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HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters | IEEE Journals & Magazine | IEEE Xplore

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


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 d...Show More

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.
Published in: IEEE Transactions on Neural Networks and Learning Systems ( Volume: 25, Issue: 2, February 2014)
Page(s): 316 - 331
Date of Publication: 15 August 2013

ISSN Information:

PubMed ID: 24807031

References

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