MASPINN: novel concepts for a neuroaccelerator for spiking neural networks

T. Schoenauer; N. Mehrtash; Andreas Jahnke; H. Klar

doi:10.1117/12.343072

22 March 1999 MASPINN: novel concepts for a neuroaccelerator for spiking neural networks

T. Schoenauer, N. Mehrtash, Andreas Jahnke, H. Klar

Proceedings Volume 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks; (1999) https://doi.org/10.1117/12.343072
Event: Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, 1998, Stockholm, Sweden

Abstract

We present the basic architecture of a Memory Optimized Accelerator for Spiking Neural Networks. The accelerator architecture exploits two novel concepts for an efficient computation of spiking neural networks: weight caching and a compressed memory organization. These concepts allow a further parallelization in processing and reduce bandwidth requirements on accelerator's components. Therefore, they pave the way to dedicated digital hardware for real-time computation of more complex networks of pulse-coded neurons in the order of 10⁶ neurons. The programmable neuron model which the accelerator is based on is described extensively. This shall encourage a discussion and suggestions on features which would be desirable to add to the current model.

Citation Download Citation

T. Schoenauer, N. Mehrtash, Andreas Jahnke, and H. Klar "MASPINN: novel concepts for a neuroaccelerator for spiking neural networks", Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); https://doi.org/10.1117/12.343072

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