R on the cloud

July 9, 2011
By

(This article was first published on Statistical Modeling, Causal Inference, and Social Science, and kindly contributed to R-bloggers)

Just as scientists should never really have to think much about statistics, I feel that, in an ideal world, statisticians would never have to worry about computing. In the real world, though, we have to spend a lot of time building our own tools.

It would be great if we could routinely run R with speed and memory limitations being less of a concern. One suggestion that sometimes arises is to run things on “the cloud.” So I was interested upon receiving this email from Niklas Frassa:

Time intensive calculations, as known from life science, finance or business intelligence, can now be processed at a whole new level of speed – in the Cloud. cloudnumbers.com provides an intuitive platform that enables everyone to run time consuming calculations on clusters with more than 1000 CPUs.

So far, High Performance Computing has only been accessible for large corporations and universities leading to significant competitive disadvantages for small and medium-sized companies. With cloudnumbers.com we finally make High Performance Computing accessible to everyone.

cloudnumbers.com’s scalable server environment results in minimal idle times – and great cost savings, as customers only pay for what they actually consume. Furthermore, users do no longer need a degree in computer science to be able to access the computing power of supercomputers.

I don’t know anything more about this. Feel free to comment, either on this or any better options.

P.S. Based on the comments below, this cloudnumbers.com thing doesn’t sound so wonderful, at least for people like me who are already using Rstudio.

P.P.S. See response from the company in comments below.

To leave a comment for the author, please follow the link and comment on his blog: Statistical Modeling, Causal Inference, and Social Science.

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