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.