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Updated: May 10, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Efficiently passing messages in distributed spiking neural network simulation
Corey M Thibeault1, Kirill Minkovich, Michael J O'Brien
1Center 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.
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.
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