Hi All,
I have been reading about general purpose GPU (graphical processing units) computing for computational statistics. I know very little about this, but I read that GPUs currently cannot handle double-precision floating points and also that they are not necessarily IEEE compliant. However, I am not sure what the practical impact of this limitation is likely to be on computational statistics problems (e.g. optimization, multivariate analysis, MCMC, etc.). What are the main obstacles that are likely to prevent widespread use of this technology in computational statistics? Can algorithms be coded in R to take advantage of the GPU architecture to speed up computations? I would appreciate hearing from R sages about their views on the usefulness of general purpose GPU (graphical processing units) computing for computational statistics. I would also like to hear about views on the future of GPGPU - i.e. is it here to stay or is it just a gimmick that will quietly disappear into the oblivion. Thanks very much. Best regards, Ravi. ---------------------------------------------------------------------------- ------------------------------ Ravi Varadhan, Ph.D. Assistant Professor, Center on Aging and Health, Johns Hopkins University School of Medicine (410)502-2619 rvarad...@jhmi.edu http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.h tml [[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.
