Communication sparsity in distributed spiking neural network simulations to improve scalability

Fernandez-Musoles, C., Coca, D. orcid.org/0000-0003-2878-2422 and Richmond, P. (2019) Communication sparsity in distributed spiking neural network simulations to improve scalability. Frontiers in Neuroinformatics, 13. 19. ISSN 1662-5196

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 Fernandez-Musoles, Coca and Richmond. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: Spiking Neural Networks; distributed simulation; hypergraph partitioning; dynamic sparse data exchange; HPC
Dates:
  • Accepted: 11 March 2019
  • Published (online): 2 April 2019
  • Published: 2 April 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 26 Apr 2019 14:48
Last Modified: 26 Apr 2019 14:48
Status: Published
Publisher: Frontiers Media
Refereed: Yes
Identification Number: https://doi.org/10.3389/fninf.2019.00019
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