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Re: Parallelize NonlinearModelFit

  • To: mathgroup at smc.vnet.net
  • Subject: [mg109576] Re: Parallelize NonlinearModelFit
  • From: Bill Rowe <readnews at sbcglobal.net>
  • Date: Thu, 6 May 2010 04:51:10 -0400 (EDT)

On 5/5/10 at 6:05 AM, obrie425 at umn.edu (Dan O'Brien) wrote:

<details snipped>

>Here "d" "m", and "p" are formatted corrected for the necessary
>arguements for NonlinearModelFit (sequential evaluation proceeds
>without any errors).  From the documentation I believe I have set
>everything necessary to parallelize, and NonlinearModelFit should
>greatly benefit from parallelization in terms of computational time.
>Is it just that this function hasn't been set internally by
>Mathematica to be able to thread its computations?

My guess is the issue has to do with how parallel processing is
implemented. Problems that can easily be split up into smaller
chunks where you do the same thing to each chunk then assemble
the results from each chunk for the final answer are fairly
simple to run as a parallel process. But the characteristic of
being easily split up doesn't seem to me to be a characteristic
non-linear regression problem.

=46or the general non-linear regression problem, you won't be able
to find an optimum value for one of the parameters in isolation
from the other unknown parameters. Consequently, there is no
obvious way to parallelize this class of problem.

But if you are doing the same non-linear fit to several data
sets, it should be possible to take advantage of parallel
processing using perhaps ParallelTable.



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