| Efficient design-specific worst-case corner extraction for integrated circuits |
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Annual ACM IEEE Design Automation Conference
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Proceedings of the 46th Annual Design Automation Conference
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San Francisco, California
SESSION: Analog/RF simulation and statistical modeling
table of contents
Pages 386-389
Year of Publication: 2009
ISBN:978-1-60558-497-3
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ABSTRACT
While statistical analysis has been considered as an important tool for nanoscale integrated circuit design, many IC designers would like to know the design-specific worst-case corners for circuit debugging and failure diagnosis. In this paper, we propose a novel algorithm to efficiently extract the worst-case corners for nanoscale ICs. Our proposed approach mathematically formulates a quadratically constrained quadratic programming (QCQP) problem for corner extraction. Next, it applies the Lagrange duality theory to convert the non-convex QCQP problem to a convex semi-definite programming (SDP) problem that is easier to solve. Our circuit example designed in a commercial CMOS process demonstrates that the proposed SDP formulation can find the worst-case corners both efficiently and robustly, while the traditional QCQP fails to achieve global convergence.
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