title: Efficiently passing messages in distributed spiking neural network simulation.
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.
authors.affiliation: Center for Neural and Emergent Systems, Information and System Sciences Laboratory, HRL Laboratories LLC. Malibu, CA, USA ; Department of Electrical and Biomedical Engineering, The University of Nevada Reno, NV, USA ; Department of Computer Science and Engineering, The University of Nevada Reno, NV, USA.
authors.forename: Corey M
authors.initials: CM
authors.lastname: Thibeault
authors.forename: Kirill
authors.initials: K
authors.lastname: Minkovich
authors.forename: Michael J
authors.initials: MJ
authors.lastname: O'Brien
authors.forename: Frederick C
authors.initials: FC
authors.lastname: Harris
authors.forename: Narayan
authors.initials: N
authors.lastname: Srinivasa
keywords: distributed computing; distributed message passing; neural networks; parallel simulation; parallel spiking neuron simulation