841 search results for "parallel"

Summing a Vector in Parallel with RcppParallel

June 28, 2014
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Summing a Vector in Parallel with RcppParallel

The RcppParallel package includes high level functions for doing parallel programming with Rcpp. For example, the parallelReduce function can be used aggreggate values from a set of inputs in parallel. This article describes using RcppParallel to sum an R vector. Serial Version First a serial version of computing the sum of a vector. For this we use a simple call to the STL std::accumulate function: #include...

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Transforming a Matrix in Parallel using RcppParallel

June 28, 2014
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Transforming a Matrix in Parallel using RcppParallel

The RcppParallel package includes high level functions for doing parallel programming with Rcpp. For example, the parallelFor function can be used to convert the work of a standard serial “for” loop into a parallel one. This article describes using RcppParallel to transform an R matrix in parallel. Serial Version First a serial version of the matrix transformation. We take the square root of each...

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sugar in parallel

June 18, 2014
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sugar in parallel

I've been playing with parallelising Rcpp11 implementation of sugar. For example, we have a NumericVector variable x and we want to compute e.g. sqrt(exp(x)) + 2.0. With sugar, we can do: NumericVector y = sqrt(exp(x)) + 2.0 ; and this does not...

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Rth: a Flexible Parallel Computation Package for R

June 17, 2014
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Rth:  a Flexible Parallel Computation Package for R

I’ve been mentioning here that I’ll be discussing a new package, Rth, developed by me and Drew Schmidt, the latter of pbdR fame.  It’s now ready for use!  In this post, I’ll explain what goals Rth has, and how to use it. Platform Flexibility The key feature of Rth is in the word flexible in

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Rth: a Flexible Parallel Computation Package for R

June 17, 2014
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Rth:  a Flexible Parallel Computation Package for R

I’ve been mentioning here that I’ll be discussing a new package, Rth, developed by me and Drew Schmidt, the latter of pbdR fame.  It’s now ready for use!  In this post, I’ll explain what goals Rth has, and how to use it. Platform Flexibility The key feature of Rth is in the word flexible in

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Hyperthreading FTW? Testing parallelization performance in R.

March 7, 2014
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Hyperthreading FTW? Testing parallelization performance in R.

Alright, let's test some parallelization functionalities in R.The machine:MacBook Air (mid-2013) with 8 GB of RAM and the i7 CPU (Intel i7 Haswell 4650U). This CPU is hyper-threaded, meaning (at least that's my understanding of it) that it has two...

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Mumbai, Feb 2014 – HPC and Parallel R

February 17, 2014
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(This article was first published on Rmetrics blogs, and kindly contributed to R-bloggers) To leave a comment for the author, please follow the link and comment on his blog: Rmetrics blogs. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web...

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Parallelizing #RStats using #make

January 30, 2014
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In the current post, I'll show how to use R as the main SHELL of GNU-Make instead of using a classical linux shell like 'bash'. Why would you do this ? awesomeness Make-based workflow management Make-based execution with --jobs. GNU make knows how to ...

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A brief foray into parallel processing with R

January 21, 2014
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A brief foray into parallel processing with R

I’ve recently been dabbling with parallel processing in R and have found the foreach package to be a useful approach to increasing efficiency of loops. To date, I haven’t had much of a need for these tools but I’ve started working with large datasets that can be cumbersome to manage. My first introduction to parallel

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Quick guide to parallel R with snow

January 10, 2014
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Quick guide to parallel R with snow

Probably, the most common complains against R are related to its speed issues, especially when handling a high volume of information. This is, in principle, true, and relies partly on the fact that R does not run parallely…. unless you … Continue reading →

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