CODEWITHSUNDEEP
roptimizationparallel-processingcontinuous
Mathieu
Mathieu

Reputation: 43

R: DEoptim parallel optimization - number of cores

I'm trying to use DEoptim optimization package in R on a continuous optimization problem, and as my cost function takes a long time to evaluate (2min), I'm trying to use parallel computation. My questions are:

  1. What's the difference between paralleltype=1 (parallel) and 2 (foreach) option ? When to use one of the two ?

  2. Is it possible to specify the number of cores with paralleltype=1, in order not to take all the available cores for computing (50 cores on 64 cores available, for instance)?

Upvotes: 4

Views: 1576

Answers (2)

Anika
Anika

Reputation: 1

Thank you for your code mjaniec!

I know it has been a while since you posted it, but I think in line 91 it should be: 

cl <- parallel::makeCluster(useCores)

instead of:

cl <- parallel::makeCluster(parallel::detectCores())

Upvotes: 0

mjaniec
mjaniec

Reputation: 1114

ad. 1 - It is explained in the package documentation.

ad. 2 - Requires some tinkering with two functions: DEoptim.control and DEoptim

First, add a variable - say limitCores - to DEoptim.control function, which controls execution parameters of the DE optimization.

Second, introduce modification to the DEoptim wrapper function to act on the limitation set by limitCores.

if (ctrl$parallelType == 1) {

    if (!is.na(ctrl$limitCores)) {

        if (ctrl$limitCores<1) useCores <- round(parallel::detectCores()*ctrl$limitCores) else useCores <- ctrl$limitCores

        cl <- parallel::makeCluster(parallel::detectCores())

    } else {

        cl <- parallel::makeCluster(parallel::detectCores())

    }

Complete code: http://pastebin.com/NumDx4ae

Upvotes: 1

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