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Scalability of parareal for large power grid simulations

Joseph, FC and Gurrala, G (2019) Scalability of parareal for large power grid simulations. In: 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), 5-7 Dec. 2019, Gold Coast, Australia, Australia, pp. 295-300.

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Official URL: https://dx.doi.org/10.1109/PDCAT46702.2019.00061

Abstract

The Parareal in time algorithm belongs to a class of temporal decomposition for a time parallel solution of differential equations. This paper investigates the approaches through which the Parareal algorithm can be deployed under a Message Passing Interface (MPI) environment. A state space model of a 10 state cascaded � network model of a transmission line, representing the computational load and nature of ordinary differential equations (ODE) in an electrical power grid/system, is used for experimentation. Two types of implementation approaches, Master Worker and Distributed, are discussed and scaling tests are performed. Analytical expressions for each approach based on the idling and non-idling processor deployment are derived. Using the expressions, weak scaling is performed to show the conditional scalability of Parareal under growing state size and integration steps. © 2019 IEEE.

Item Type: Conference Paper
Publication: Proceedings - 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: cited By 0; Conference of 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019 ; Conference Date: 5 December 2019 Through 7 December 2019; Conference Code:158474
Keywords: Message passing; Ordinary differential equations; Scalability; State space methods, Analytical expressions; Computational loads; Implementation approach; Message passing interface; Ordinary differential equation (ODE); Parareal algorithms; State - space models; Temporal decomposition, Electric power transmission networks
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 04 Sep 2020 10:10
Last Modified: 04 Sep 2020 10:10
URI: http://eprints.iisc.ac.in/id/eprint/65252

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