Hi Charles, You can have a look at the MinFinder algorithm for which I've just created a pull request to Optim.jl (talk about a coincidence!): https://github.com/JuliaOpt/Optim.jl/pull/72
I'd like to add the possibility to run each optimization in parallel, but I have no experience with these things, although I have time to learn :). Would you like to collaborate on this? Does anyone know of some parallel sample code to have a look at? Basically it's sending each optimization problem to a separate worker and getting the results, taking into account that some optimizations might take much longer than others. Cheers, Ken On Saturday, 26 July 2014 23:13:28 UTC-5, Charles Martineau wrote: > > Yes I could do that but it is simpler (I think) to execute the code in > parallel instead of sending 20 codes to be executed on the cluste.r > > On Saturday, July 26, 2014 10:08:20 AM UTC-7, Michael Prentiss wrote: >> >> What you are doing makes sense. Starting from multiple starting points >> is important. >> >> I am curious why you just don't just run 20 different 1-processor jobs >> instead of bothering with the parallelism? >> >> >> On Saturday, July 26, 2014 11:22:07 AM UTC-5, Iain Dunning wrote: >>> >>> The idea is to call the optimize function multiple times in parallel, >>> not to call it once and let it do parallel multistart. >>> >>> Check out the "parallel map and loops" section of the parallel >>> programming chapter in the Julia manual, I think it'll be clearer there. >>> >>> On Friday, July 25, 2014 8:00:40 PM UTC-4, Charles Martineau wrote: >>>> >>>> Thank you for your answer. So I would have to loop over, say 20 random >>>> set of starting points, where in my loop I would use the Optim package to >>>> minimize my MLE function for each random set. Where online is the >>>> documents >>>> that shows how to specify that we want the command >>>> >>>> Optim.optimize(my function, etc.) to be parallelized? Sorry for my >>>> ignorance, I am new to Julia! >>>> >>>> >>>> On Friday, July 25, 2014 2:04:08 PM UTC-7, Iain Dunning wrote: >>>>> >>>>> I'm not familiar with that particular package, but the Julia way to do >>>>> it could be to use the Optim.jl package and create a random set of >>>>> starting >>>>> points, and do a parallel-map over that set of starting points. Should >>>>> work >>>>> quite well. Trickier (maybe) would be to just give each processor a >>>>> different random seed and generate starting points on each processor. >>>>> >>>>> On Friday, July 25, 2014 3:05:05 PM UTC-4, Charles Martineau wrote: >>>>>> >>>>>> Dear Julia developers and users, >>>>>> >>>>>> I am currently using in Matlab the multisearch algorithm to find >>>>>> multiple local minima: >>>>>> http://www.mathworks.com/help/gads/multistart-class.html for a MLE >>>>>> function. >>>>>> I use this Multisearch in a parallel setup as well. >>>>>> >>>>>> Can I do something similar in Julia using parallel programming? >>>>>> >>>>>> Thank you >>>>>> >>>>>> Charles >>>>>> >>>>>>
