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dc.contributor.authorBorrell Pol, Ricard
dc.contributor.authorOyarzun Altamirano, Guillermo
dc.contributor.authorDosimont, Damien
dc.contributor.authorHouzeaux, Guillaume
dc.contributor.otherBarcelona Supercomputing Center
dc.identifier.citationBorrell Pol, R. [et al.]. Parallel SFC-based mesh partitioning and load balancing. A: Parallel SFC-based mesh partitioning and load balancing. "2019 IEEE/ACM 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA): 18-18 Nov. 2019, Denver, CO, USA: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 72-78. DOI 10.1109/ScalA49573.2019.00014.
dc.description.abstractModern supercomputers allow the simulation of complex phenomena with increased accuracy. Eventually, this requires finer geometric discretizations with larger numbers of mesh elements. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, adaptation or partition, become a critical issue within the simulation workflow. In this paper, we focus on mesh partitioning. In particular, we present some improvements carried out on an in-house parallel mesh partitioner based on the Hilbert Space-Filling Curve. Additionally, taking advantage of its performance, we present the application of the SFC-based partitioning for dynamic load balancing. This method is based on the direct monitoring of the imbalance at runtime and the subsequent re-partitioning of the mesh. The target weights for the optimized partitions are evaluated using a least-squares approximation considering all measurements from previous iterations. In this way, the final partition corresponds to the average performance of the computing devices engaged.
dc.description.sponsorshipThis work is partially supported by the BSC-IBM Deep Learning Research Agreement, under JSA “Application porting, analysis and optimization for POWER and POWERAI”. It has also been partially supported by the EXCELLERAT project funded by the European Commission’s ICT activity of the H2020 Programme under grant agreement number: 823691. It has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number: 846139 (Exa-FireFlows). This paper expresses the opinions of the authors and not necessarily those of the European Commission. The European Commission is not liable for any use that may be made of the information contained in this paper. This work has also been financially supported by the Ministerio de Economia, Industria y Competitividad, of Spain (TRA2017-88508-R). The computing experiments of this paper have been performed on the resources of the Barcelona Supercomputing Center.
dc.format.extent7 p.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures paral·leles
dc.subject.lcshParallel processing (Electronic computers)
dc.subject.lcshNumerical grid generation (Numerical analysis)
dc.subject.lcshResource allocation
dc.subject.otherSpace-Filling Curve
dc.subject.otherGeometric partitioning
dc.subject.otherParallel computing
dc.subject.otherLoad Balancing
dc.titleParallel SFC-based mesh partitioning and load balancing
dc.typeConference lecture
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/823691/EU/The European Centre of Excellence for Engineering Applications/EXCELLERAT
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/846139/EU/Exascale framework for supporting high-fidelity simulations of multiphase reacting flows in complex geometries/Exa-FireFlows
local.citation.contributorParallel SFC-based mesh partitioning and load balancing
local.citation.publicationName2019 IEEE/ACM 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA): 18-18 Nov. 2019, Denver, CO, USA: proceedings

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