Communication Dans Un Congrès Année : 2024

A survey of Reinforcement Learning for Electronic Design Automation

Huming Zhu
  • Fonction : Auteur
  • PersonId : 1405904
Xiangru Chen
  • Fonction : Auteur

Résumé

With the technological evolution of fabrication processes, the complexity of integrated circuit design has increased accordingly. Engineers are considering integrating machine learning techniques into the Electronic Design Automation (EDA) domain to assist in enhancing product performance and minimizing power consumption in the face of Moore's Law limitations. Reinforcement Learning (RL), as a branch of machine learning, has garnered attention in recent years. This paper provides a brief overview of RL in conjunction with EDA technology, outlining in detail the application scenarios of RL within EDA
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Dates et versions

hal-04903766 , version 1 (21-01-2025)

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Citer

Huming Zhu, Xiangru Chen. A survey of Reinforcement Learning for Electronic Design Automation. ISEDA 2024 - 2nd International Symposium of Electronics Design Automation, May 2024, Xi'An, China. pp.717-721, ⟨10.1109/SEDA62518.2024.10617712⟩. ⟨hal-04903766⟩
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