I am running optimizations using different algorithms within the NLopt.jl package. Memory slowly builds until the julia process is killed. I thought the problem might be that the NLopt opt objects leaks some memory so I tried the following code after each optimization run (there is a big loop running multiple optimization runs after each other) to release the NLopt::Opt object saved in my nlopt in "slot" named "opt" object:
# Overwrite the opt object to try to give back its memory. There seems to be mem leaks # when we have long-running opt runs: NLopt.destroy(nlopt.opt) # Not sure what is the effect of this but we try... nlopt.opt = nothing gc() but memory keeps building. I guess it could be in my (large and very complex and thus hard to distill down to an example) code used in the fitness function that NLopt calls out to but this is normal Julia code and should be garbage collected. I realize it is hard to debug without more concrete code but if anyone has ideas on why the Julia process might slowly but continuously be increasing its mem use (I'm running on a MacBoock Pro with Yosemite) I'd appreciate any tips/pointers or how to debug further. Each NLopt run is on the order of 15 minutes with around 2000 function evaluations. Regards, Robert Feldt
