MSc CE Thesis Presentation

Digital Neuron Cells for Highly Parallel Cognitive Systems

Haipeng Lin

The biophysically-meaningful neuron models can be used to simulate human brain behavior. The understanding of neuron behaviours is expected to have prominent role in the fields such as artificial intelligence, treatments of damaged brain, etc. Several neuron models exist, which vary in a level of accuracy complexity, speed, etc. In this thesis, a general simulator is presented, which can implement Hodgkin-Huxley(HH) model, Integrate and Fire model and Izhikevich model in the same architecture in a real-time. The different neuron models can be selected in the simulator to evaluate various network configurations, such as the amount of the neuron cells in the network, properties of the neuron models and so on. The simulator communication cost grows approximately linearly with the number of the neuron cells. Similarly, implementation over multiple Field Programmable Gate Array(FPGA) devices is possible. At last, this simulator is synthesised and validated on a FPGA device. The pipeline is added to reduce resource cost and latency.

Overview of MSc CE Thesis Presentation