April 9, 2024, 4:42 a.m. | Zhihui Deng, Yuanyuan Duan, Leilai Shao, Xiaolei Zhu

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.04943v1 Announce Type: new
Abstract: Chiplet-based systems, integrating various silicon dies manufactured at different integrated circuit technology nodes on a carrier interposer, have garnered significant attention in recent years due to their cost-effectiveness and competitive performance. The widespread adoption of reinforcement learning as a sequential placement method has introduced a new challenge in determining the optimal placement order for each chiplet. The order in which chiplets are placed on the interposer influences the spatial resources available for earlier and later …

abstract adoption arxiv attention cost cs.ai cs.ar cs.lg exploration graph graph representation nodes performance placement reinforcement reinforcement learning representation silicon systems technology type

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

AI Engineering Manager

@ M47 Labs | Barcelona, Catalunya [Cataluña], Spain