I'm not sure I understand the appeal of foreach. Why not do this within the
functional paradigm, i.e, parLapply?

Michael

On Fri, Nov 16, 2012 at 9:41 AM, Ryan C. Thompson <rct@thompsonclan.org>wrote:

> You could write a %dopar% backend for the foreach package, which would
> allow any code using foreach (or plyr which uses foreach) to parallelize
> using your code.
>
> On a related note, it might be nice to add Bioconductor-compatible
> versions of foreach and the plyr functions to BiocParallel if they're not
> already compatible.
>
>
> On 11/16/2012 12:18 AM, Hahne, Florian wrote:
>
>> I've hacked up some code that uses BatchJobs but makes it look like a
>> normal parLapply operation. Currently the main R process is checking the
>> state of the queue in regular intervals and fetches results once a job has
>> finished. Seems to work quite nicely, although there certainly are more
>> elaborate ways to deal with the synchronous/asynchronous issue. Is that
>> something that could be interesting for the broader audience? I could add
>> the code to BiocParallel for folks to try it out.
>> The whole thing may be a dumb idea, but I find it kind of useful to be
>> able to start parallel jobs directly from R on our huge SGE cluster, have
>> the calling script wait for all jobs to finish and then continue with some
>> downstream computations, rather than having to manually check the job
>> status and start another script once the results are there.
>> Florian
>>
>
>

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