Pyomo parallel processing to solve an instance

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​​​I'm following the steps here in order to use all my computing power (10-core Intel i9 CPU) and solve a one-instance abstract Pyomo model. However, it seems that the solver is just using one CPU core and it takes more than 2 days to return a solution for a 50-node input (with 10 nodes it just takes seconds.) any help about making Pyomo model run in all available CPU cores?

Thanks

Sep 11, 2018 in Python by bug_seeker
• 15,360 points
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1 answer to this question.

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Depends on the solver and the model. Some solvers are single threaded others operate in parallel. Typically, MIP models can benefit a lot from parallel processing. LPs not as much (some interior point methods do a reasonable job). Beware that you need a ton of memory to allow the solver to run the model in parallel on many cores.

answered Sep 11, 2018 by Priyaj
• 57,300 points

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