Simulation of Spiking Neural Networks on Different Hardware Platforms

: Substantial evidence indicates that the time structure of neuronal spike trains is relevant in neuronal signal processing. Bio-inspired spiking neural networks are taking these results into account. Applications of these networks to low vision problems, e.g. segmentation, requires that the simulation of large-scale networks must be performed in a reasonable time. On this basis, we investigated the achievable performance of existing hardware platforms for the simulation of spiking neural networks with sizes from 8k neurons up to 512k neurons/50M synapses. We present results for workstations (Sparc-Ultra), digital signal processors (TMS-C8x), neurocomputers (CNAPS, SYNAPSE), small- and large-scale parallel-computers (4xPentium, CM-2, SP2) and discuss the specific implementation issues. According to our investigation, only supercomputers like CM-2 can match the performance requirements for the simulation of very large-scale spiking neural networks. Therefore, there is still the need for...

• Type: Conference
• Year: 1997
• Where: ICANN
• Authors: Axel Jahnke, Tim Schönauer, Ulrich Roth, K. Mohraz, Heinrich Klar
• Keywords: Bio-inspired Spiking, ICANN 1997, Neural Networks, Neuronal Signal Processing, Spiking Neural Networks