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One thing I can think of is that R is not well suited for computationally expensive work --- by "computationally expensive" I mean something that takes months t
by geoalchimista 7y ago
One thing I can think of is that R is not well suited for computationally expensive work --- by "computationally expensive" I mean something that takes months to run on a cluster. Not only is R 100--1000x slower than Fortran, but it also does not have strong support for parallelism or GPU computing. I have yet to see a computational fluid dynamicist using R. Though Python is also not much better in that aspect, it can be used as a glue language to interact with native C/C++/Fortran code under the hood.
- tylermw 7y agoR has interfaces for Fortran, C, and C++ as well. Quite good ones, in fact.
- gnufx 7y agoR is actually the basis of one of the CORAL2 benchmark sets, and there are published scaling results to 5000 cores as far as I remember. I've not done it, but presumably you can substitute its BLAS with a GPU version, the same as with an OpenMP-parallelized one to get performance for anything linear algebra-ish. [HPC clusters on which you'd run CFD typically don't let you run for more than days, let alone months. There's probably no reason you couldn't use R the same way as Python for such things.]