CAREER: Career Development Plan: Behavioral Modeling, Simulation and Optimization for Mixed-Signal System on a Chip

University Of California-Riverside, Riverside CA

Investigators

Abstract

Abstract NSF Proposal#: 0448534 Dr. Xiang-Dong (Sheldon Tan) Tan University of California at Riverside This research seeks to develop an integrated research and education program on behavioral modeling, simulation, and optimization techniques to address and overcome the mixed-signal (MS) system-on-a-chip (SoC) design challenges and enable a leap to a new generation of mixed-signal VLSI systems. The focus is to develop efficient techniques for modeling, simulation and optimization of MS SoCs designs, which consist of both analog and digital blocks and operates in mixed frequency ranges (base-band frequency or radio frequency (RF)). The project specifically targets at (a) development of efficient parametric behavioral modeling and hierarchical piecewise linear (PWL) nonlinear modeling techniques based on a graph-based approach for linear and nonlinear analog circuits; (b) investigation of efficient algorithms for optimizing analog circuits and on-chip power-delivery systems for MS-SoC circuits based on modeling techniques. The new modeling techniques will explore a determinant-design diagram (DDD) based symbolic analysis method to construct behavioral models that consider device parameter ranges and design variations to cope with increasing manufacture uncertainty. For modeling nonlinear analog circuits, DDD-based hierarchical piece wise linear (PWL) modeling techniques will be investigated, which promises high fidelity behavioral modeling of very large nonlinear circuits at various abstract levels. As more physical effects become prominent, design practice, especially for the analog circuits, has become an optimization-like process because performance, reliability and manufacturability specifications have to be satisfied or optimized simultaneously. Such optimization-like design paradigms require new different design strategies and methodologies from that of digital circuits and will be explored in this research. The education component of the program consists of development of new curriculum in behavioral modeling, simulation and optimization of MS SoCs, and exploration of innovative learning approaches via web-enabled instructional tools and project-oriented learning for the education of future engineers with the knowledge of behavioral modeling, design and verification for mixed-signal SoCs. Engineers very versed in MS VLSI design and MS CAD development will be trained under this research project.