# 724 search results for "parallel"

## Introducing parallelRandomForest: faster, leaner, parallelized

September 23, 2013
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Together with other members of Andreas Beyer's research group, I participated in the DREAM 8 toxicogenetics challenge. While the jury is still out on the results, I want to introduce my improvement of the R randomForest package, namely parall...

## Easy 3-Minute Guide to Making apply() Parallel over Distributed Grids and Clusters in R

September 1, 2013
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Last week I attended a workshop on how to run highly parallel distributed jobs on the Open Science Grid (osg). There I met Derek Weitzel who has made an excellent contribution to advancing R as a high performance computing language by developing BoscoR. BoscoR greatly facilitates the use of the already existing package “GridR” by The post Easy...

## Tutorial: Parallel programming with foreach

August 30, 2013
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Exegetic Analytics extols the wonders of foreach package for iterative operations that go beyond the standard "for" loop in R. For example, here's a neat (if not optimally efficient) construct using filters to calculate the primes less than 100: foreach(n = 1:100, .combine = c) %:% when (isPrime(n)) %do% n The open-source team at Revolution Analytics created the foreach...

## Multicore (parallel) processing in R

August 27, 2013
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Multicore (parallel) processing in R from Wallace Campbell on Vimeo. If you're not programming in parallel, you're only using a fraction of your computer's power! I demonstrate how to run "for" loops in parallel using the mclapply function from the multicore library. The code can be scaled to any number of available cores.

## Advanced sab-R-metrics: Parallelization with the ‘mgcv’ Package

July 18, 2013
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Carson Sievert (creator of the really neat pitchRx package) and Steamer Projections posed a question about reasonable run times of the mgcv package on large data in R yesterday, and promised my Pitch F/X friends I would post here with a quick tip on sp...

## Parallel Random Number Generation using TRNG

July 10, 2013
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To my surprise and disappointment, popular scientific libraries like Boost or GSL provide no native support for parallel random number generation. Recently I came across TRNG, an excellent random number generation library for C++ built specifically with parallel architectures in mind. Over the last few days I’ve been trawling internet forums and reading discussions about The post Parallel...

## Parallel computation with helper threads in pqR

June 23, 2013
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One innovative feature of pqR (my new, faster, version of R), is that it can perform some numeric computations in “helper” threads, in parallel with other such numeric computations, and with interpretive operations performed in the “master” thread. This can potentially speed up your computations by a factor as large as the number of processor cores

## Intro to Parallel Random Number Generation with RevoScaleR

June 6, 2013
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by Joseph Rickert Random number generation is fundamental to doing computational statistics. As you might expect, R is very rich in random number resources. The R base code provides several high quality random number generators including: Wichmann-Hill, Marsaglia-Multicarry, Super-Duper, Mersenne-Twister, Knuth-TAOCP-2002 and L’Ecuyer-CMRG. (See Random for details.) And, there are at least three packages, rspring, rlecuyer, and rstream for...

June 1, 2013
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In my previous post (http://statcompute.wordpress.com/2013/05/25/test-drive-of-parallel-computing-with-r) on 05/25/2013, I’ve demonstrated the power of parallel computing with various R packages. However, in the real world, it is not straight-forward to utilize these powerful tools in our day-by-day computing tasks without carefully formulate the problem. In the example below, I am going to show how to use the

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