rdiaz02 at gmail.com
Tue Nov 20 15:59:55 CET 2012
On Sat, 17 Nov 2012 13:05:29 -0800,"Ryan C. Thompson" <rct at thompsonclan.org> wrote:
> On 11/17/2012 02:39 AM, Ramon Diaz-Uriarte wrote:
> > In addition to Steve's comment, is it really a good thing that "all code
> > stays the same."? I mean, multiple machines vs. multiple cores are,
> > often, _very_ different things: for instance, shared vs. distributed
> > memory, communication overhead differences, whether or not you can assume
> > packages and objects to be automagically present in the slaves/child
> > process, etc. So, given they are different situations, I think it
> > sometimes makes sense to want to write different code for each situation
> > (I often do); not to mention Steve's hybrid cases ;-).
> > Since BiocParallel seems to be a major undertaking, maybe it would be
> > appropriate to provide a flexible approach, instead of hard wiring the
> > foreach approach.
> Of course there are cases where the same code simply can't work for both
> multicore and multi-machine situations, but those generally don't fall
> into the category of things that can be done using lapply. Lapply and
> all of its parallelized buddies like mclapply, parLapply, and foreach
> are designed for data-parallel operations with no interdependence
> between results, and these kinds of operations generally parallelize as
> well across machines as across cores, unless your network is not fast
> enough (in which case you would choose not to use multi-machine
> parallelism). If you want a parallel algorithm for something like the
> disjoin method of GRanges, you might need to write some special purpose
> code, and that code might be very different for multicore vs multi-machine.
> So yes, sometimes there is a fundamental reason that you have to change
> the code to make it run on multiple machines, and neither foreach nor
> any other parallelization framework will save you from having to rewrite
> your code. But often there is no fundamental reason that the code has to
> change, but you end up changing it anyway because of limitations in your
> parallelization framework. This is the case that foreach saves you from.
Hummm... I guess you are right, and we are talking about "often" or "most
of the time", which is where all this would fit. Point taken.
Department of Biochemistry, Lab B-25
Facultad de Medicina
Universidad Autónoma de Madrid
Arzobispo Morcillo, 4
Email: rdiaz02 at gmail.com
ramon.diaz at iib.uam.es
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