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Oil fields, hedge funds, and drugs
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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
PANEL SESSION: Panel table of contents
Pages: 416-417  
Year of Publication: 2009
ISBN:978-1-60558-497-3
Authors
Patrick Groeneveld  Magma Design Automation, Inc.
Rob A. Rutenbar  Carnegie Mellon University, Pittsburgh, PA
Jed Pitera  IBM Almaden Research Lab, San Jose, CA
Erik Carlson  Armored Wolf, Aliso Viejo, CA
Jinsong Chen  Lawrence Berkeley Labs, Berkeley, CA
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

Statistical analysis is a fundamental method in analysis, design, and optimization of large systems with uncertainties. It is being applied in drug development, analyzing financial markets, search for new oil fields, and many more areas. As the silicon process technology scales to its limits, uncertainty plays an increasing role and has made its way into tools such as yield analysis, statistical time analysis, etc. In this educational panel, we will start with a short tutorial on Monte Carlo methods including their use in EDA. Three experts from distinct application fields will then follow and discuss their experience in using Monte Carlo methods for solving large-scale problems in their domain. It may come as a surprise to some attendees of DAC to learn how much commonality there is between methods used in EDA and other field that seem far-fetched.


Collaborative Colleagues:
Patrick Groeneveld: colleagues
Rob A. Rutenbar: colleagues
Jed Pitera: colleagues
Erik Carlson: colleagues
Jinsong Chen: colleagues