On a Moreau Envelope Wirelength Model for Analytical Global Placement

Peiyu Liao, Hongduo Liu, Yibo Lin*, Bei Yu*, Martin Wong

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

3 Citations (Scopus)


Analytical placement is proven to be effective in global placement. The differentiability of wirelength models is very critical to gradient-based numerical optimization. Most previous works approximate the non-smooth half-perimeter wirelength (HPWL) model with various differentiable functions. In this paper, we propose a new differentiable wirelength model using the Moreau envelope to approximate HPWL. By combining the state-of-the-art electrostatic-based placement algorithm, the experimental results demonstrate that our proposed algorithm can achieve up to 5.4% HPWL improvement and more than 1% on average compared to the most widely-used nonlinear wirelength model.
Original languageEnglish
Title of host publication60th ACM/IEEE Design Automation Conference - Proceedings 2023
Number of pages6
ISBN (Electronic)9798350323481
ISBN (Print)9798350323498
Publication statusPublished - 13 Jul 2023
Event60th ACM/IEEE Design Automation Conference, DAC 2023 - Moscone West, San Francisco, United States
Duration: 9 Jul 202313 Jul 2023

Publication series

NameACM/IEEE Design Automation Conference - Proceedings
ISSN (Print)0738-100X


Conference60th ACM/IEEE Design Automation Conference, DAC 2023
Country/TerritoryUnited States
CitySan Francisco
Internet address

Scopus Subject Areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications
  • Modelling and Simulation

User-Defined Keywords

  • Analytical models
  • Approximation algorithms
  • Approximation error
  • Benchmark testing
  • Design automation
  • Graphics processing units
  • Runtime


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