CE Seminar: Janet Meiling Wang, "Chebyshev Affine Arithmetic Based Parametric Yield Prediction Under Limited Descriptions of Uncertainty" 22 April, 2:00-3:00 in ECE 530
Coordinates:
| Date: | 22 April, 2:00-3:00 |
| Title: | Chebyshev Affine Arithmetic Based Parametric Yield Prediction Under Limited Descriptions of Uncertainty |
| Speaker: | Janet Meiling Wang |
| Location: | ECE530 |
Abstract:
Due to the hard-to-measure distributions of the real process data, it is difficult to provide accurate parametric yield prediction for modern circuit design. Most existing approaches are not able to handle the uncertain distribution properties coming from the process data. Other approaches are inadequate considering correlations among the distributions of variations. This paper suggests a new approach that not only takes care of correlations among distributions but also provides a low cost and efficient computation scheme. The proposed method approximates the parameter variations with Chebyshev Affine Arithmetic (CAA) to capture both the uncertainty and nonlinearity in Cumulative Distribution Function (CDF). The CAA based probabilistic range presentation describes both fully and partially specified process and environmental parameters. Thus we are able to predict probability bounds for leakage consumption with unknown dependency among variations. The end result is the chip level parametric yield estimation based on leakage prediction. Experimental results demonstrate that the new approach provides reliable bound estimation while leads to 20% yield improvement compared with only using the intervals of partially-specified uncertainty.
Biography:
Janet Meiling Wang received the B.S. degree from Nanjing University of Science and Technology (former East China Institute of Technology ), Nanjing, Jiang Su, China, in 1991, the M.E. degree from the Chinese Academy of Sciences, Beijing, China, in 1994, and the Master's and Ph.D degrees in electrical engineering and computer sciences, from the University of California at Berkeley, in 1997 and 2000, respectively. She was with Intel, Santa Clara, CA, and Cadence Santa Clara, CA from 2000 to 2002. Since 2003, she has been a faculty member in the Electrical Computing Engineering Department at University of Arizona, Tucson. Dr. Wang is a member of IEEE Circuits and Systems Society and was the recipient of the 2005 National Science Foundation Career Award, and 2006 Presidential Earlier Career Award for Scientist and Engineers(PECASE).