Enabling Large-Scale Simulations With the GENESIS Neuronal Simulator

Frontiers in Neuroinformatics

卷:13

Manuel M. Vindiola¹  Joshua C. Crone¹  David Beeman²  Piotr J. Franaszczuk³  David L. Boothe⁴  Alfred B. Yu⁴  Kelvin S. Oie⁴ 

[1] Computational and Information Sciences Directorate, Army Research Laboratory, Aberdeen Proving Ground, MD, United States;

[2] Department of Electrical, Computer, and Energy Engineering, University of Colorado, Boulder, CO, United States;

[3] Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States;

[4] Human Research and Engineering Directorate, Army Research Laboratory, Aberdeen Proving Ground, MD, United States;

关键词: large-scale simulation;    spiking neuronal network;    computational neuroscience;    multi-compartment neuron model;    high performance computing;    multiscale modeling;   

DOI  :  10.3389/fninf.2019.00069

来源: DOAJ

【 摘 要 】

In this paper, we evaluate the computational performance of the GEneral NEural SImulation System (GENESIS) for large scale simulations of neural networks. While many benchmark studies have been performed for large scale simulations with leaky integrate-and-fire neurons or neuronal models with only a few compartments, this work focuses on higher fidelity neuronal models represented by 50–74 compartments per neuron. After making some modifications to the source code for GENESIS and its parallel implementation, PGENESIS, particularly to improve memory usage, we find that PGENESIS is able to efficiently scale on supercomputing resources to network sizes as large as 9 × 106 neurons with 18 × 109 synapses and 2.2 × 106 neurons with 45 × 109 synapses. The modifications to GENESIS that enabled these large scale simulations have been incorporated into the May 2019 Official Release of PGENESIS 2.4 available for download from the GENESIS web site (genesis-sim.org).

【 授权许可】

Unknown