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Chapter 5 A PROBABILISTIC-BASED DESIGN FOR NANOSCALE COMPUTATION

By R. Iris Bahar, Jie Chen and Joseph Mundy

Abstract

Abstract As current silicon-based techniques fast approach their practical limits, the investigation of nanoscale electronics, devices and system architectures becomes a central research priority. It is expected that nanoarchitectures will confront devices and interconnections with high inherent defect rates, which motivates the search for new architectural paradigms. In this chapter, we exam probabilistic-based design methodologies for designing nanoscale computer architectures based on Markov Random Fields (MRF) The MRF can express arbitrary logic circuits and logic operation is achieved by maximizing the probability of state configurations in the logic network. Maximizing state probability is equivalent to minimizing a form of energy that depends on neighboring nodes in the network. Once we develop a library of elementary logic components, we can link them together to build desired architectures. Overall, the probabilistic-based design can dynamically adapt to structural and signal-based faults. During the past decades, we have witnessed the boom of microelectronics

Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.8721
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