Publications -

AnalogCoder: Analog Circuit Design via Training-Free Code Generation

Yao Lai, Sungyoung Lee, Guojin Chen, Souradip Poddar, Mengkang Hu, David Z. Pan, Ping Luo

AAAI Conference on Artificial Intelligence (AAAI) 2025

AnalogCoder is a training-free LLM agent for analog circuit design, using feedback-driven prompts and a circuit library to achieve high success rates, outperforming GPT-4o by designing 25 circuits.

[Paper]

AnalogCoder: Analog Circuit Design via Training-Free Code Generation

Yao Lai, Sungyoung Lee, Guojin Chen, Souradip Poddar, Mengkang Hu, David Z. Pan, Ping Luo

AAAI Conference on Artificial Intelligence (AAAI) 2025

AnalogCoder is a training-free LLM agent for analog circuit design, using feedback-driven prompts and a circuit library to achieve high success rates, outperforming GPT-4o by designing 25 circuits.

[Paper]

Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier Designs

Yao Lai, Jinxin Liu, David Z. Pan, Ping Luo

Conference on Neural Information Processing Systems (NeurIPS) 2024 Spotlight

This work uses reinforcement learning to optimize adder and multiplier designs as tree generation tasks, achieving up to 49% faster speed and 45% smaller size, with scalability to 7nm technology.

[Paper]

Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier Designs

Yao Lai, Jinxin Liu, David Z. Pan, Ping Luo

Conference on Neural Information Processing Systems (NeurIPS) 2024 Spotlight

This work uses reinforcement learning to optimize adder and multiplier designs as tree generation tasks, achieving up to 49% faster speed and 45% smaller size, with scalability to 7nm technology.

[Paper]

ChiPFormer: Transferable Chip Placement via Offline Decision Transformer

Yao Lai, Jinxin Liu, Zhentao Tang, Bin Wang, Jianye Hao, Ping Luo

International Conference on Machine Learning (ICML) 2023

ChiPFormer is an offline RL-based method that achieves 10x faster chip placement with superior quality and transferability to unseen circuits.

[Paper]

ChiPFormer: Transferable Chip Placement via Offline Decision Transformer

Yao Lai, Jinxin Liu, Zhentao Tang, Bin Wang, Jianye Hao, Ping Luo

International Conference on Machine Learning (ICML) 2023

ChiPFormer is an offline RL-based method that achieves 10x faster chip placement with superior quality and transferability to unseen circuits.

[Paper]

MaskPlace: Fast Chip Placement via Reinforced Visual Representation Learning

Yao Lai, Yao Mu, Ping Luo

Conference on Neural Information Processing Systems (NeurIPS) 2022 Spotlight

MaskPlace is a method that leverages pixel-level visual representation for chip placement, achieving superior performance with simpler rewards, 60%-90% wirelength reduction, and zero overlaps.

[Paper]

MaskPlace: Fast Chip Placement via Reinforced Visual Representation Learning

Yao Lai, Yao Mu, Ping Luo

Conference on Neural Information Processing Systems (NeurIPS) 2022 Spotlight

MaskPlace is a method that leverages pixel-level visual representation for chip placement, achieving superior performance with simpler rewards, 60%-90% wirelength reduction, and zero overlaps.

[Paper]