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PV-Clock: Process Variation-Aware 3D Clock Network Synthesis for Robust and Power-Efficient Timing Optimization

  • Beihang University
  • Aristotle University of Thessaloniki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Three-dimensional integration technology enables higher density and heterogeneous integration, extending Moore's Law. However, increasing integration density complicates clock network design. Existing synthesis methods often neglect process variations, which are inherent in fabrication and degrade clock signal precision. Additionally, optimizing one design metric, such as reducing clock skew, often increases power consumption, limiting overall efficiency. These trade-offs restrict the design space and hinder 3D IC performance. To address these challenges, this paper proposes a novel process variation-aware clock network synthesis technique incorporating a multi-objective collaborative optimization framework. The proposed method effectively balances clock skew and power consumption while enhancing robustness. Experimental results demonstrate significant improvements: clock skew is reduced from 21.54 p s to 15.02 p s, while clock power decreases by 23.8%, highlighting the method's effectiveness in mitigating process variations and optimizing 3D clock networks.

Original languageEnglish
Title of host publicationIEEE Computer Society Annual Symposium on VLSI, ISVLSI 2025 - Conference Proceedings
PublisherIEEE Computer Society
ISBN (Electronic)9798331534776
DOIs
StatePublished - 2025
Event28th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2025 - Kalamata, Greece
Duration: 6 Jul 20259 Jul 2025

Publication series

NameProceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI
ISSN (Print)2159-3469
ISSN (Electronic)2159-3477

Conference

Conference28th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2025
Country/TerritoryGreece
CityKalamata
Period6/07/259/07/25

Keywords

  • 3D ICs
  • Clock Network Synthesis
  • Geometric Optimization
  • Process Variations

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