Efficiently Passing Messages in Distributed Spiking Neural Network Simulation
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Authors
Thibeault, Corey M.
Minkovich, Kirill
O'Brien, Michael J.
Harris, Frederick C. Jr.
Srinivasa, Narayan
Issue Date
2013
Type
Article
Language
Keywords
Distributed Computing , distributed message passing , neural networks , parallel simulation , parallel spiking neuron simulation
Alternative Title
Abstract
Efficiently passing spiking messages in a neural model is an important aspect of high-performance simulation. As the scale of networks has increased so has the size of the computing systems required to simulate them. In addition, the information exchange of these resources has become more of an impediment to performance. In this paper we explore spike message passing using different mechanisms provided by the Message Passing Interface (MPI). A specific implementation, MVAPICH, designed for high-performance clusters with Infiniband hardware is employed. The focus is on providing information about these mechanisms for users of commodity high-performance spiking simulators. In addition, a novel hybrid-method for spike exchange was implemented and benchmarked.
Description
Citation
Publisher
License
Creative Commons Attribution 4.0 United States
Journal
Volume
Issue
PubMed ID
ISSN
1662-5188