I have access to a machine (not a desktop) with quite a few CPUs and quite a few GPUs. So, if for example there are 100 CPU cores and 100,000 GPU cores, I guess that I could do a foreach for these 100 CPU cores for an R function, and then if this R function calls RcppArrayFire, RcppArrayFire could call 1,000 GPU cores for each call, to make the whole 100,000 GPU cores, no? Or is everything more complex than that?
Jordi Molins i Coronado +34 69 38 000 59 On Sat, Sep 22, 2018 at 7:35 PM Dirk Eddelbuettel <e...@debian.org> wrote: > > On 22 September 2018 at 17:52, Jordi Molins wrote: > | In relation to doing "CPU x GPU": what would happen if I have 3 variables > | to be parallelized (independent from each other, no interdependencies) > and > | then I create an R function, using RcppArrayFire, to GPU-parallelize two > of > | them. Then, I use foreach (or similar) in R to CPU-paralellize the third > | one (and for each variable of the third one, the R function is called, > and > | then internally, RcppArrayFire uses GPUs). > > Just because you want to access ONE gpu device N times does not make it N > gpus. > > And as you have only one GPU, if you call it N times "in parallel" (we > know: > time sliced) you get contention. > > No different from having OpenBLAS or Intel MKL using ALL your cores for > matrix algebra. If you can that from any of the R process parallel helpers > you get contention. All this is well documented. > > Dirk > > -- > http://dirk.eddelbuettel.com | @eddelbuettel | e...@debian.org >
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