Generating Routing-Driven Power Distribution Networks with Machine-Learning Technique

Li-De Chen
Li-De Chen
Chien-Hsueh Lin
Chien-Hsueh Lin
Yen-Chih Chiu
Yen-Chih Chiu

IEEE Trans. on CAD of Integrated Circuits and Systems, Volume 36, Issue 8, 2017, Pages 1237-1250.

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Abstract:

As technology node keeps scaling and design complexity keeps increasing, power distribution networks (PDNs) require more routing resource to meet IR-drop and electro-migration (EM) constraints. This paper presents a design flow to generate a PDN that can result in near-minimal overhead for the routing of the underlying standard cells whil...More

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