Toward Energy-Efficient, Bio-Inspired Circuits and Systems for Error-Resilient and Biomedical Applications

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Many of us get our computers, laptops or phones replaced every few years. Technology advances due to the continuous miniaturization of electronic devices, such that a larger number of devices can be packed into a single chip, while the cost has been kept relatively stable. This trend has slowed down, however, and is predicted to end in less than a decade. A transistor, the basic functional unit in a circuit, is now sized in just a few nanometers, that is, a few billionth of a meter. At such a small scale, it is difficult to fabricate all transistors uniformly and make them operate reliably. The current method to ensure a reliable operation is to apply a larger power than it is often necessary, so electronics still consume a lot of energy. On the other hand, many computer applications, such as multimedia, voice recognition and web search, do not always require a fully accurate result and a "good-enough" result is often sufficient due to many factors such as human perceptual limitations. This class of applications is considered imprecision-tolerant or error-resilient. One objective of this research program is to address the energy-efficiency and error-resilience issues in nanometer-scale electronics by developing new and innovative computational structures that employ approximate, stochastic and the brain-inspired neuromorphic computing techniques. These new techniques allow computing systems to trade off quality for energy. ******As a transistor is to a computer, a cell is the basic unit of life in a biological system such as a human body. The advances of computing techniques also provide opportunities to help address some emerging biomedical issues. For example, computational models have been used to help understand how a gene network functions in a cell. Validated computational results provide additional knowledge to our understanding of biological systems. The other objective of this research program is to apply computing techniques to the modeling and analysis of biological networks by exploiting the similarity between an electronic circuit and a biological network. Such a network can be a genetic network or a signaling pathway in a cancerous cell. The obtained results will help to investigate gene intervention-based therapeutic methods for some genetic diseases such as cancer. ******This research program addresses some of the fundamental and challenging issues faced by the information technology industry and the biomedical research community. It will take a truly interdisciplinary approach to leveraging the interactions between computer engineering, computational biology and biomedical engineering. This program will also facilitate the training of highly qualified personnel (HQP) with skills highly demanded by the high-tech sectors in Canadian industry. Such skills will be crucial to the long-term growth of the economy, and thus will be of significant economic importance to Canada.**