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Physically justifiable die-level modeling of spatial variation in view of systematic across wafer variability
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 46th Annual Design Automation Conference table of contents
San Francisco, California
SESSION: Statistical methods in static timing analysis table of contents
Pages 104-109  
Year of Publication: 2009
ISBN:978-1-60558-497-3
Authors
Lerong Cheng  University of California, Los Angeles
Puneet Gupta  University of California, Los Angeles
Costas Spanos  University of California, Berkeley
Kun Qian  University of California, Berkeley
Lei He  University of California, Los Angeles
Sponsors
EDAC : Electronic Design Automation Consortium
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CAS : Circuits & Systems
Publisher
ACM  New York, NY, USA
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ABSTRACT

Modeling spatial variation is important for statistical analysis. Most existing works model spatial variation as spatially correlated random variables. We discuss process origins of spatial variability, all of which indicate that spatial variation comes from deterministic across-wafer variation, and purely random spatial variation is not significant. We analytically study the impact of across-wafer variation and show how it gives an appearance of correlation. We have developed a new dielevel variation model considering deterministic across-wafer variation and derived the range of conditions under which ignoring spatial variation altogether may be acceptable. Experimental results show that our model is within 1% error from exact simulation result while the error of the existing distance-based spatial variation model is up to 8%. Moreover, our new model is also 10X faster than the spatial variation model for Monte-Carlo analysis.


REFERENCES

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