The First IEEE International Workshop on LLM-Aided Design, 2024 (LAD’24)

This new international workshop will focus on how to use LLM (Large Language Model) as a methodology to help design circuits, software, and computing systems with improved quality, productivity, robustness, and cost. It is the first of its kind international workshop in the community that will focus on discussing results that leverage the significant advancement and innovation captured by the generative AI and LLM technology to offer new methods and solutions for design automation targeting various applications. The workshop will be a timely venue that will host leading researchers and thought leaders in this fast-growing area and will provide a forum for researchers and practitioners to present their latest results, contribute open-source LLM models, datasets, tool flows, and offer benchmarking, testing and validation methods and solutions. LAD'24 is in-cooperation with ACM SIGDA.

Large Language Model (LLM) for Standard Cell Layout Design Optimization 

Authors: Chia-Tung Ho, Haoxing Ren

MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation 

Authors: Yongan Zhang, Zhongzhi Yu, Yonggan Fu, Cheng Wan, Yingyan Celine Lin

AMSNet: Netlist Dataset for AMS Circuits Authors: Zhuofu Tao, Yichen Shi, Yiru Huo, Rui Ye, Zonghang Li, Li Huang, Chen Wu, Na Bai, Zhiping Yu, Ting-Jung Lin, Lei He