Posts Tagged ‘ high-performance computing ’

Slides and replay for “Big Data with Revolution R”

August 25, 2010
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Thanks to everyone who attended our webinar this morning, Big Data Analysis for R Using Revolution R Enterprise, and in particular thanks for all the thoughtful questions during the Q&A session. If you missed the live broadcast, a replay is now available (requires the ability to view WMV files), and you can also download the slides in PDF format....

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Webinar: Big Data Analysis with Revolution R

August 24, 2010
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Don't forget that I'll be hosting a webinar tomorrow talking about the new RevoScaleR package included with the forthcoming Revolution R Enterprise 4.0. The webinar will also feature a live demonstration from Joseph Rickert. The full details are below, and you can register for the webinar here. Big Data Analysis for R Using Revolution R Enterprise Date: Wednesday, Aug...

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Taking R to the Limit: Parallelism and Big Data

August 23, 2010
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In a two-part series at the Los Angeles R User Group, Ryan Rosario took a look at the many ways you can take the R language to the limits of high-performance computing. In Part I (see video at this link; slides and code also available), Ryan focuses on the various methods of parallel computing in R. There's some great...

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Wanted: Big-data beta testers

July 15, 2010
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We're nearing completion of the package of statistical tools for very large data sets that I gave an early preview of at R/Finance 2010. It will be released for Revolution R Enterprise later this year, but we're looking for some R users with big data sets to put the 1.0 version through its paces in the beta program and...

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How to peg 7 cores with doSMP

June 28, 2010
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How to peg 7 cores with doSMP

Statistics PhD student Nathan VanHoudnos has an 8-core laptop, and by his own admission, takes "an almost unhealthy pleasure in pushing computer to its limits". It seems like he's found an outlet for this passion with the new doSMP library included with Revolution R, that allows him to use all his processors for some gnarly simulations in R:...

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Making Data Work online conference

June 3, 2010
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O'Reilly is hosting a conference on June 9 on the topic of the analysis of large data sets. The title of the conference is Making Data Work: Ever since Hal Varian proclaimed that data analysis is the sexy career for the coming decade, people have been talking about data. And big data. And even bigger data. This online conference,...

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Map-reduce in R with Amazon EMR

May 27, 2010
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There's new video at the Video Rchive of a JD Long presentation: Amazon Elastic Map-Reduce (So Easy an Economist Can Do It). I'm on a plane right now and the in-flight wi-fi isn't quite up to playing the 30-minute video, but judging from the slides it looks like a nice, practical demonstration of getting a map-reduce computation programmed in...

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Prediction in the cloud: turbulent

May 19, 2010
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While Microsoft rolled out its Technical Computing Initiative -- promising new tools for distributed parallel computing on large data sets in the cloud -- with much fanfare earlier this week, Google made a rather more understated response. In a post to the developer-focused Google Code Blog, they quietly announced two new, but potentially disruptive, products. Google BigQuery promises super-fast...

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Parallel Computing with R for Life Sciences

May 18, 2010
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I hadn't heard of the CloudAsia 2010 conference before, but from the programme the workshop Master Class on HPC Application For Life Sciences looked like it was interesting. One workshop session in particular caught my eye: Practical Parallel Computing in R by Xie Chao and Tan Tin Wee (from the National University of Singapore). The workshop notes (PDF) provide...

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Slides from High-Performance Analytics webinar now available

April 14, 2010
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Thanks to everyone who attended the webinar I presented this morning, High-Performance Analytics with REvolution R and Windows HPC Server. My slides are now available for download at the link below; even if you're not using Windows, I hope the slides are a useful introduction to the foreach parallel programming construct in general. If you do use R on...

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