Category: Analytics

Matlab-Mathematica-R and GPU Computing

Matlab announced they have a parallel computing toolbox- specially to enable GPU computing as well

http://www.mathworks.com/products/parallel-computing/

Parallel Computing Toolbox™ lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms—let you parallelize MATLAB® applications without CUDA or MPI programming. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel.

MATLAB GPU Support

The toolbox provides eight workers (MATLAB computational engines) to execute applications locally on a multicore desktop. Without changing the code, you can run the same application on a computer cluster or a grid computing service (using MATLAB Distributed Computing Server™). You can run parallel applications interactively or in batch.

Parallel Computing with MATLAB on Amazon Elastic Compute Cloud (EC2)

Also a video of using Mathematica and GPU

Also R has many packages for GPU computing

Parallel computing: GPUs

from http://cran.r-project.org/web/views/HighPerformanceComputing.html

  • The gputools package by Buckner provides several common data-mining algorithms which are implemented using a mixture of nVidia‘s CUDA langauge and cublas library. Given a computer with an nVidia GPU these functions may be substantially more efficient than native R routines. The rpud package provides an optimised distance metric for NVidia-based GPUs.
  • The cudaBayesreg package by da Silva implements the rhierLinearModel from the bayesm package using nVidia’s CUDA langauge and tools to provide high-performance statistical analysis of fMRI voxels.
  • The rgpu package (see below for link) aims to speed up bioinformatics analysis by using the GPU.
  • The magma package provides an interface to the hybrid GPU/CPU library Magma (see below for link).
  • The gcbd package implements a benchmarking framework for BLAS and GPUs (using gputools).

I tried to search for SAS and GPU and SPSS and GPU but got nothing. Maybe they would do well to atleast test these alternative hardwares-

Also see Matlab on GPU comparison for the product Jacket vs Parallel Computing Toolbox

http://www.accelereyes.com/products/compare

A Google App for Sales- ERPLY

While not quite Salesforce.com, a promising start for the first ERP Google App at https://www.google.com/enterprise/marketplace/viewListing?productListingId=5759+8485502070963042532

An interesting development-maybe there could be some statistical or BI apps on Google App Marketplace soon 😉

Hearst DataMining Challenge

Check out the Hearst Data Mining Challenge- a new competition-sponsored by DMA, Hearst Magazine, and EXL

THE HEARST CHALLENGE STARTS ON OCTOBER 14TH

CHALLENGE

DESCRIPTION

Over the years, the magazine publishing industry has made significant strides in improving subscription based circulation by developing analytic frameworks that better predict customer response to acquisition and renewal offers. The objective of this contest is to apply the same analytic discipline and effectively predict newsstand locations “response”. Specifically the objective is to predict the number of copies to be placed in each newsstand location to optimize the overall contribution of the newsstand location typically referred to as draw.

Data for the competition is provided by CMG and Experian.

and

RULES

HOW TO ENTER: Beginning October 14th, 2010 at 12:01 AM (ET) throughDecember 3rd, 2010 at 11:59 PM (ET) go to the Hearst Challenge website located at http://www.HearstChallenge.com (the “Site”) and complete and submit the entry form pursuant to the onscreen instructions. Entrants will be provided a historical sample of newsstand location draw, sales and associated location level data to help develop their predictive algorithm. Hearst will in turn hold back two distinct sets of draw/sales data, one to be used as a validation set by the contestant and one to be used as a final contest evaluation set. Entrants may not include any other external variables for the challenge. Additional details will be provided with the data. Entrants will be able to track their performance against the validation set throughout the course of the challenge via a leader tracking board to be made available on the Site. Entries must include the following documentation:

  • Data file with id variables and expected sales values by store and publication
  • The final model/ algorithm code used to score the final data set
  • Any supporting documentation that pertains to the development of the submitted model/algorithm including variable creation. Variables that were used in the model need to be traced through from input to coefficient / node (if using a tree based methodology).

Check out http://www.hearstchallenge.com/index.php for further details.

Where is Waldo? Webcast on Network Intelligence

From the good folks at AsterData, a webcast on a slightly interesting analytics topic

Enterprises and government agencies can become overwhelmed with information. The value of all that data lies in the insights it can reveal. To get the maximum value, you need an analytic platform that lets you analyze terabytes of information rapidly for immediate actionable insights.

Aster Data’s massively parallel database with an integrated analytics engine can quickly reveal hard-to-recognize trends on huge datasets which other systems miss. The secret? A patent-pending SQL-MapReduce framework that enables business analysts and business intelligence (BI) tools to iteratively analyze big data more quickly. This allows you to find anomalies more quickly and stop disasters before they happen.

Discover how you can improve:

  • Network intelligence via graph analysis to understand connectivity among suspects, information propagation, and the flow of goods
  • Security analysis to prevent fraud, bot attacks, and other breaches
  • Geospatial analytics to quickly uncover details about regions and subsets within those communities
  • Visual analytics to derive deeper insights more quickly

September Roundup by Revolution

From the monthly newsletter- which I consider quite useful for keeping updated on application of R

——————————————————————————————————————————————————————————————————–

Revolution News
Every month, we’ll bring you the latest news about Revolution’s products and events in this section. Follow us on Twitter at @RevolutionR for up-to-the-minute news and updates from Revolution Analytics!

Revolution R Enterprise 4.0 for Windows now available. Based on the latest R 2.11.1 and including the RevoScaleR package for big-data analysis in R, Revolution R Enterprise is now available for download for Windows 32-bit and 64-bit systems. Click here to subscribe, or available free to academia.

New! Integrate R with web applications, BI dashboards and more with web services. RevoDeployR is a new Web Services framework that integrates dynamic R-based computations into applications for business users. It will be available September 30 with Revolution R Enterprise Server on RHEL 5. Click here to learn more.

Free Webinar, September 22: In a joint webinar from Revolution Analytics and Jaspersoft, learn how to use RevoDeployR to integrate advanced analytics on-demand in applications, BI dashboards, and on the web. Register here.

Revolution in the News: SearchBusinessAnalytics.com previews the forthcoming Revolution R GUI; Channel Register introduces RevoDeployR, while IT Business Edge shows off the Web Services architecture; and ReadWriteWeb.com looks at how RevoScaleR tackles the Big Data explosion.

Inside-R: A new site for the R Community. At www.inside-R.org you’ll find the latest information about R from around the Web, searchable R documentation and packages, hints and tips about R, and more. You can even add a “Download R” badge to your own web-page to help spread the word about R.

R News, Tips and Tricks from the Revolutions blog
The Revolutions blog brings you daily news and tips about R, statistics and open source. Here are some highlights from Revolutions from the past month.

R’s key role in the oil spill response: Read how NIST’s Division Chief of Statistical Engineering used R to provide critical analysis in real time to the Secretaries of Energy and the Interior, and helped coordinate the government’s response.

Animating data with R and Google Earth: Learn how to use R to create animated visualizations of geographical data with Google Earth, such as this video showing how tuna migrations intersect with the location of the Gulf oil spill.

Are baseball games getting longer? Or is it just Red Sox games? Ryan Elmore uses nonparametric regression in R to find out.

Keynote presentations from useR! 2010: the worldwide R user’s conference was a great success, and there’s a wealth of useful tips and information in the presentations. Video of the keynote presentations are available too: check out in particular Frank Harrell’s talk Information Allergy, and Friedrich Leisch’s talk on reproducible statistical research.

Looking for more R tips and tricks? Check out the monthly round-ups at the Revolutions blog.

Upcoming Events
Every month, we’ll highlight some upcoming events from R Community Calendar.

September 23: The San Diego R User Group has a meetup on BioConductor and microarray data analysis.

September 28: The Sydney Users of R Forum has a meetup on building world-class predictive models in R (with dinner to follow).

September 28: The Los Angeles R User Group presents an introduction to statistical finance with R.

September 28: The Seattle R User Group meets to discuss, “What are you doing with R?”

September 29: The Raleigh-Durham-Chapel Hill R Users Group has its first meeting.

October 7: The NYC R User Group features a presentation by Prof. Andrew Gelman.

There are also new R user groups in Singapore, Seoul, Denver, Brisbane, and New Jersey.  Please let us know if we’re missing your R user group, or if want to get a new one started.

———————————————————————————————-Editor

David Smith, VP Marketing
david@revolutionanalytics.com
Twitter: @revodavid

subscribe here for Revo’s Monthly newsletter-

IBM Buys Netezza

IBM just bought Netezza (maker of Twin Fin appliance) for handling big data.

http://dealbook.blogs.nytimes.com/2010/09/20/i-b-m-to-buy-analytics-firm-for-1-7-billion/?hpw

The deal values Netezza at $27 a share, a 9.8 percent premium to its closing price on Friday.

Since Netezza was an existing SAS partner, probably it would impact it more if at all, since IBM-SPSS acquisition. Also Netezza was one of the foremost BI companies for both using and expounding R-

See- Using Netezza and R http://www.biecek.pl/WZUR2009/LukaszBartnik2009c.pdf

and http://www.netezza.com/userconference/pce.html#rmftfic

Below a paper on using R on Netezza-

> library(nzr)
> nzconnect(“user”, “password”, “host”, “database”)
> library(rpart)
> data(kyphosis)
# this creates a table out of kyphosis data.frame
# and sends its data to TwinFin
> invisible(as.nz.data.frame(kyphosis))
> nzQuery(“SELECT * FROM kyphosis”)
KYPHOSIS AGE NUMBER START
1 absent 71 3 5
2 absent 158 3 14
3 present 128 4 5
[ cut ]
# now create a nz.data.frame
> k <- nz.data.frame(“kyphosis”)
> as.data.frame(k)
KYPHOSIS AGE NUMBER START
1 absent 71 3 5
2 absent 158 3 14
3 present 128 4 5
[ cut ]
> nzQuery(“SELECT * FROM kyphosis”)
COUNT
1 81

JMP 9 releasing on Oct 12

JMP 9 releases on Oct 12- it is a very good reliable data visualization and analytical tool ( AND available on Mac as well)

AND IT is advertising R Graphics as well (lol- I can visualize the look on some ahem SAS fans in the R Project)

Updated Pricing- note I am not sure why they are charging US academics 495$ when SAS On Demand is free for academics. Shouldnt JMP be free to students- maybe John Sall and his people can do a tradeoff analysis for this given JMP’s graphics are better than Base SAS (which is under some pressure from WPS and R)

http://www.sas.com/govedu/edu/programs/soda-account-setup.html

and http://www.enterpriseinnovation.net/content/sas-delivers-free-data-management-and-analytics-solutions-academe

*Offer good in the U.S. only.

OFFER PRICING DETAILS
New Corporate Customer

$1,595

Save $300.

 No special requirements.
ORDER NOW (WIN) ORDER NOW (MAC)
Corporate Upgrade

$795

Save $155.

 Complete the form below or call 1-877-594-6567. Requires valid JMP® 8 serial number.
New Academic

$495

Save $100.

 Complete the form below or call 1-877-594-6567. Requires campus street address and campus e-mail address.
Academic Upgrade

$250

Save $45.

 Complete the form below or call 1-877-594-6567. Requires campus street address and campus e-mail address.

From- the mailer-

Be First in Line for JMP® 9
Save up to $300 when you pre-order a
single-user license by Oct. 11

Pre-Order JMP 9

Make JMP your analytic hub for visual data discovery with this special offer, good through Oct. 11, 2010. Pre-order a single-user license of JMP 9 – for a discount of up to $300 – and get ready for a leap in data interactivity.

Order now and enjoy the compelling new features of JMP 9 when the software is released Oct. 12. New capabilities in JMP 9 let you:

  • Optimize and simulate using your Microsoft Excel spreadsheets.
  • Use maps to find patterns in your geographic data.
  • Enjoy the updated look and flexibility of JMP 9 on Microsoft Windows.
  • Create and share custom add-ins that extend JMP.
  • Leverage an expanded array of advanced statistical methodologies.
  • Display analytic results from R using interactive graphics.

PRE-ORDER JMP 9

What if I already have a JMP 8 single-user license?
Great news! You can upgrade to JMP 9 for less than half the regular price.

What if I’m an annual license customer?
Don’t worry, we’ve got you covered. Annual license customers enjoy priority access to all the latest JMP releases as soon as they become available. JMP 9 will be shipped to you automatically.

What if I work or study in the academic world?
Call 1-877-594-6567 to learn about significant discounts for students and professors through the JMP Academic Program.

Please feel free to forward this offer to interested colleagues.

Got two or more users?
A JMP® annual license is the way to go. Call for details.
1-877-594-6567

Remember: Act by Oct. 11!

JMP runs on Macintosh and Windows