[pymvpa] Parallelization
Matteo Visconti di Oleggio Castello
matteo.visconti at gmail.com
Thu Nov 9 18:35:39 UTC 2017
Hi Marco,
AFAIK, there is no support for parallelization at the level of
cross-validation. Usually for a small ROI (such a searchlight) and with
standard CV schemes, the process is quite fast, and the bottleneck is
really the number of searchlights to be computed (for which parallelization
exists).
In my experience, we tend to parallelize at the level of individual
participants; for example we might set up a searchlight analysis with
however n_procs you can have, and then submit one such job for every
participant to a cluster (using either torque or condor).
HTH,
Matteo
On Thu, Nov 9, 2017 at 4:08 AM, marco tettamanti <mrctttmnt at gmail.com>
wrote:
> Dear all,
> forgive me if this has already been asked in the past, but I was wondering
> whether there has been any development meanwhile.
>
> Are there any chances that one can generally apply parallel computing
> (multiple CPUs or clusters) with pymvpa2, in addition to what is already
> implemented for searchlight (pprocess)? That is, also for general
> cross-validation, nested cross-validation, permutation testing, RFE, etc.?
>
> Has anyone had succesful experience with parallelization schemes such as
> ipyparallel, condor or else?
>
> Thank you and best wishes!
> Marco
>
> --
> Marco Tettamanti, Ph.D.
> Nuclear Medicine Department & Division of Neuroscience
> IRCCS San Raffaele Scientific Institute
> Via Olgettina 58
> <https://maps.google.com/?q=Via+Olgettina+58&entry=gmail&source=g>
> I-20132 Milano, Italy
> Phone ++39-02-26434888
> Fax ++39-02-26434892
> Email: tettamanti.marco at hsr.it
> Skype: mtettamanti
>
>
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--
Matteo Visconti di Oleggio Castello
Ph.D. Candidate in Cognitive Neuroscience
Dartmouth College
+1 (603) 646-8665
mvdoc.me || github.com/mvdoc || linkedin.com/in/matteovisconti
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