  This paper introduces the Exascale Grid Optimization (ExaGO) toolkit, a
library for solving large-scale alternating current optimal power flow (ACOPF)
problems including stochastic effects, security constraints and multi-period
constraints. ExaGO can run on parallel distributed memory platforms, including
massively parallel hardware accelerators such as graphical processing units
(GPUs). We present the details of the ExaGO library including its architecture,
formulations, modeling details, and its performance for several optimization
applications.
