726 search results for "parallel"

The first version of my “inference from iterative simulation using parallel sequences” paper!

May 9, 2012
By

From August 1990. It was in the form of a note sent to all the people in the statistics group of Bell Labs, where I’d worked that summer. To all: Here’s the abstract of the work I’ve done this summer. It’s stored in the file, /fs5/gelman/abstract.bell, and copies of the Figures 1-3 are on Trevor’s The post The...

Read more »

A simple example of parallel computing on a Windows (and also Mac) machine

May 8, 2012
By
A simple example of parallel computing on a Windows (and also Mac) machine

by Yanchang Zhao, RDataMining.com With a Mac, parallel computing can be achieved with package multicore. Unfortunately, it does not work under Windows. A simple way for parallel computing under Windows (and also Mac) is using package snowfall, which can work … Continue reading →

Read more »

Online resources for handling big data and parallel computing in R

May 6, 2012
By
Online resources for handling big data and parallel computing in R

by Yanchang Zhao, RDataMining.com Compared with many other programming languages, such as C/C++ and Java, R is less efficient and consumes much more memory. Fortunately, there are some packages that enables parallel computing in R and also packages for processing … Continue reading →

Read more »

Download Prices From Yahoo In Parallel

April 24, 2012
By

Following my previous post about rewriting my code to run in parallel I have modified the code for downloading the S&P 500 prices from Yahoo to run i parallel as well. To be honest, I quite enjoy writing the code to run in parallel. It's fun for various reasons, but some theoretical background is highly

Read more »

Rewriting My Code to Run in Parallel (1)

April 21, 2012
By

As I have mentioned in my previous post I am about to make my code for finding co-integrated pairs run in parallel and more efficient. But before I do so in the actual co-integration code I would like to run some tests to see whether it would improve t...

Read more »

A No BS Guide to the Basics of Parallelization in R

March 15, 2012
By

What is parallelization?Parallelization is using multiple processing cores to, hopefully, make your programs run faster than serial code, which is the use of just one processing core. Parallel code is not always faster than its serial counterpart (but if you're doing it right and you're careful about what you parallelize, it will be --- remember, that's your goal here). ...

Read more »

DEoptim in Parallel

March 4, 2012
By

Running DEoptim in parallel has been on the development team's wishlist for awhile.  It had not been a priority though, because none of us have personally needed it.  An opportunity arose when Kris Boudt approached me about collaborating to a...

Read more »

Parallelizing Voting simulation

March 1, 2012
By
Parallelizing Voting simulation

Last week I have compared synchronous and asynchronous implementation of NetLogo Voting model. An interesting afterthought is that synchronous model implementation can be easily made much faster using vectorization.The two versions of the Voting synchr...

Read more »

Parallel R Model Prediction Building and Analytics

January 26, 2012
By

Modifying R code to run in parallel can lead to huge performance gains. Although a significant amount of code can easily be run in parallel, there are some learning techniques, such as the Support Vector Machine, that cannot be easily parallelized. However, there is an often overlooked way to speed up these and other models. It...

Read more »

Parallel R Model Prediction Building and Analytics

January 26, 2012
By

Modifying R code to run in parallel can lead to huge performance gains. Although a significant amount of code can easily be run in parallel, there are some learning techniques, such as the Support Vector Machine, that cannot be easily parallelized. However, there is an often overlooked way to speed up these and other models. It involves executing the...

Read more »