MPI+OpenMP tasking scalability for multi-morphology simulations of the human brain

Pedro Valero-Lara; Raül Sirvent; Antonio J. Peña; Jesús Labarta

doi:10.1016/j.parco.2019.03.006

MPI+OpenMP tasking scalability for multi-morphology simulations of the human brain

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

Research output: Contribution to journal › Article › peer-review

11 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 (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.

Original language	English
Pages (from-to)	50-61
Number of pages	12
Journal	Parallel Computing
Volume	84
DOIs	https://doi.org/10.1016/j.parco.2019.03.006
State	Published - May 2019
Externally published	Yes

Funding

We 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 . We 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.

Funders	Funder number
Computación de Altas Prestaciones VII
European Union’s Horizon 2020 Research and Innovation Program
Spanish Ministry of Economy and Competitiveness
Horizon 2020 Framework Programme	720270, 749516
Generalitat de Catalunya	IJCI-2017-33511, 2014-SGR-1051
Departament d'Innovació, Universitats i Empresa, Generalitat de Catalunya
Ministerio de Economía y Competitividad	TIN2015-65316-P

Keywords

Human brain
Human brain project
MPI
OpenMP
Simulation
Tasking

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10.1016/j.parco.2019.03.006

Cite this

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title = "MPI+OpenMP tasking scalability for multi-morphology simulations of the human brain",

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 (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{\textquoteright} 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.",

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MPI+OpenMP tasking scalability for multi-morphology simulations of the human brain

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Keywords

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