Latest R Journal

Including juicy stuff on using a cluster of Apple Machines for grid computing , seasonality forecasting (Yet Another Package For Time Series )

But I kind of liked Sumo too-

https://code.google.com/p/sumo/

Sumo is a fully-functional web application template that exposes an authenticated user’s R session within java server pages.

Sumo: An Authenticating Web Application with an Embedded R Session by Timothy T. Bergsma and Michael S. Smith Abstract Sumo is a web application intended as a template for developers. It is distributed as a Java ‘war’ file that deploys automatically when placed in a Servlet container’s ‘webapps’
directory. If a user supplies proper credentials, Sumo creates a session-specific Secure Shell connection to the host and a user-specific R session over that connection. Developers may write dynamic server pages that make use of the persistent R session and user-specific file space.

and for Apple fanboys-

We created the xgrid package (Horton and Anoke, 2012) to provide a simple interface to this distributed computing system. The package facilitates use of an Apple Xgrid for distributed processing of a simulation with many independent repetitions, by simplifying job submission (or grid stuffing) and collation of results. It provides a relatively thin but useful layer between R and Apple’s ‘xgrid’ shell command, where the user constructs input scripts to be run remotely. A similar set of routines, optimized for parallel estimation of JAGS (just another Gibbs sampler) models is available within the runjags package (Denwood, 2010). However, with the exception of runjags, none of the previously mentioned packages support parallel computation over an Apple Xgrid.

Hmm I guess parallel computing enabled by Wifi on mobile phones would be awesome too ! So would be anything using iOS . See the rest of the R Journal at http://journal.r-project.org/current.html

RJournal_2012-1

Teradata Analytics

A recent announcement showing Teradata partnering with KXEN and Revolution Analytics for Teradata Analytics.

http://www.teradata.com/News-Releases/2012/Teradata-Expands-Integrated-Analytics-Portfolio/

The Latest in Open Source Emerging Software Technologies
Teradata provides customers with two additional open source technologies – “R” technology from Revolution Analytics for analytics and GeoServer technology for spatial data offered by the OpenGeo organization – both of which are able to leverage the power of Teradata in-database processing for faster, smarter answers to business questions.

In addition to the existing world-class analytic partners, Teradata supports the use of the evolving “R” technology, an open source language for statistical computing and graphics. “R” technology is gaining popularity with data scientists who are exploiting its new and innovative capabilities, which are not readily available. The enhanced “R add-on for Teradata” has a 50 percent performance improvement, it is easier to use, and its capabilities support large data analytics. Users can quickly profile, explore, and analyze larger quantities of data directly in the Teradata Database to deliver faster answers by leveraging embedded analytics.

Teradata has partnered with Revolution Analytics, the leading commercial provider of “R” technology, because of customer interest in high-performing R applications that deliver superior performance for large-scale data. “Our innovative customers understand that big data analytics takes a smart approach to the entire infrastructure and we will enable them to differentiate their business in a cost-effective way,” said David Rich, chief executive officer, Revolution Analytics. “We are excited to partner with Teradata, because we see great affinity between Teradata and Revolution Analytics – we embrace parallel computing and the high performance offered by multi-core and multi-processor hardware.”

and

The Teradata Data Lab empowers business users and leading analytic partners to start building new analytics in less than five minutes, as compared to waiting several weeks for the IT department’s assistance.

“The Data Lab within the Teradata database provides the perfect foundation to enable self-service predictive analytics with KXEN InfiniteInsight,” said John Ball, chief executive officer, KXEN. “Teradata technologies, combined with KXEN’s automated modeling capabilities and in-database scoring, put the power of predictive analytics and data mining directly into the hands of business users. This powerful combination helps our joint customers accelerate insight by delivering top-quality models in orders of magnitude faster than traditional approaches.”

Read more at

http://www.sacbee.com/2012/03/06/4315500/teradata-expands-integrated-analytics.html

Amazon Ec2 goes Red Hat

message from Amazing Amazon’s cloud team- this will also help for #rstats users given that revolution Analytics full versions on RHEL.

—————————————————-

on-demand instances of Amazon EC2 running Red Hat Enterprise Linux (RHEL) for as little as $0.145 per instance hour. The offering combines the cost-effectiveness, scalability and flexibility of running in Amazon EC2 with the proven reliability of Red Hat Enterprise Linux.

Highlights of the offering include:

  • Support is included through subscription to AWS Premium Support with back-line support by Red Hat
  • Ongoing maintenance, including security patches and bug fixes, via update repositories available in all Amazon EC2 regions
  • Amazon EC2 running RHEL currently supports RHEL 5.5, RHEL 5.6, RHEL 6.0 and RHEL 6.1 in both 32 bit and 64 bit formats, and is available in all Regions.
  • Customers who already own Red Hat licenses will continue to be able to use those licenses at no additional charge.
  • Like all services offered by AWS, Amazon EC2 running Red Hat Enterprise Linux offers a low-cost, pay-as-you-go model with no long-term commitments and no minimum fees.

For more information, please visit the Amazon EC2 Red Hat Enterprise Linux page.

which is

Amazon EC2 Running Red Hat Enterprise Linux

Amazon EC2 running Red Hat Enterprise Linux provides a dependable platform to deploy a broad range of applications. By running RHEL on EC2, you can leverage the cost effectiveness, scalability and flexibility of Amazon EC2, the proven reliability of Red Hat Enterprise Linux, and AWS premium support with back-line support from Red Hat.. Red Hat Enterprise Linux on EC2 is available in versions 5.5, 5.6, 6.0, and 6.1, both in 32-bit and 64-bit architectures.

Amazon EC2 running Red Hat Enterprise Linux provides seamless integration with existing Amazon EC2 features including Amazon Elastic Block Store (EBS), Amazon CloudWatch, Elastic-Load Balancing, and Elastic IPs. Red Hat Enterprise Linux instances are available in multiple Availability Zones in all Regions.

Sign Up

Pricing

Pay only for what you use with no long-term commitments and no minimum fee.

On-Demand Instances

On-Demand Instances let you pay for compute capacity by the hour with no long-term commitments.

Region:US – N. VirginiaUS – N. CaliforniaEU – IrelandAPAC – SingaporeAPAC – Tokyo
Standard Instances Red Hat Enterprise Linux
Small (Default) $0.145 per hour
Large $0.40 per hour
Extra Large $0.74 per hour
Micro Instances Red Hat Enterprise Linux
Micro $0.08 per hour
High-Memory Instances Red Hat Enterprise Linux
Extra Large $0.56 per hour
Double Extra Large $1.06 per hour
Quadruple Extra Large $2.10 per hour
High-CPU Instances Red Hat Enterprise Linux
Medium $0.23 per hour
Extra Large $0.78 per hour
Cluster Compute Instances Red Hat Enterprise Linux
Quadruple Extra Large $1.70 per hour
Cluster GPU Instances Red Hat Enterprise Linux
Quadruple Extra Large $2.20 per hour

Pricing is per instance-hour consumed for each instance type. Partial instance-hours consumed are billed as full hours.

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and

Available Instance Types

Standard Instances

Instances of this family are well suited for most applications.

Small Instance – default*

1.7 GB memory
1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit)
160 GB instance storage
32-bit platform
I/O Performance: Moderate
API name: m1.small

Large Instance

7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large

Extra Large Instance

15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge

Micro Instances

Instances of this family provide a small amount of consistent CPU resources and allow you to burst CPU capacity when additional cycles are available. They are well suited for lower throughput applications and web sites that consume significant compute cycles periodically.

Micro Instance

613 MB memory
Up to 2 EC2 Compute Units (for short periodic bursts)
EBS storage only
32-bit or 64-bit platform
I/O Performance: Low
API name: t1.micro

High-Memory Instances

Instances of this family offer large memory sizes for high throughput applications, including database and memory caching applications.

High-Memory Extra Large Instance

17.1 GB of memory
6.5 EC2 Compute Units (2 virtual cores with 3.25 EC2 Compute Units each)
420 GB of instance storage
64-bit platform
I/O Performance: Moderate
API name: m2.xlarge

High-Memory Double Extra Large Instance

34.2 GB of memory
13 EC2 Compute Units (4 virtual cores with 3.25 EC2 Compute Units each)
850 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.2xlarge

High-Memory Quadruple Extra Large Instance

68.4 GB of memory
26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.4xlarge

High-CPU Instances

Instances of this family have proportionally more CPU resources than memory (RAM) and are well suited for compute-intensive applications.

High-CPU Medium Instance

1.7 GB of memory
5 EC2 Compute Units (2 virtual cores with 2.5 EC2 Compute Units each)
350 GB of instance storage
32-bit platform
I/O Performance: Moderate
API name: c1.medium

High-CPU Extra Large Instance

7 GB of memory
20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: c1.xlarge

Cluster Compute Instances

Instances of this family provide proportionally high CPU resources with increased network performance and are well suited for High Performance Compute (HPC) applications and other demanding network-bound applications. Learn more about use of this instance type for HPC applications.

Cluster Compute Quadruple Extra Large Instance

23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge

Cluster GPU Instances

Instances of this family provide general-purpose graphics processing units (GPUs) with proportionally high CPU and increased network performance for applications benefitting from highly parallelized processing, including HPC, rendering and media processing applications. While Cluster Compute Instances provide the ability to create clusters of instances connected by a low latency, high throughput network, Cluster GPU Instances provide an additional option for applications that can benefit from the efficiency gains of the parallel computing power of GPUs over what can be achieved with traditional processors. Learn more about use of this instance type for HPC applications.

Cluster GPU Quadruple Extra Large Instance

22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge

 


Getting Started

To get started using Red Hat Enterprise Linux on Amazon EC2, perform the following steps:

  • Open and log into the AWS Management Console
  • Click on Launch Instance from the EC2 Dashboard
  • Select the Red Hat Enterprise Linux AMI from the QuickStart tab
  • Specify additional details of your instance and click Launch
  • Additional details can be found on each AMI’s Catalog Entry page

The AWS Management Console is an easy tool to start and manage your instances. If you are looking for more details on launching an instance, a quick video tutorial on how to use Amazon EC2 with the AWS Management Console can be found here .
A full list of Red Hat Enterprise Linux AMIs can be found in the AWS AMI Catalog.

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Support

All customers running Red Hat Enterprise Linux on EC2 will receive access to repository updates from Red Hat. Moreover, AWS Premium support customers can contact AWS to get access to a support structure from both Amazon and Red Hat.

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Resources

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About Red Hat

Red Hat, the world’s leading open source solutions provider, is headquartered in Raleigh, NC with over 50 satellite offices spanning the globe. Red Hat provides high-quality, low-cost technology with its operating system platform, Red Hat Enterprise Linux, together with applications, management and Services Oriented Architecture (SOA) solutions, including the JBoss Enterprise Middleware Suite. Red Hat also offers support, training and consulting services to its customers worldwide.

 

also from Revolution Analytics- in case you want to #rstats in the cloud and thus kill all that talk of RAM dependency, slow R than other softwares (just increase the RAM above in the instances to keep it simple)

,or Revolution not being open enough

http://www.revolutionanalytics.com/downloads/gpl-sources.php

GPL SOURCES

Revolution Analytics uses an Open-Core Licensing model. We provide open- source R bundled with proprietary modules from Revolution Analytics that provide additional functionality for our users. Open-source R is distributed under the GNU Public License (version 2), and we make our software available under a commercial license.

Revolution Analytics respects the importance of open source licenses and has contributed code to the open source R project and will continue to do so. We have carefully reviewed our compliance with GPLv2 and have worked with Mark Radcliffe of DLA Piper, the outside General Legal Counsel of the Open Source Initiative, to ensure that we fully comply with the obligations of the GPLv2.

For our Revolution R distribution, we may make some minor modifications to the R sources (the ChangeLog file lists all changes made). You can download these modified sources of open-source R under the terms of the GPLv2, using either the links below or those in the email sent to you when you download a specific version of Revolution R.

Download GPL Sources

Product Version Platform Modified R Sources
Revolution R Community 3.2 Windows R 2.10.1
Revolution R Community 3.2 MacOS R 2.10.1
Revolution R Enterprise 3.1.1 RHEL R 2.9.2
Revolution R Enterprise 4.0 Windows R 2.11.1
Revolution R Enterprise 4.0.1 RHEL R 2.11.1
Revolution R Enterprise 4.1.0 Windows R 2.11.1
Revolution R Enterprise 4.2 Windows R 2.11.1
Revolution R Enterprise 4.2 RHEL R 2.11.1
Revolution R Enterprise 4.3 Windows & RHEL R 2.12.2

 

 

 

Intel® Threading Challenge 2011 Software Contest

Logo of Intel, Jul 1968 - Dec 2005
Image via Wikipedia

One more software contests for you, but in the sub million dollar prize range

http://software.intel.com/en-us/contests/intel-threading-challenge-2011/contests.php

Intel® Threading Challenge 2011 – Win a Trip to Intel Developer Forum in San Francisco

Intel® Threading Challenge 2011 is going BIG this year! After three exciting threading competitions, our fourth Threading Challenge is stepping up the excitement with a BIG Grand Prize, a trip to the Intel Developer Forum (IDF) in San Francisco (September 13-15, 2011).

Since 2008, the Intel® Threading Challenge has attracted developers of varying experience from around the world. The active participation from the community has made the Threading Challenge not only a great programming competition, but a great way for community members to engage with each other, trade threading tips, and discover new parallel programming resources.

Last year’s format of two competition levels, Master and Apprentice, generated great excitement and opened the Threading Challenge to a new group of participants. So, we are going to continue the competition with a Master level and Apprentice level, each competing for the Grand Prize for their level, as well as individual problem awards. We know you love a great challenge and great prizes, so our Threading Challenge Team is putting together some exciting threading problems for you.

Monday, April 18, 2011 – Threading Challenge 2011 (Phase 1) Launches (both levels) at 12:00 PM (noon PDT)– The competition for 2011 is very similar to last year’s, but read on whether you’re a previous participant or new to the Threading Challenge, so you will be aware of all elements of the competition and how to compete. Then, you can start threading your way to prizes today!

Choose the right level for you!

 

Threading Challenge 2011:

• Two levels available for entry: Apprentice & Master
• Phase 1: 3 problems in each level
• Phase 2: Stay tuned for details, coming in Autumn 2011
• We will award 1st, 2nd & 3rd place prizes for each problem in each level
• No overlap of problems and each level’s problems will be offered consecutively
• Participants have the option to use the Intel® Manycore Testing Lab (MTL), consisting of 40 cores, 80 threads
• To enter the Threading Challenge 2011, please read the Official Rules and register for the competition with link in the “To Enter” Section.

The Threading Challenge will be implemented in two phases, with the 1st Phase consisting of 3 problems in each level. The details of the 2nd Phase will be announced in September 2011. For Phase 1, a new problem in each level will be launched on the days listed below at 12:00 noon (PDT) and will be open for entry for 22 days (inclusive of the problem starting day), until closing on the final problem day at 12:00 noon (PDT).

Problem Start and Closing Dates (both Master and Apprentice levels):

Problem 1:
Starts: Monday, April 18, 2011 at 12:00pm (PDT)
Ends. Monday, May 9, 2011 at 12:00pm (PDT)

Problem 2:
Starts: Monday, May 9, 2011 at 12:00pm (PDT)
Ends: Monday, May 30, 2011 at 12:00pm (PDT)

Problem 3: (Due to U.S. Memorial Day Holiday, Problem 2 will start on Tuesday, May 31, 2011)
Starts: Tuesday, May 31, 2011 at 12:00pm (PDT)
Ends: Tuesday, June 21, 2011 at 12:00pm (PDT)

*All problems start and end at 12:00 noon (Pacific Daylight Time)

Contestants will have 22 days to complete their entry submission (solution only for Apprentice OR solution and write-up for Master) for each problem. You may enter ONLY 1 problem at a time and will need to choose which level (Apprentice or Master) you wish to participate in during each problem cycle. You will be awarded points based on your solution submitted. Be sure to take advantage of our threading resources and tools, and you may validate your solution (optional) using the Intel® Manycore Testing Lab to solve your problems and get involved in the dedicated forums to earn extra points.

Each problems winners will be announced on the site after the problem is closed, and Prizes will be awarded to those problem winners (see official rules for prize distribution information). The Grand Prize, a Trip to Intel® Developer Forum (IDF) in San Francisco, will be awarded for each level to the participant that has the highest total points earned for the three problems in each level (i.e., highest total points for Master level problems and Apprentice level problems).

The Intel® Threading Challenge attracts some of the most talented developers in the world to solve parallelism code challenges. Now is your chance to take multithreading to the next level and possibly win great prizes. Demonstrate your threading expertise today!

More Details:

Intel® Threading Challenge 2011 is organized so any level of developer can have the opportunity to participate. Two levels of participation are available. The Apprentice level gives those just getting started in multithreading development a chance to try out and improve their threading skills. The Master level will be executed similarly to previous threading challenges, providing those with more experience a chance to test their skills and compete against other experienced developers.

Intel® Manycore Testing Lab – Available as Option for Threading Challenge 2011 Participants

This year competitors will have the optional opportunity to develop and validate their code using the Intel® Manycore Testing Lab. This 40-core, 80-thread development environment has the latest hardware and software available and will be used by this year’s judges to test the winning entries in Threading Challenge 2011 Phase 1.

The Intel® Manycore Testing Lab (MTL) will be made available to Threading Challenge 2011 contestants. Use of the MTL will give participants the opportunity to write and test their code on systems exactly configured to what the judges will be using to score submitted entries. No more guessing about if your code will build or how it will run. (There is no requirement to use the MTL for any part of the contest. It is strictly an optional alternative being made available to those that wish to use it.)

Using Views in R and comparing functions across multiple packages

Some RDF hacking relating to updating probabil...
Image via Wikipedia

R has almost 2923 available packages

This makes the task of searching among these packages and comparing functions for the same analytical task across different packages a bit tedious and prone to manual searching (of reading multiple Pdfs of help /vignette of packages) or sending an email to the R help list.

However using R Views is a slightly better way of managing all your analytical requirements for software rather than the large number of packages (see Graphics view below).

CRAN Task Views allow you to browse packages by topic and provide tools to automatically install all packages for special areas of interest. Currently, 28 views are available. http://cran.r-project.org/web/views/

Bayesian Bayesian Inference
ChemPhys Chemometrics and Computational Physics
ClinicalTrials Clinical Trial Design, Monitoring, and Analysis
Cluster Cluster Analysis & Finite Mixture Models
Distributions Probability Distributions
Econometrics Computational Econometrics
Environmetrics Analysis of Ecological and Environmental Data
ExperimentalDesign Design of Experiments (DoE) & Analysis of Experimental Data
Finance Empirical Finance
Genetics Statistical Genetics
Graphics Graphic Displays & Dynamic Graphics & Graphic Devices & Visualization
gR gRaphical Models in R
HighPerformanceComputing High-Performance and Parallel Computing with R
MachineLearning Machine Learning & Statistical Learning
MedicalImaging Medical Image Analysis
Multivariate Multivariate Statistics
NaturalLanguageProcessing Natural Language Processing
OfficialStatistics Official Statistics & Survey Methodology
Optimization Optimization and Mathematical Programming
Pharmacokinetics Analysis of Pharmacokinetic Data
Phylogenetics Phylogenetics, Especially Comparative Methods
Psychometrics Psychometric Models and Methods
ReproducibleResearch Reproducible Research
Robust Robust Statistical Methods
SocialSciences Statistics for the Social Sciences
Spatial Analysis of Spatial Data
Survival Survival Analysis
TimeSeries Time Series Analysis

To automatically install these views, the ctv package needs to be installed, e.g., via

install.packages("ctv")
library("ctv")
Created by Pretty R at inside-R.org


and then the views can be installed via install.views or update.views (which first assesses which of the packages are already installed and up-to-date), e.g.,

install.views("Econometrics")
 update.views("Econometrics")
 Created by Pretty R at inside-R.org

CRAN Task View: Graphic Displays & Dynamic Graphics & Graphic Devices & Visualization

Maintainer: Nicholas Lewin-Koh
Contact: nikko at hailmail.net
Version: 2009-10-28

R is rich with facilities for creating and developing interesting graphics. Base R contains functionality for many plot types including coplots, mosaic plots, biplots, and the list goes on. There are devices such as postscript, png, jpeg and pdf for outputting graphics as well as device drivers for all platforms running R. lattice and grid are supplied with R’s recommended packages and are included in every binary distribution. lattice is an R implementation of William Cleveland’s trellis graphics, while grid defines a much more flexible graphics environment than the base R graphics.

R’s base graphics are implemented in the same way as in the S3 system developed by Becker, Chambers, and Wilks. There is a static device, which is treated as a static canvas and objects are drawn on the device through R plotting commands. The device has a set of global parameters such as margins and layouts which can be manipulated by the user using par() commands. The R graphics engine does not maintain a user visible graphics list, and there is no system of double buffering, so objects cannot be easily edited without redrawing a whole plot. This situation may change in R 2.7.x, where developers are working on double buffering for R devices. Even so, the base R graphics can produce many plots with extremely fine graphics in many specialized instances.

One can quickly run into trouble with R’s base graphic system if one wants to design complex layouts where scaling is maintained properly on resizing, nested graphs are desired or more interactivity is needed. grid was designed by Paul Murrell to overcome some of these limitations and as a result packages like latticeggplot2vcd or hexbin (on Bioconductor ) use grid for the underlying primitives. When using plots designed with grid one needs to keep in mind that grid is based on a system of viewports and graphic objects. To add objects one needs to use grid commands, e.g., grid.polygon() rather than polygon(). Also grid maintains a stack of viewports from the device and one needs to make sure the desired viewport is at the top of the stack. There is a great deal of explanatory documentation included with grid as vignettes.

The graphics packages in R can be organized roughly into the following topics, which range from the more user oriented at the top to the more developer oriented at the bottom. The categories are not mutually exclusive but are for the convenience of presentation:

  • Plotting : Enhancements for specialized plots can be found in plotrix, for polar plotting, vcd for categorical data, hexbin (on Bioconductor ) for hexagon binning, gclus for ordering plots and gplots for some plotting enhancements. Some specialized graphs, like Chernoff faces are implemented in aplpack, which also has a nice implementation of Tukey’s bag plot. For 3D plots latticescatterplot3d and misc3d provide a selection of plots for different kinds of 3D plotting. scatterplot3d is based on R’s base graphics system, while misc3d is based on rgl. The package onion for visualizing quaternions and octonions is well suited to display 3D graphics based on derived meshes.
  • Graphic Applications : This area is not much different from the plotting section except that these packages have tools that may not for display, but can aid in creating effective displays. Also included are packages with more esoteric plotting methods. For specific subject areas, like maps, or clustering the excellent task views contributed by other dedicated useRs is an excellent place to start.
    • Effect ordering : The gclus package focuses on the ordering of graphs to accentuate cluster structure or natural ordering in the data. While not for graphics directly cba and seriation have functions for creating 1 dimensional orderings from higher dimensional criteria. For ordering an array of displays, biclust can be useful.
    • Large Data Sets : Large data sets can present very different challenges from moderate and small datasets. Aside from overplotting, rendering 1,000,000 points can tax even modern GPU’s. For univariate datalvplot produces letter value boxplots which alleviate some of the problems that standard boxplots exhibit for large data sets. For bivariate data ash can produce a bivariate smoothed histogram very quickly, and hexbin, on Bioconductor , can bin bivariate data onto a hexagonal lattice, the advantage being that the irregular lines and orientation of hexagons do not create linear artifacts. For multivariate data, hexbin can be used to create a scatterplot matrix, combined with lattice. An alternative is to use scagnostics to produce a scaterplot matrix of “data about the data”, and look for interesting combinations of variables.
    • Trees and Graphs ape and ade4 have functions for plotting phylogenetic trees, which can be used for plotting dendrograms from clustering procedures. While these packages produce decent graphics, they do not use sophisticated algorithms for node placement, so may not be useful for very large trees. igraph has the Tilford-Rheingold algorithm implementead and is useful for plotting larger trees. diagram as facilities for flow diagrams and simple graphs. For more sophisticated graphs Rgraphviz and igraph have functions for plotting and layout, especially useful for representing large networks.
  • Graphics Systems lattice is built on top of the grid graphics system and is an R implementation of William Cleveland’s trellis system for S-PLUS. lattice allows for building many types of plots with sophisticated layouts based on conditioning. ggplot2 is an R implementation of the system described in “A Grammar of Graphics” by Leland Wilkinson. Like latticeggplot (also built on top of grid) assists in trellis-like graphics, but allows for much more. Since it is built on the idea of a semantics for graphics there is much more emphasis on reshaping data, transformation, and assembling the elements of a plot.
  • Devices : Whereas grid is built on top of the R graphics engine, many in the R community have found the R graphics engine somewhat inflexible and have written separate device drivers that either emphasize interactivity or plotting in various graphics formats. R base supplies devices for PostScript, PDF, JPEG and other formats. Devices on CRAN include cairoDevice which is a device based libcairo, which can actually render to many device types. The cairo device is desgned to work with RGTK2, which is an interface to the Gimp Tool Kit, similar to pyGTK2. GDD provides device drivers for several bitmap formats, including GIF and BMP. RSvgDevice is an SVG device driver and interfaces well with with vector drawing programs, or R web development packages, such as Rpad. When SVG devices are for web display developers should be aware that internet explorer does not support SVG, but has their own standard. Trust Microsoft. rgl provides a device driver based on OpenGL, and is good for 3D and interactive development. Lastly, the Augsburg group supplies a set of packages that includes a Java-based device, JavaGD.
  • Colors : The package colorspace provides a set of functions for transforming between color spaces and mixcolor() for mixing colors within a color space. Based on the HCL colors provided in colorspacevcdprovides a set of functions for choosing color palettes suitable for coding categorical variables ( rainbow_hcl()) and numerical information ( sequential_hcl()diverge_hcl()). Similar types of palettes are provided in RColorBrewer and dichromat is focused on palettes for color-impaired viewers.
  • Interactive Graphics : There are several efforts to implement interactive graphics systems that interface well with R. In an interactive system the user can interactively query the graphics on the screen with the mouse, or a moveable brush to zoom, pan and query on the device as well as link with other views of the data. rggobi embeds the GGobi interactive graphics system within R, so that one can display a data frame or several in GGobi directly from R. The package has functions to support longitudinal data, and graphs using GGobi’s edge set functionality. The RoSuDA repository maintained and developed by the University of Augsburg group has two packages, iplots and iwidgets as well as their Java development environment including a Java device, JavaGD. Their interactive graphics tools contain functions for alpha blending, which produces darker shading around areas with more data. This is exceptionally useful for parallel coordinate plots where many lines can quickly obscure patterns. playwith has facilities for building interactive versions of R graphics using the cairoDevice and RGtk2. Lastly, the rgl package has mechanisms for interactive manipulation of plots, especially 3D rotations and surfaces.
  • Development : For development of specialized graphics packages in R, grid should probably be the first consideration for any new plot type. rgl has better tools for 3D graphics, since the device is interactive, though it can be slow. An alternative is to use Java and the Java device in the RoSuDA packages, though Java has its own drawbacks. For porting plotting code to grid, using the package gridBase presents a nice intermediate step to embed base graphics in grid graphics and vice versa.

Windows Azure and Amazon Free offer

Simple Cpu Cache Memory Organization
Image via Wikipedia

For Hi-Computing folks try out Azure for free-

http://www.microsoft.com/windowsazure/offers/popup/popup.aspx?lang=en&locale=en-US&offer=MS-AZR-0001P#compute

Windows Azure Platform
Introductory Special

This promotional offer enables you to try a limited amount of the Windows Azure platform at no charge. The subscription includes a base level of monthly compute hours, storage, data transfers, a SQL Azure database, Access Control transactions and Service Bus connections at no charge. Please note that any usage over this introductory base level will be charged at standard rates.

Included each month at no charge:

  • Windows Azure
    • 25 hours of a small compute instance
    • 500 MB of storage
    • 10,000 storage transactions
  • SQL Azure
    • 1GB Web Edition database (available for first 3 months only)
  • Windows Azure platform AppFabric
    • 100,000 Access Control transactions
    • 2 Service Bus connections
  • Data Transfers (per region)
    • 500 MB in
    • 500 MB out

Any monthly usage in excess of the above amounts will be charged at the standard rates. This introductory special will end on March 31, 2011 and all usage will then be charged at the standard rates.

Standard Rates:

Windows Azure

  • Compute*
    • Extra small instance**: $0.05 per hour
    • Small instance (default): $0.12 per hour
    • Medium instance: $0.24 per hour
    • Large instance: $0.48 per hour
    • Extra large instance: $0.96 per hour

 

http://aws.amazon.com/ec2/pricing/

Free Tier*

As part of AWS’s Free Usage Tier, new AWS customers can get started with Amazon EC2 for free. Upon sign-up, new AWScustomers receive the following EC2 services each month for one year:

  • 750 hours of EC2 running Linux/Unix Micro instance usage
  • 750 hours of Elastic Load Balancing plus 15 GB data processing
  • 10 GB of Amazon Elastic Block Storage (EBS) plus 1 million IOs, 1 GB snapshot storage, 10,000 snapshot Get Requests and 1,000 snapshot Put Requests
  • 15 GB of bandwidth in and 15 GB of bandwidth out aggregated across all AWS services

 

Paid Instances-

 

Standard On-Demand Instances Linux/UNIX Usage Windows Usage
Small (Default) $0.085 per hour $0.12 per hour
Large $0.34 per hour $0.48 per hour
Extra Large $0.68 per hour $0.96 per hour
Micro On-Demand Instances
Micro $0.02 per hour $0.03 per hour
High-Memory On-Demand Instances
Extra Large $0.50 per hour $0.62 per hour
Double Extra Large $1.00 per hour $1.24 per hour
Quadruple Extra Large $2.00 per hour $2.48 per hour
High-CPU On-Demand Instances
Medium $0.17 per hour $0.29 per hour
Extra Large $0.68 per hour $1.16 per hour
Cluster Compute Instances
Quadruple Extra Large $1.60 per hour N/A*
Cluster GPU Instances
Quadruple Extra Large $2.10 per hour N/A*
* Windows is not currently available for Cluster Compute or Cluster GPU Instances.

 

NOTE- Amazon Instance definitions differ slightly from Azure definitions

http://aws.amazon.com/ec2/instance-types/

Available Instance Types

Standard Instances

Instances of this family are well suited for most applications.

Small Instance – default*

1.7 GB memory
1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit)
160 GB instance storage
32-bit platform
I/O Performance: Moderate
API name: m1.small

Large Instance

7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large

Extra Large Instance

15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge

Micro Instances

Instances of this family provide a small amount of consistent CPU resources and allow you to burst CPU capacity when additional cycles are available. They are well suited for lower throughput applications and web sites that consume significant compute cycles periodically.

Micro Instance

613 MB memory
Up to 2 EC2 Compute Units (for short periodic bursts)
EBS storage only
32-bit or 64-bit platform
I/O Performance: Low
API name: t1.micro

High-Memory Instances

Instances of this family offer large memory sizes for high throughput applications, including database and memory caching applications.

High-Memory Extra Large Instance

17.1 GB of memory
6.5 EC2 Compute Units (2 virtual cores with 3.25 EC2 Compute Units each)
420 GB of instance storage
64-bit platform
I/O Performance: Moderate
API name: m2.xlarge

High-Memory Double Extra Large Instance

34.2 GB of memory
13 EC2 Compute Units (4 virtual cores with 3.25 EC2 Compute Units each)
850 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.2xlarge

High-Memory Quadruple Extra Large Instance

68.4 GB of memory
26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.4xlarge

High-CPU Instances

Instances of this family have proportionally more CPU resources than memory (RAM) and are well suited for compute-intensive applications.

High-CPU Medium Instance

1.7 GB of memory
5 EC2 Compute Units (2 virtual cores with 2.5 EC2 Compute Units each)
350 GB of instance storage
32-bit platform
I/O Performance: Moderate
API name: c1.medium

High-CPU Extra Large Instance

7 GB of memory
20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: c1.xlarge

Cluster Compute Instances

Instances of this family provide proportionally high CPU resources with increased network performance and are well suited for High Performance Compute (HPC) applications and other demanding network-bound applications. Learn more about use of this instance type for HPC applications.

Cluster Compute Quadruple Extra Large Instance

23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge

Cluster GPU Instances

Instances of this family provide general-purpose graphics processing units (GPUs) with proportionally high CPU and increased network performance for applications benefitting from highly parallelized processing, including HPC, rendering and media processing applications. While Cluster Compute Instances provide the ability to create clusters of instances connected by a low latency, high throughput network, Cluster GPU Instances provide an additional option for applications that can benefit from the efficiency gains of the parallel computing power of GPUs over what can be achieved with traditional processors. Learn moreabout use of this instance type for HPC applications.

Cluster GPU Quadruple Extra Large Instance

22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge

versus-

Windows Azure compute instances come in five unique sizes to enable complex applications and workloads.

Compute Instance Size CPU Memory Instance Storage I/O Performance
Extra Small 1 GHz 768 MB 20 GB* Low
Small 1.6 GHz 1.75 GB 225 GB Moderate
Medium 2 x 1.6 GHz 3.5 GB 490 GB High
Large 4 x 1.6 GHz 7 GB 1,000 GB High
Extra large 8 x 1.6 GHz 14 GB 2,040 GB High

*There is a limitation on the Virtual Hard Drive (VHD) size if you are deploying a Virtual Machine role on an extra small instance. The VHD can only be up to 15 GB.

 

 

Amazon goes HPC and GPU: Dirk E to revise his R HPC book

Looking south above Interstate 80, the Eastsho...
Image via Wikipedia

Amazon just did a cluster Christmas present for us tech geek lizards- before Google could out doogle them with end of the Betas (cough- its on NDA)

Clusters used by Academic Departments now have a great chance to reduce cost without downsizing- but only if the CIO gets the email.

While Professor Goodnight of SAS / North Carolina University is still playing time sharing versus mind sharing games with analytical birdies – his 70 mill server farm set in Feb last is about to get ready

( I heard they got public subsidies for environment- but thats historic for SAS– taking public things private -right Prof as SAS itself began as a publicly funded project. and that was in the 1960s and they didnt even have no lobbyists as well. )

In realted R news, Dirk E has been thinking of a R HPC book without paying attention to Amazon but would now have to include Amazon

(he has been thinking of writing that book for 5 years, but hey he’s got a day job, consulting gigs with revo, photo ops at Google, a blog, packages to maintain without binaries, Dirk E we await thy book with bated holes.

Whos Dirk E – well http://dirk.eddelbuettel.com/ is like the Terminator of R project (in terms of unpronounceable surnames)

Back to the cause du jeure-

 

From http://aws.amazon.com/ec2/hpc-applications/ but minus corporate buzz words.

 

Unique to Cluster Compute and Cluster GPU instances is the ability to group them into clusters of instances for use with HPC

applications. This is particularly valuable for those applications that rely on protocols like Message Passing Interface (MPI) for tightly coupled inter-node communication.

Cluster Compute and Cluster GPU instances function just like other Amazon EC2 instances but also offer the following features for optimal performance with HPC applications:

  • When run as a cluster of instances, they provide low latency, full bisection 10 Gbps bandwidth between instances. Cluster sizes up through and above 128 instances are supported.
  • Cluster Compute and Cluster GPU instances include the specific processor architecture in their definition to allow developers to tune their applications by compiling applications for that specific processor architecture in order to achieve optimal performance.

The Cluster Compute instance family currently contains a single instance type, the Cluster Compute Quadruple Extra Large with the following specifications:

23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge

The Cluster GPU instance family currently contains a single instance type, the Cluster GPU Quadruple Extra Large with the following specifications:

22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge

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