subscribe to R-hpc. and check out these: https://github.com/armstrtw/rzmq https://github.com/armstrtw/AWS.tools https://github.com/armstrtw/deathstar
and this: http://code.google.com/p/segue/ If you're willing to work, you can probably get deathstar to work using a local windows box and remote linux nodes. -Whit On Wed, Dec 7, 2011 at 6:02 PM, Ben quant <ccqu...@gmail.com> wrote: > Hello, > > I'm working with the gam function and due to the amount of data I am > working with it is taking a long time to run. I looked at the tips to get > it to run faster, but none have acceptable side effects. That is the real > problem. > > I have accepted that gam will run a long time. I will be running gam many > times for many different models. To make gam useable I am looking at > splitting the work up and putting all of it on an Amazon EC2 cloud. I have > a Windows machine and I'm (planning on) running Linux EC2 instances via > Amazon. > > I have R running on one EC2 instance now. Now I'm looking to: > > 1) division of processing > 2) creating/terminating instances via R > 3) porting code and data to the cloud > 4) producing plots on the cloud and getting them back on my (Windows) > computer for review > 5) do all of the above programmically (over night) > > I am new'ish to R, brand new to the cloud, and I am new to Linux (but I > have access to a Linux expert at my company). I'm looking for 1) guidance > so I am headed in the best direction from the start, 2) any gotchas I can > learn from, 3) package suggestions. > > Thank you very much for your assistance! > > Regards, > > Ben > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
