Dear all, Probably many of you experience long computation times when estimating large number of parameters using maximum likelihood with functions that reguire numerical methods such as integration or root-finding. Maximum likelihood is an example of paralellization that could sucessfully utilize GPU. The general algorithm is described here: http://openlab-mu-internal.web.cern.ch/openlab-mu-internal/03_Documents/4_Presentations/Slides/2010-list/CHEP-Maximum-likelihood-fits-on-GPUs.pdf. Is it possible to implement this algorithm in R ? Kind regards, Oyvind Foshaug
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