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dc.contributor.authorValero-Lara, Pedro
dc.contributor.authorSirvent, Raül
dc.contributor.authorPeña, Antonio J.
dc.contributor.authorLabarta Mancho, Jesús José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2019-11-26T08:42:03Z
dc.date.available2021-04-01T00:28:41Z
dc.date.issued2019-05
dc.identifier.citationValero-Lara, P. [et al.]. MPI+OpenMP tasking scalability for multi-morphology simulations of the human brain. "Parallel computing", Maig 2019, vol. 84, p. 50-61.
dc.identifier.issn0167-8191
dc.identifier.otherhttps://arxiv.org/abs/2005.06332
dc.identifier.urihttp://hdl.handle.net/2117/173032
dc.description.abstractThe simulation of the behavior of the human brain is one of the most ambitious challenges today with a non-end of important applications. We can find many different initiatives in the USA, Europe and Japan which attempt to achieve such a challenging target. In this work, we focus on the most important European initiative (the Human Brain Project) and on one of the models developed in this project. This tool simulates the spikes triggered in a neural network by computing the voltage capacitance on the neurons’ morphology, being one of the most precise simulators today. In the present work, we have evaluated the use of MPI+OpenMP tasking on top of this framework. We prove that this approach is able to achieve a good scaling even when computing a relatively low workload (number of neurons) per node. One of our targets consists of achieving not only a highly scalable implementation, but also to develop a tool with a high degree of abstraction without losing control and performance by using MPI+OpenMP tasking. The main motivation of this work is the evaluation of this cutting-edge simulation on multi-morphology neural networks. The simulation of a high number of neurons, which are completely different among them, is an important challenge. In fact, in the multi-morphology simulations, we find an important unbalancing between the nodes, mainly due to the differences in the neurons, which causes an important under-utilization of the available resources. In this work, the authors present and evaluate mechanisms to deal with this and reduce the time of this kind of simulations considerably.
dc.description.sponsorshipWe would like to appreciate the valuable feedback and help provided by the main developers of the Arbor simulator: Benjamin Cumming (ETH Zürich) and Alexander Peyser (Jülich Supercomputing Center). This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 720270 (HBP SGA1 and SGA2), from the Spanish Ministry of Economy and Competitiveness under the project Computación de Altas Prestaciones VII (TIN2015-65316- P) and the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya, under project MPEXPAR: Models de Programació i Entorns d’Execució Paral · lels (2014-SGR-1051). Finally, this project also received funding from the Spanish Ministry of Economy and Competitiveness under the Juan de la Cierva Grant Agreement No IJCI-2017-33511, and from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska Curie grant agreement No. 749516.
dc.format.extent12 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica
dc.subject.lcshBrain -- Computer simulation
dc.subject.lcshNeural networks (Computer science)
dc.subject.otherMPI
dc.subject.otherOpenMP
dc.subject.otherTasking
dc.subject.otherSimulation
dc.subject.otherHuman brain
dc.subject.otherHuman Brain Project
dc.titleMPI+OpenMP tasking scalability for multi-morphology simulations of the human brain
dc.typeArticle
dc.subject.lemacCervell -- Simulació per ordinador
dc.subject.lemacXarxes neuronals (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1016/j.parco.2019.03.006
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S016781911830317X
dc.rights.accessOpen Access
local.identifier.drac24253240
dc.description.versionPostprint (author's final draft)
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1051
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/720270/EU/Human Brain Project Specific Grant Agreement 1/HBP SGA1
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/749516/EU/Advanced Ecosystem for Broad Heterogeneous Memory Usage/ECO-H-MEM
local.citation.authorValero-Lara, P.; Sirvent, R.; Peña, A.; Labarta, J.
local.citation.publicationNameParallel computing
local.citation.volume84
local.citation.startingPage50
local.citation.endingPage61


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