Articles by JottR on R

SatRday LA 2019 Slides on Futures

May 16, 2019 | JottR on R

A bit late but here are my slides on Future: Friendly Parallel Processing in R for Everyone that I presented at the satRday LA 2019 conference in Los Angeles, CA, USA on April 6, 2019. My talk (33 slides; ~45 minutes): Title: : Friendly Parallel...
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SatRday Paris 2019 Slides on Futures

March 7, 2019 | JottR on R

Below are links to my slides from my talk on Future: Friendly Parallel Processing in R for Everyone that I presented last month at the satRday Paris 2019 conference in Paris, France (February 23, 2019). My talk (32 slides; ~40 minutes): Title: F...
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Maintenance Updates of Future Backends and doFuture

January 6, 2019 | JottR on R

New versions of the following future backends are available on CRAN: future.callr - parallelization via callr, i.e. on the local machine future.batchtools - parallelization via batchtools, i.e. on a compute cluster with job schedulers (SLURM, SGE, Torque/PBS, etc.) but also on the local machine future.... [Read more...]

future 1.9.0 – Output from The Future

July 22, 2018 | JottR on R

future 1.9.0 - Unified Parallel and Distributed Processing in R for Everyone - is on CRAN. This is a milestone release: Standard output is now relayed from futures back to the master R session - regardless of where the futures are processed! Disclaimer: A future’s output is relayed only after ...
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R.devices – Into the Void

July 20, 2018 | JottR on R

R.devices 2.16.0 - Unified Handling of Graphics Devices - is on CRAN. With this release, you can now easily suppress unwanted graphics, e.g. graphics produced by one of those do-everything-in-one-call functions that we all bump into once in a while. To suppress graphics, the R.devices package provides graphics ... [Read more...]

future.apply – Parallelize Any Base R Apply Function

June 22, 2018 | JottR on R

Got compute? future.apply 1.0.0 - Apply Function to Elements in Parallel using Futures - is on CRAN. With this milestone release, all* base R apply functions now have corresponding futurized implementations. This makes it easier than ever before to parallelize your existing apply(), lapply(), mapply(), … code - just prepend future_ ...
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Delayed Future(Slides from eRum 2018)

June 17, 2018 | JottR on R

As promised - though a bit delayed - below are links to my slides and the video of my talk on Future: Parallel & Distributed Processing in R for Everyone that I presented last month at the eRum 2018 conference in Budapest, Hungary (May 14-16, 2...
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future 1.8.0: Preparing for a Shiny Future

April 11, 2018 | JottR on R

future 1.8.0 is available on CRAN. This release lays the foundation for being able to capture outputs from futures, perform automated timing and memory benchmarking (profiling) on futures, and more. These features are not yet available out of the b...
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Performance: Avoid Coercing Indices To Doubles

April 1, 2018 | JottR on R

x[idxs + 1] or x[idxs + 1L]? That is the question. Assume that we have a vector $x$ of $n = 100,000$ random values, e.g. __ n x idxs y y typeof(idxs) [1] "integer" __ typeof(idxs + 1) [1] "double" __ typeof(1) [1] "double" Note also that doubles (aka “numerics” in R) take up twice the amount of ...
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Startup with Secrets – A Poor Man’s Approach

March 29, 2018 | JottR on R

New release: startup 0.10.0 is now on CRAN. If your R startup files (.Renviron and .Rprofile) get long and windy, or if you want to make parts of them public and other parts private, then you can use the startup package to split them up in separate files and directories under .... [Read more...]

The Many-Faced Future

June 4, 2017 | JottR on R

The future package defines the Future API, which is a unified, generic, friendly API for parallel processing. The Future API follows the principle of write code once and run anywhere - the developer chooses what to parallelize and the user how and where. The nature of a future is such ... [Read more...]

Start Me Up

December 21, 2016 | JottR on R

The startup package makes it easy to control your R startup processes and to share part of your startup settings with others (e.g. as a public Git repository) while keeping secret parts to yourself. Instead of having long and windy .Renviron and .Rprofile startup files, you can split them ... [Read more...]
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