Accelerating Neural Computation

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Computing systems that have found the inspiration of their function in Biology or model the functioning of actual biological systems have been introduced for many years and have seen their development accelerating recently as advances in technology have allowed the deployment of high performance computing systems. In this research program, we will focus on developing methods of accelerating the computations needed in neural networks. Neural networks can be viewed as (i) Artificial Neural Networks that have found applications in classification, modeling and learning, and (ii) spiking neuromorphic systems that closer resemble the structure and functioning of the central nervous system. Our long term objective is to devise a system that can accurately emulate a part of the brain in real or near-real time. Such a system can be used in biological research to test hypotheses especially as related to diseases, and to better understand the influence of the structure on function. Such a goal is novel, as most of the current neuromorphic systems research is focusing on developing complex systems that scale, often using simplified neural models and interconnects that do not accurately represent biology. Our approach is computationally challenging, but its complexity is tractable. An additional goal is the development of systems enhancing the performance of generalizing ANN. It is expected that the successful completion of this research will lead to advanced study, and contribute to the understanding of complex neural systems. In the field of artificial neural networks, having an efficient computational environment will allow the modeling complex systems and classifiers and it will contribute to big data analytics. In the field of neuromorphic systems, having the ability to accurately simulate brain structures in real or near-real time, will allow researchers to experiment and understand the functioning of these brain structures. Such systems have the potential of becoming virtual laboratories to experiment on such brain structures, prod their functionality, explore how learning occurs and understand how some degenerating diseases manifest themselves.