A comprehensive model of process variability for statistical timing optimization

Kun Qian; Costas J. Spanos

doi:10.1117/12.772980

4 March 2008 A comprehensive model of process variability for statistical timing optimization

Kun Qian, Costas J. Spanos

Proceedings Volume 6925, Design for Manufacturability through Design-Process Integration II; 69251G (2008) https://doi.org/10.1117/12.772980
Event: SPIE Advanced Lithography, 2008, San Jose, California, United States

Abstract

As technologies scale, the impact of process variations to circuit performance and power consumption is increasingly significant. In order to improve the efficiency of statistical circuit optimization, a better understanding of the relationship between circuit variability and process variation is needed. Our work proposes a hierarchical variability model, which addresses both systematic and random variations at wafer, field, die, and device level, and spatial correlation artifacts are captured implicitly. Finally, layout dependent effects are incorporated as an additive component. The model is verified by applying to 90nm ring oscillator measurement data and can be used for variability prediction and optimization.

Citation Download Citation

Kun Qian and Costas J. Spanos "A comprehensive model of process variability for statistical timing optimization", Proc. SPIE 6925, Design for Manufacturability through Design-Process Integration II, 69251G (4 March 2008); https://doi.org/10.1117/12.772980

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