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윤의성

Yoon, Eisung
Fusion and Plasma Application Research Lab.
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dc.citation.conferencePlace US -
dc.citation.endPage 80 -
dc.citation.startPage 73 -
dc.citation.title 9th IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, ScalA 2018 -
dc.contributor.author Diamond, Gerrett -
dc.contributor.author Smith, Cameron W. -
dc.contributor.author Yoon, Eisung -
dc.contributor.author Shephard, Mark S. -
dc.date.accessioned 2024-02-01T01:06:35Z -
dc.date.available 2024-02-01T01:06:35Z -
dc.date.created 2018-12-30 -
dc.date.issued 2018-11-12 -
dc.description.abstract Extracting performance from simulations with complex information dependencies on massively parallel computers requires the computational work to be evenly distributed across the processing resources while maintaining low communication costs. Plasma simulations using a particle-in-cell method and computational fluid dynamics using unstructured mesh-based finite element and volume methods present three distinct distribution requirements. To meet these needs, we present EnGPar’s diffusive partition improvement method. An initial demonstration of EnGPar’s particle distribution improvement is provided along with fluid dynamics mesh partition improvement results on up
to 512Ki processes on an IBM BlueGene/Q.
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dc.identifier.bibliographicCitation 9th IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, ScalA 2018, pp.73 - 80 -
dc.identifier.doi 10.1109/ScalA.2018.00013 -
dc.identifier.scopusid 2-s2.0-85063080614 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/80466 -
dc.identifier.url https://ieeexplore.ieee.org/document/8638110 -
dc.language 영어 -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.title Dynamic Load Balancing of Plasma and Flow Simulations -
dc.type Conference Paper -
dc.date.conferenceDate 2018-11-12 -

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