SRAM dynamic stability estimation using MPFP and its applications

Diaa Eldin Khalil, Muhammad Khellah, Nam Sung Kim, Yehea Ismail, Tanay Karnik, Vivek De

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, an accurate approach for estimating the dynamic stability of static random access memory (SRAM) is proposed. The conventional methods of SRAM stability estimation suffer from two major drawbacks: (1) using static failure criteria, such as SNM, which does not capture the transient and dynamic behavior of SRAM operation, and (2) using quasi-Monte-Carlo simulation, which approximates the failure distribution, resulting in large errors at the tails where the desired failure probabilities exist. These drawbacks are eliminated by employing accurate simulation-based dynamic failure criteria along with a new distribution-independent, Most-probable-failure-point search technique for accurate probability calculation. Compared to previously published techniques, the proposed dynamic stability technique offers orders of magnitude improvement in accuracy. Furthermore, the proposed dynamic stability technique enables the correct evaluation of stability in real operation conditions and for different dynamic circuit techniques, such as dynamic write back, where the conventional methods are not applicable.

Original languageEnglish (US)
Pages (from-to)1523-1530
Number of pages8
JournalMicroelectronics Journal
Volume40
Issue number11
DOIs
StatePublished - Nov 2009
Externally publishedYes

Keywords

  • DVFS
  • Dynamic stability
  • Process variations
  • Read assist
  • SRAM yield
  • Supply noise effects

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Condensed Matter Physics
  • Surfaces, Coatings and Films
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'SRAM dynamic stability estimation using MPFP and its applications'. Together they form a unique fingerprint.

Cite this