dc.contributorSeveso Franco, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.contributorMarichal Raúl, Universidad de la República (Uruguay). Facultad de Ingeniería
dc.contributorDufrechou Ernesto, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.contributorEzzatti Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.creatorSeveso, Franco
dc.creatorMarichal, Raúl
dc.creatorDufrechou, Ernesto
dc.creatorEzzatti, Pablo
dc.date.accessioned2023-04-10T22:03:27Z
dc.date.accessioned2023-07-13T17:29:47Z
dc.date.available2023-04-10T22:03:27Z
dc.date.available2023-07-13T17:29:47Z
dc.date.created2023-04-10T22:03:27Z
dc.date.issued2022
dc.identifierSeveso, F., Marichal, R., Dufrechou, E. y otros. Refactoring an electric-market simulation software for massively parallel computations [Preprint] Publicado en: Latin America High Performance Computing Conference, CARLA 2022, Porto Alegre, Brazil, Sep. 26-30, 2022, pp.190-204.
dc.identifierhttps://hdl.handle.net/20.500.12008/36663
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7425200
dc.description.abstractIn the last two decades, Uruguay has been immersed in the process of significantly changing its energy generation matrix, especially by the introduction of wind and solar sources. In this context, SimSEE, a simulation and optimization software designed to help decision-making in generating and distributing electrical energy, is extensively used. The design of this tool is conceived for conventional CPUs and follows a sequential execution paradigm. This paper focuses on a refactoring of SimSEE that enables leveraging massively-parallel hardware platforms, seeking to adapt the tool for the increasing size and complexity of Uruguay’s electric market. We extend our previous ideas about reorganizing the software architecture to exploit the parallelism in each time-step of Sim-SEE’s simulation. In more detail, we present two variants following this parallelism pattern, a straightforward parallel version that requires replicating the used memory and a variant that implies limited performance restrictions but requires a minimal memory overhead.
dc.languageen
dc.rightsLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
dc.rightsLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)
dc.subjectCoarse-grained parallelism
dc.subjectElectric energy generation
dc.subjectStochastic dynamic programming
dc.subjectMemory usage
dc.titleRefactoring an electric-market simulation software for massively parallel computations
dc.typePreprint


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