HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters

Author

Minkovich, Kirill ; Thibeault, Corey M. ; O´Brien, Michael J. ; Nogin, Aleksey ; Youngkwan Cho ; Srinivasa, Narayan

Author_Institution

Inf. & Syst. Sci. Dept., HRL Labs. LLC, Malibu, CA, USA

Volume

25

Issue

2

fYear

2014

fDate

Feb. 2014

Firstpage

316

Lastpage

331

Abstract

Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called HRL Spiking Simulator (HRLSim). This simulator is suitable for implementation on a cluster of general purpose graphical processing units (GPGPUs). Novel aspects of HRLSim are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive GPGPU cards and compute power, HRLSim offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.

Keywords

graphics processing units; neural nets; GPGPU cards; GPGPU clusters; HRL spiking simulator; HRLSim; brain function; general purpose graphical processing units; high performance spiking neural network simulator; large scale spiking neural models; real time simulation; Analytical models; Biological system modeling; Computational modeling; Delays; Graphics processing units; Mathematical model; Neurons; Distributed graphical processing units (GPUs) programming; general purpose GPU (GPGPU); large scale; neuron simulation; spike timing-dependent plasticity (STDP); spiking neural simulation;

fLanguage

English

Journal_Title

Neural Networks and Learning Systems, IEEE Transactions on

Publisher

ieee

ISSN

2162-237X

Type

jour

DOI

10.1109/TNNLS.2013.2276056

Filename

6579754