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Title:Overcoming nanoscale variations through statistical error compensation
Author(s):Gao, Tianqi
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):variation-tolerant techniques
power-efficient design
emerging technologies
error compensation
Abstract:Increasingly severe parameter variations that are observed in advanced nanoscale technologies create great obstacles in designing high-performance, next-generation digital integrated circuits (ICs). Conventional design principles impose increased design margins in power supply, device sizing, and operating frequency, leading to overly conservative designs which prevent the realization of potential benefits from nanotechnology advances. In response, robust digital circuit design techniques have been developed to overcome processing non-idealities. Statistical error compensation (SEC) is a class of system-level, communication-inspired techniques for designing energy efficient and robust systems. In this thesis, stochastic sensor network on chip (SSNOC), a known SEC technique, is applied to a computational kernel implemented with carbon nanotube field-effect transistors (CNFETs). With the aid of a well developed CNFET delay distribution modeling method, circuit simulations show up to 90× improvement of the SSNOC-based design in the circuit yield over the conventional design. The results verify the robustness of an SEC-based design under CNFET-specific variations. The error resiliency of SEC allows CNFET circuits to operate with reduced design margins under relaxed processing requirements, while concurrently maintaining the desired application-level performance.
Issue Date:2015-04-07
Rights Information:Copyright 2015 Tianqi Gao
Date Available in IDEALS:2015-07-22
Date Deposited:May 2015

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