mpi-sppy: Optimization Under Uncertainty for Pyomo

Bernard Knueven, David Mildebrath, Christopher Muir, John Siirola, David Woodruff, Jean-Paul Watson

Research output: NRELPresentation


We introduce a new Pyomo extension for optimization under uncertainty, mpi-sppy. This extension allows for the mixing of, and sharing of information between, various algorithmic approaches for optimization under uncertainty. We will discuss the underlying architecture and assess the performance and scalability of mpi-sppy on various systems, including HPC clusters.
Original languageAmerican English
Number of pages16
StatePublished - 2020

Publication series

NamePresented at the INFORMS Annual Meeting 2020, 9-13 November 2020

NREL Publication Number

  • NREL/PR-2C00-78043


  • parallel programming
  • stochastic optimization
  • unit commitment


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