Who uses R with multicore, SNOW or CUDA package for resource intense computing? Who of you in this forum uses ">R with the multicore, snow packages, or CUDA, so for advanced calculations that need more power than a workstation CPU? On which hardware do you compute these scripts? At home/work or do you have data center access somewhere?
The background of these questions is the following: I am currently writing my M.Sc. thesis about R and High Performance Computing and need a strong knowledge about who actually uses R. I read that R had 1 million users in 2008, but that's more or less the only user statistics I could find on this topic - so I hope for your answers!
Sincerely Heinrich
 A: I am a biologist who models the effects of inter-annual climatic variation on population dynamics of several migratory species. My datasets are very large (spatially intensive data) so I run my R code using multicore on Amazon EC2 servers. If my task is particularly resource intensive, I will choose a High Memory Quadruple Extra Large instance which comes with 26 CPU units, 8 cores, and 68G of RAM. In this case I usually run 4-6 scripts simultaneously, each of which is working through a fairly large data set. For smaller tasks, I choose servers with 4-6 cores and about 20 gigs of RAM.
I launch these instances (usually spot instances because they are cheaper but can terminate anytime the current rate exceeds what I have chosen to pay), run the script for several hours, and then terminate the instance once my script has finished. As for the machine image (Amazon Machine Image), I took someone elses Ubuntu install, updated R, installed my packages, and saved that as my private AMI on my S3 storage space.
My personal machine is a dualcore macbook pro and it has a hard time forking multicore calls. Feel free to email if you have other questions.
A: Since you ask, I am using the foreach package with the multicore backend. I use it to split an embarrassingly parallel workload across multiple cores on a single Nehalem box with lots of RAM. This works pretty well for the task at hand.
A: I work in academy and I'm using multicore for some heavy benchmarks of machine learning algorithms, mostly on our Opteron based Sun Constellation and some smaller clusters; those are also rather embarrassingly parallel problems so multicore's main role is to spread computation over node without multiplication of memory usage.
A: I use snow and snowfall for course parallelization on HPC clusters and CUDA for fine data parallel processing.  I'm in Epidemiology doing disease transmission modeling.  So I use both.
