MPI+OpenMP tasking scalability for the simulation of the human brain

Pedro Valero-Lara, Raül Sirvent, Antonio J. Peña, Xavier Martorell, Jesús Labarta

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

The 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 (Human Brain Project) and on one of the tools (Arbor). This tool simulates the spikes triggered in a neuronal 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 the Arbor simulator. In this paper, we present the main characteristics of the Arbor tool and how these can be efficiently managed by using MPI+OpenMP tasking. We prove that this approach is able to achieve a good scaling even when computing a relatively low workload (number of neurons) per node using up to 32 nodes. Our target consists of achieving not only a highly scalable implementation based on MPI, but also to develop a tool with a high degree of abstraction without losing control and performance by using MPI+OpenMP tasking.

Original languageEnglish
Title of host publicationEuroMPI 2018 - Proceedings of the 25th European MPI Users' Group Meeting
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450364928
DOIs
StatePublished - Sep 23 2018
Externally publishedYes
Event25th European MPI Users' Group Meeting, EuroMPI 2018 - Barcelona, Spain
Duration: Sep 23 2018Sep 26 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference25th European MPI Users' Group Meeting, EuroMPI 2018
Country/TerritorySpain
CityBarcelona
Period09/23/1809/26/18

Funding

We would like to apreciate the valuable feedback and help provided by Benjamin Cumming and Alexander Peyser. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 720270 (HBP SGA1 and HBP SGA2), from the Spanish Ministry of Economy and Competitiveness under the project Computación de Altas Presta-ciones 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). This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska Curie grand agreement No. 749516. We would like to apreciate the valuable feedback and help provided by Benjamin Cumming and Alexander Peyser. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 720270 (HBP SGA1 and HBP SGA2), from the Spanish Ministry of Economy and Competitiveness under the project Computación de Altas Presta-ciones 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). This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska Curie grand agreement No. 749516.

FundersFunder number
Computación de Altas Presta-ciones VIITIN2015-65316-P
European Union’s Horizon 2020 Research and Innovation Program
Spanish Ministry of Economy and Competitiveness
Horizon 2020 Framework Programme785907, 720270, 749516
Generalitat de Catalunya
Ministerio de Economía y Competitividad

    Keywords

    • Arbor
    • Human Brain
    • MPI
    • OpenMP
    • Simulation
    • Tasking

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