Turns out it is a bug in the mcmapply() code -- when the number of jobs is
less than the number of cores, then the function routes it to standard
mapply() rather than letting the jobs run in parallel.  Sorry for the red
herring.

-Aaron

On Mon, Aug 13, 2012 at 1:14 PM, Martin Morgan <mtmorgan@fhcrc.org> wrote:

> On 08/13/2012 10:07 AM, Aaron Mackey wrote:
>
>> I have mcmapply (and related parallel library functions) working fine with
>> example code, but when I try to run my own function (which makes calls to
>> estimateGLMCommonDisp, etc) in parallel, only one core remains engaged, no
>> forking happens.  The only thing I can imagine is that the parallel
>> library
>> has detected my use of a dynamically loaded .so, and has reverted to
>> serial
>> behavior?  Or is edgeR preventing it's functions from being fork'ed
>> somehow?
>>
>
> using a shared object shouldn't be a problem with mclapply (rather than
> mcmapply, which is not from the parallel library?); maybe you can create a
> short script that has the essentials for someone else to evaluate, maybe
> using small simulated data, perhaps from one of the help pages of edgeR?
>
> Martin
>
>
>> Thanks in advance,
>> -Aaron
>>
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