| When: | Wednesday March 12, 2008. 9:00am – 10:00am |
| Where: | Design Automation and Test in Europe Conference (DATE) ICM, Munich, Germany Room 2156 |
| Who: | Designers, Design Managers, CAD Managers |
| Cost: | Free |
Breakfast will be served. Registration.
As process technologies and supply voltages shrink, designers are faced with a pressing need to address systematic and random sources of variation in a more deliberate and thorough way. Accounting for variation within the flow of design has not progressed commensurate with the process technologies. We still rely on best-, worst- case corners, mismatch plots and maybe a Monte Carlo verification if there is enough time. It is time for a new approach.
This talk will begin with a brief review of the physical phenomena and industry standard device models for variation sources, including random local and global variations and systematic proximity effects. New techniques to accelerate, increase accuracy and derive more information from statistical variation analysis will be presented.
Patrick Drennan is Chief Technology Officer of Solido Design Automation, Inc. Prior to joining Solido, Patrick was a Distinguished Member of the Technical Staff at Freescale Semiconductor (formerly Motorola, Inc.).
Patrick was one of the creators of the backwards propagation of variance (BPV) method for statistical characterization. This model guarantees consistency between simulation and silicon measurement and it is valid for all biases and geometries, which are significant attributes for design. His mismatch (local variation) model earned the Best Regular paper at the 2002 IEEE Custom Integrated Circuit Conference. He was the first to describe the impact of shallow trench isolation (STI) and well proximity effect (WPE) on design, demonstrating that the WPE produces a graded channel MOSFET. More importantly, he showed the catastrophic impact these unforeseen phenomena can have on circuit design. For this work, he received the Best Invited Paper at the 2006 IEEE Custom Integrated Circuit Conference. Patrick has extensive experience in measurement, modeling, characterization, test structure generation and design application of systematic and stochastic semiconductor variations.
Patrick received the B.S. degree in microelectronic engineering and M.S. degree in electrical engineering from Rochester Institute of Technology and the Ph.D. degree in electrical engineering from Arizona State University.