SRAM parametric failure analysis

• Published in: 2009 46th ACM/IEEE Design Automation Conference pp. 496 - 501
• Main Authors: Wang, Jian, Yaldiz, Soner, Li, Xin, Pileggi, Lawrence T.
• Format: Conference Proceeding
• Language: English
• Published: New York, NY, USA ACM 26-07-2009; IEEE
• Series: ACM Conferences
• Subjects: Acceleration; Circuit stability; Costs; Failure analysis; Failure Probability Estimation; Hardware > Hardware validation; Measurement; Parametric Failure; Probability; Probes; Random access memory; Response surface methodology; Response Surface Model; Sampling methods; SRAM; failure probability estimation; SRAM; parametric failure; response surface model
• ISBN: 9781605584973; 1605584975
• ISSN: 0738-100X
• DOI: 10.1145/1629911.1630041

With aggressive technology scaling, SRAM design has been seriously challenged by the difficulties in analyzing rare failure events. In this paper we propose to create statistical performance models with accuracy sufficient to facilitate probability extraction for SRAM parametric failures. A piecewise modeling technique is first proposed to capture the performance metrics over the large variation space. A controlled sampling scheme and a nested Monte Carlo analysis method are then applied for the failure probability extraction at cell-level and array-level respectively. Our 65nm SRAM example demonstrates that by combining the piecewise model and the fast probability extraction methods, we have significantly accelerated the SRAM failure analysis.