EMT/MISC: Theory and methods for design and synthesis of approximate logic circuits and systems: a paradigm for emerging technologies

University Of Southern California, Los Angeles CA

Investigators

Abstract

Abstract This research develops a completely new approach for automatically synthesizing and manually designing digital circuits that implement approximate-yet-acceptable versions of logic functions. This approach provides lower cost and higher speed versions of many widely used digital systems. The benefits of this research will grow with the adoption of each new nanotechnology. All future nanoscale CMOS and emerging non-CMOS nanotechnologies will suffer from increasing levels of non-idealities ? especially high process variations, defect densities, and noise sensitivity. These non-idealities present a fundamental challenge, since, if left unchecked, they will erode most benefits provided by adoption of these nanotechnologies. This research involves development of approximate design and synthesis, a completely new paradigm for dealing with this fundamental challenge. This paradigm builds upon the recent demonstration that there is considerable flexibility in the behavioral specifications for wide classes of digital systems. Such flexibilities in specifications are captured in the form of acceptable deviations from the nominal behavioral specifications and the first logic synthesis and design approaches and tools are developed to exploit these deviations to reduce cost or enhance performance and yield. In contrast to all existing research directions, this paradigm mitigates the effects of non-idealities by simplifying the designed circuit. This approach is applicable to application-specific chips for many embedded systems and many types of widely used processors, e.g., arithmetic co-processors, processors for digital signal processing, and graphics processors. Collectively, the set of chips that benefit from this approach constitute a significant proportion of all chips sold in any given year. This research opens a completely new avenue for dramatically improving cost, performance, and yield for future nanotechnologies. 1