REvolution Computing Demos "R" in Risk, Genomics and Statistical Computation

The company also announced that it is providing a training course, prior to the Joint Stat Conference, on July 31 in High Performance Computing with R for the R language to help faster, scalable analytics that can take advantage of multiprocessor capability. The one-day effort will take place at the Intel (News - Alert) Government Affairs Office in Washington, D.C.

The company said officials will give a presentation on open source predictive analytics titled “Why We Don’t Understand Risk and How it Dooms Us All,” at the Open Source Convention (OSCON) July 20 to 24 at the McEnery Convention Center in San Jose, Calif. In its most basic understood computational form, ‘Risk” generally is the prediction and understanding of all parameters and their behaviour patterns in any given project, with a special and highlighted focus on what can go wrong, and good “Risk” program offer decision makers the best possible solutions to circumvent predicted road blocks.

REvolution Computing said it will be giving a workshop titled “Parallel Computing in R,” and demonstrating how to deploy R programming across multiple workstations and clusters to ramp up speed computations at Bioconductor (BioC 2009) July 27 to 28 at the Fred Hutchinson Cancer Research Center in Seattle. It will also demo the use of its new “iterator” and “foreach” packages from CRAN, which it recently developed and released.

 The 2009 Joint Statistical Meetings (JSM, which takes place Aug. 1 to 6 at the Walter E. Washington Convention Center in Washington is reportedly one of the largest stat conferences because it is being held jointly by the American Statistical Association, the International Biometric Society, the Institute of Mathematical Statistics, The Statistical Society of Canada, the International Chinese Statistical Association and the International Indian Statistical Association. REvolution officials will present, “Data Display for Large Complex Datasets,” “gsDesign for Clinical Trials,” and “Parallel Statistical Computing with R,” at the upcoming JSA. 

Earlier on July 1, REvolution released the three new packages - iterators, foreach and doMC - it is showcasing at the conferences. These allow all R users to more quickly handle large, complex sets of data, and enhance REvolution R Enterprise's high-performance computing functionality, which is unavailable in any other distribution.

Iterators implements the "iterator" data structure familiar to users of languages like Java, C# and Python to make it easy to program useful sequences - from all the prime numbers to the columns of a matrix or the rows of an external database.

Foreach builds on the "iterators" package to introduce a new way of programming loops in R. Unlike the traditional "for" loop, foreach runs multiple iterations simultaneously, in parallel, and works with parallel programming backends for R from the open-source and commercial domains.

doMC is an open source parallel programming backend to enable parallel computation with "foreach" on Unix/Linux machines. It automatically helps foreach and iterator functions work with the "multicore" packages from R.