Thanks for your reply.
Okay, I just read this
and it seems that LinuxPMI is multi-system-image software, which looks like SSI, but from the perspective of each node. So it is sort-of-SSI (see also here
). Still, I'm not 100% sure what the difference between Beowulf and SSI is (but see also second point below).
The way I understand things is that Beowulf is different from SSI because with Beowul you have a master node and slave nodes (which you do not have with SSI). So if you want to tailor your programs using MPI
, then using a Beowulf is better (this is probably called explicit parallelism
). If you just want to run some programs without explicit parallel programming, use something like LinuxPMI, but the speed gains might be lower than with Beowulf (i.e. implicit parallelism
). Please correct me if I'm wrong (which might very well be the case).
By Eucalyptus I mean this
. My point is not if one can use it with R in a cloud (most likely yes), but whether or not it would result in a meaningful speed improvement without having to explicitly code R in a parallel way (i.e. implicit parallelism).
I'm in general open to alternatives to R. But since R is the lingua franca in statistics, I want to focus (at least for now) on R. See also this R task view
. Is there a particular alternative that you might have in mind, i.e. an alternative that would work in some way better than R in a cluster?