Here is an interesting training from Revolution Computing
New Training Course from REvolution Computing
High-Performance Computing with R
July 31, 2009 – Washington, DC – Prior to JSM
Time: 9am – 5pm
$600 commercial delegates, $450 government, $250 academic
An overview of available HPC technologies for the R language to enable faster, scalable analytics that can take advantage of multiprocessor capability will be presented in a one-day course. This will include a comprehensive overview of REvolution’s recently released R packages foreach and iterators, making parallel programming easier than ever before for R programmers, as well as other available technologies such as RMPI, SNOW and many more. We will demonstrate each technology with simple examples that can be used as starting points for more sophisticated work. The agenda will also cover:
- Identifying performance problems
- Profiling R programs
- Multithreading, using compiled code, GPGPU
- Multiprocess computing
- SNOW, MPI, NetWorkSpaces, and more
- Batch queueing systems
- Dealing with lots of data
Attendees should have basic familiarity with the R language—we will keep examples elementary but relevant to real-world applications.
This course will be conducted hands-on, classroom style. Computers will not be provided. Registrants are required to bring their own laptops.
Disclaimer- I am NOT commerically related to REvolution, just love R. I do hope REvolution chaps do spend tiny bit of time improving the user GUI as well not just for HPC purposes.
They recently released some new packages free to the CRAN community as well
The release of 3 new packages for R designed to allow all R users to more quickly handle large, complex sets of data: iterators, foreach and doMC.
* 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. This makes loops run faster on a multi-core laptop, and enables distribution of large parallel-processing problems to multiple workstations in a cluster or in the cloud, without additional complicated programming. foreach 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 enables foreach and iterator functions to work with the “multicore” package from R Core member Simon Urbanek
The new packages have been developed by REvolution Computing and released under open source licenses to the R community, enabling all existing R users