SRAM parametric failure analysis

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. Categories and Subject Descriptors B.8.2 [Performance and Reliability]: Performance Analysis and Design Aids General Terms: Algorithms, Reliability

• Type: Conference
• Year: 2009
• Where: DAC
• Authors: Jian Wang, Soner Yaldiz, Xin Li, Lawrence T. Pileggi
• Keywords: DAC 2009, Design Automation, Failure Probability Extraction, SRAM Failure Analysis, SRAM Parametric Failures