A scalable soft spot analysis methodology for compound noise effects in nano-meter circuits

  • Authors:
  • Chong Zhao;Xiaoliang Bai;Sujit Dey

  • Affiliations:
  • University of California, San Diego, La Jolla, CA;University of California, San Diego, La Jolla, CA;University of California, San Diego, La Jolla, CA

  • Venue:
  • Proceedings of the 41st annual Design Automation Conference
  • Year:
  • 2004

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Abstract

Circuits using nano-meter technologies are becoming increasingly vulnerable to signal interference from multiple noise sources as well as radiation-induced soft errors. One way to ensure reliable functioning of chips is to be able to analyze and identify the spots in the circuit which are susceptible to such effects (called "soft spots" in this paper), and to make sure such soft spots are "hardened" so as to resist multiple noise effects and soft errors. In this paper, we present a scalable soft spot analysis methodology to study the vulnerability of digital ICs exposed to nano-meter noise and transient soft errors. First, we define "softness" as an important characteristic to gauge system vulnerability. Then several key factors affecting softness are examined. Finally an efficient Automatic Soft Spot Analyzer (ASSA) is developed to obtain the softness distribution which reflects the unbalanced noise-tolerant capability of different regions in a design. The proposed methodology provides guidelines to reduction of severe nano-meter noise effects caused by aggressive design in the pre-manufacturing phase, and guidelines to selective insertion of on-line protection schemes to achieve higher robustness. The quality of the proposed soft-spot analysis technique is validated by HSPICE simulation, and its scalability is demonstrated on a commercial embedded processor.