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David Z. Pan

Researcher at University of Texas at Austin

Publications -  557
Citations -  12677

David Z. Pan is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Computer science & Routing (electronic design automation). The author has an hindex of 50, co-authored 496 publications receiving 10182 citations. Previous affiliations of David Z. Pan include University of California, Los Angeles & Fudan University.

Papers
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Proceedings ArticleDOI

AppSAT: Approximately deobfuscating integrated circuits

TL;DR: This paper shows how the AppSAT attack can deobfuscate 68 out of the 71 benchmark circuits that were obfuscated with state-of-the-art SAT attack defenses with an accuracy of, n being the number of inputs.
Proceedings ArticleDOI

Layout decomposition for triple patterning lithography

TL;DR: It is shown that TPL layout decomposition is a more difficult problem than that for DPL, and a novel vector programming formulation is proposed which can simultaneously minimize conflict and stitch numbers and solve it through effective semidefinite programming (SDP) approximation.
Proceedings ArticleDOI

Buffer block planning for interconnect-driven floorplanning

TL;DR: An effective buffer block planning (BBP) algorithm is developed to perform buffer clustering such that the overall chip area and the buffer block number can be minimized.
Proceedings ArticleDOI

Pushing ASIC performance in a power envelope

TL;DR: The trade-off between multiple supply voltages and multiple threshold voltages in the optimization of dynamic and static power is explored and optimization techniques such as clock skew scheduling are discussed which can be effectively used to push performance in a power neutral way.
Proceedings ArticleDOI

Redundant-via enhanced maze routing for yield improvement

TL;DR: This paper proposes the first routing algorithm that considers feasibility of redundant via insertion in the detailed routing stage, and transforms the routing problem to a multiple constraint shortest path problem, and solved by Lagrangian relaxation technique.