Neural systems are composed of a large number of highly-connected neurons and are widely simulated within the neurological community. In this paper, we examine the application of parallel discrete event simulation techniques to networks of a complex model called the Hodgkin-Huxley neuron[1]. We describe the conversion of this model into an event-driven simulation, a technique that offers the potential of much greater performance in parallel and distributed simulations compared to timestepped techniques. We report results of an initial set of experiments conducted to determine the feasibility of this parallel event-driven Hodgkin-Huxley model and analyze its viability for large-scale neural simulations.
Collin J. Lobb, Zenas Chao, Richard M. Fujimoto, S