Yield estimation of SRAM circuits using “Virtual SRAM Fab”

Abstract

Static Random Access Memories (SRAMs) are key components of modern VLSI designs and a major bottleneck to technology scaling as they use the smallest size devices with high sensitivity to manufacturing details. Analysis performed at the “schematic” level can be deceiving as it ignores the interdependence between the implementation layout and the resulting electrical performance. We present a computational framework, referred to as “Virtual SRAM Fab”, for analyzing and estimating pre-Si SRAM array manufacturing yield considering both lithographic and electrical variations. The framework is being demonstrated for SRAM design/optimization in 45nm nodes and currently being used for both 32nm and 22nm technology nodes. The application and merit of the framework are illustrated using two different SRAM cells in a 45nm PD/SOI technology, which have been designed for similar stability/performance, but exhibit different parametric yields due to layout/lithographic variations. We also demonstrate the application of Virtual SRAM Fab for prediction of layout-induced imbalance in an 8T cell, which is a popular candidate for SRAM implementation in 32–22nm technology nodes.