of backends exist, and third-party contributions meeting the specifications, which ensure that the same code works on all backends, are automatically supported. The future framework solves several problems not addressed by other parallel frameworks in R.

Received: 2020-10-30; online 2021-11-10, supplementary material, (1.2 KiB)
CRAN packages: sparklyr, future, foreach, multicore, snow, doMC, doParallel, doMPI, doRedis, progressr, globals, codetools, future.apply, furrr, promises, listenv, future.callr, callr, future.batchtools, batchtools, googleComputeEngineR, parallelly, digest, future.tests, caret, glmnet, NMF, plyr, TSP, doFuture, DBI, xml2, stan, data.table, microbenchmark, bench, proffer, profvis, future.BatchJobs, BatchJobs, purrr, targets, drake, shiny, plumber, civis
CRAN Task Views implied by cited CRAN packages: HighPerformanceComputing, WebTechnologies, Databases, MachineLearning, ModelDeployment, ReproducibleResearch, Finance, Multivariate, Optimization, Survival, TeachingStatistics, TimeSeries
Bioconductor packages: BiocParallel

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This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

  author = {Henrik Bengtsson},
  title = {{A Unifying Framework for Parallel and Distributed Processing
          in R using Futures}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-048},
  url = {},
  pages = {273--291},
  volume = {13},
  number = {2}