Efficient Simulation of Biological Neural Networks on Massively Parallel Supercomputers with Hypercube Architecture

Part of Advances in Neural Information Processing Systems 6 (NIPS 1993)

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Ernst Niebur, Dean Brettle


We present a neural network simulation which we implemented on the massively parallel Connection Machine 2. In contrast to previous work, this simulator is based on biologically realistic neu(cid:173) rons with nontrivial single-cell dynamics, high connectivity with a structure modelled in agreement with biological data, and preser(cid:173) vation of the temporal dynamics of spike interactions. We simulate neural networks of 16,384 neurons coupled by about 1000 synapses per neuron, and estimate the performance for much larger systems. Communication between neurons is identified as the computation(cid:173) ally most demanding task and we present a novel method to over(cid:173) come this bottleneck. The simulator has already been used to study the primary visual system of the cat.