841 search results for "parallel"

Parallel processing with short jobs only increases the run time

December 27, 2013
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Parallel processing with short jobs only increases the run time

Parallel processing has become much more important over the years as multi-core processors have become common place. From version 02.14 onwards, parallel processing has become part of the standard R installation in the form of the parallel package. This package… See more ›

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Parallel R (and air travel)

Parallel R (and air travel)

My heart sinks a little when I check on my laptop in the morning and the computation I started the night before still hasn’t finished. Even when the data I’m playing with isn’t particularly.... large... (I’m not going to say it), I have a knack for choosing expensive algorithms late at night. Because of my »more

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Running Back-tests in parallel

November 11, 2013
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Running Back-tests in parallel

Once you start experimenting with many different asset allocation algorithms, the computation time of running the back-tests can be substantial. One simple way to solve the computation time problem is to run the back-tests in parallel. I.e. if the asset allocation algorithm does not use the prior period holdings to make decision about current allocation,

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Stochastic Optimization in R by Parallel Tempering

October 12, 2013
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Stochastic Optimization in R by Parallel Tempering

I’ve written a few posts now about using parallel tempering to sample from complicated multi-modal target distributions but there are also other benefits and uses to this algorithm. There is a nice post on Darren Wilkinson’s blog about using tempered posteriors for marginal likelihood calculations. There is also another area where parallel tempering finds application, The post Stochastic...

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Parallel Tempering in R with Rmpi

October 6, 2013
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Parallel Tempering in R with Rmpi

My office computer recently got a really nice upgrade and now I have 8 cores on my desktop to play with. I also at the same time received some code for a Gibbs sampler written in R from my adviser. I wanted to try a metropolis-coupled markov chain monte carlo, , algorithm on it to The post Parallel...

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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...

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

September 1, 2013
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Easy 3-Minute Guide to Making apply() Parallel over Distributed Grids and Clusters in R

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...

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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...

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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.

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

July 18, 2013
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Advanced sab-R-metrics: Parallelization with the ‘mgcv’ Package

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...

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