Special-purpose hardware architecture for neuromorphic computing

In this paper, we describe a special-purpose hardware architecture for neural network simulation systems called neuron machine that can be used effectively for neuromorphic simulations. A neuron machine system consists of a single digital hardware neuron, which is designed as a large-scale fine-grained pipelined circuit, and a memory unit called network unit. By using extensive pipelining and a large number of memories, neuron machine system exploits a large amount of the parallelism inherent in neural networks while retaining the flexibilities of network topology. As an example of the proposed architecture, a simulation system for the networks of biologically realistic Hodgkin-Huxley neurons capable of complex synaptic features such as spike-timing dependent plasticity and dynamic synapse, is implemented on a field-programmable gate array (FPGA). Our system implemented on a single mid-range FPGA chip computed at a speedup of 1200x over a CPU-based system.