Publications

Our publications provide insight into some of our leading-edge research.

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2025

Marco: Configurable Graph-Based Task Solving and Multi-AI Agents Framework for Hardware Design
Chia-Tung (Mark) Ho, Jing Gong, Yunsheng Bai, Chenhui Deng, Haoxing (Mark) Ren, Brucek Khailany

2024

DRC-Coder: Automated DRC Checker Code Generation Using LLM Autonomous Agent
Chen-Chia Chang, Chia-Tung (Mark) Ho, Yaguang Li, Yiran Chen, Haoxing (Mark) Ren
VerilogCoder: Autonomous Verilog Coding Agents with Graph-based Planning and Abstract Syntax Tree (AST)-based Waveform Tracing Tool
Chia-Tung (Mark) Ho, Haoxing (Mark) Ren, Brucek Khailany
Large Language Model (LLM) for Standard Cell Layout Design Optimization
Chia-Tung (Mark) Ho, Haoxing (Mark) Ren
Best Paper Award
Novel Transformer Model Based Clustering Method for Standard Cell Design Automation
Chia-Tung (Mark) Ho, Ajay Chandna, David Guan, Alvin Ho, Minsoo Kim, Yaguang Li, Haoxing (Mark) Ren
Best Paper Award

2023

CircuitOps: An ML Infrastructure Enabling Generative AI for VLSI Circuit Optimization
Rongjian Liang, Anthony Agnesina, Geraldo Pradipta, Vidya A. Chhabria, Haoxing (Mark) Ren
ChipNeMo: Domain-Adapted LLMs for Chip Design
Mingjie Liu, Teo Ene, Robert Kirby, Chris Cheng, Nathaniel Pinckney, Rongjian Liang, Jonah Alben, Himyanshu Anand, Sanmitra Banerjee, Ismet Bayraktaroglu, Bonita Bhaskaran, Bryan Catanzaro, Arjun Chaudhuri, Sharon Clay, Bill Dally, Laura Dang, Parikshit Deshpande, Siddhanth Dhodhi, Sameer Halepete, Eric Hill, Jiashang Hu, Sumit Jain, Brucek Khailany, George Kokai, Kishor Kunal, Xiaowei Li, Charley Lind, Hao Liu, Stuart Oberman, Sujeet Omar, Sreedhar Pratty, Jonathan Raman, Ambar Sarkar, Zhengjiang Shao, Hanfei Sun, Pratik P Suthar, Varun Tej, Walker Turner, Kaizhe Xu, Haoxing (Mark) Ren
Late Breaking Results: Test Selection For RTL Coverage By Unsupervised Learning From Fast Functional Simulation
Rongjian Liang, Nathaniel Pinckney, Yuji Chai, Haoxing (Mark) Ren, Brucek Khailany
Efficient Transformer Inference with Statically Structured Sparse Attention
Steve Dai, Hasan Genc, Rangharajan Venkatesan, Brucek Khailany
Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields
Guojin Chen, Zehua Pei, Haoyu Yang, Yuzhe Ma, Bei Yu, Martin Wong
Reinforcement Learning Guided Detailed Routing for Custom Circuits
Hao Chen, Kai-Chieh Hsu, Walker Turner, Po-Hsuan Wei, Keren Zhu, David Z. Pan, Haoxing (Mark) Ren
DREAM-GAN: Advancing DREAMPlace towards Commercial-Quality using Generative Adversarial Learning
Yi-Chen Lu, Haoxing (Mark) Ren, Hao-Hsiang Hsiao, Sung Kyu Lim
NVCell 2: Routability-Driven Standard Cell Layout in Advanced Nodes with Lattice Graph Routability Model
Chia-Tung (Mark) Ho, Alvin Ho, Matt Fojtik, Minsoo Kim, Shang Wei, Yaguang LI, Brucek Khailany, Haoxing (Mark) Ren
AutoDMP: Automated DREAMPlace-based Macro Placement
Anthony Agnesina, Puranjay Rajvanshi, Tian Yang, Geraldo Pradipta, Austin Jiao, Ben Keller, Brucek Khailany, Haoxing (Mark) Ren
Enabling Scalable AI Computational Lithography with Physics-Inspired Models
Haoyu Yang, Haoxing (Mark) Ren
A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm
Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, Charbel Sakr, William Dally, Tom Gray, Brucek Khailany

2022

Efficient Arithmetic Block Identification with Graph Learning and Network-flow
Ziyi Wang, Zhuolun He, Chen Bai, Haoyu Yang, Bei Yu
An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design
Mingjie Liu, Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Selim Dogru, Anima Anandkumar, David Z. Pan, Brucek Khailany, Haoxing (Mark) Ren
LNS-Madam: Low-Precision Training in Logarithmic Number System Using Multiplicative Weight Update
Jiawei Zhao, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, Mustafa Ali, Ming-Yu Liu, Brucek Khailany, William Dally, Anima Anandkumar
Why are Graph Neural Networks Effective for EDA Problems?
Haoxing (Mark) Ren, Siddhartha Nath, Yanqing Zhang, Hao Chen, Mingjie Liu
TransSizer: A Novel Transformer-Based Fast Gate Sizer
Siddhartha Nath, Geraldo Pradipta, Corey Hu, Tian Yang, Brucek Khailany, Haoxing (Mark) Ren
TAG: Learning Circuit Spatial Embedding from Layouts
Keren Zhu, Hao Chen, Walker Turner, George F. Kokai, Po-Hsuan Wei, David Z. Pan, Haoxing (Mark) Ren
XT-PRAGGMA: Crosstalk Pessimism Reduction Accessible by GPU Gate-level Simulations and Machine Learning
Vidya Chhabria, Ben Keller, Yanqing Zhang, Sandeep Vollala, Sreedhar Patty, Haoxing (Mark) Ren, Brucek Khailany
Placement Optimization via PPA-Directed Graph Clustering
Yi-Chen Lu, Tian Yang, Sung Kyu Lim, Haoxing (Mark) Ren
A 17–95.6 TOPS/W Deep Learning Inference Accelerator with Per-Vector Scaled 4-bit Quantization for Transformers in 5nm
Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, William Dally, Tom Gray, Brucek Khailany
Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks
Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Mark Kilgard, Anima Anandkumar, Brucek Khailany, Vivek Singh, Haoxing (Mark) Ren
Machine Learning and Algorithms: Let Us Team Up for EDA
Haoxing (Mark) Ren, Brucek Khailany, Matt Fojtik, Yanqing Zhang

2021

NVCell: Standard Cell Layout in Advanced Technology Nodes with Reinforcement Learning
Haoxing (Mark) Ren, Matt Fojtik, Brucek Khailany
Softermax: Hardware/Software Co-Design of an Efficient Softmax for Transformers
Jacob R. Stevens, Rangharajan Venkatesan, Steve Dai, Brucek Khailany, Anand Raghunathan
Graph Learning-Based Arithmetic Block Identification
Zhuolun He, Ziyi Wang, Chen Bai, Haoyu Yang, Bei Yu
Simba: scaling deep-learning inference with chiplet-based architecture
Yakun Sophia Shao, Jason Clemons, Rangharajan Venkatesan, Brian Zimmer, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Brucek Khailany, Steve Keckler
ACM Research Highlight
VS-QUANT: Per-Vector Scaled Quantization for Accurate Low-Precision Neural Network Inference
Steve Dai, Rangharajan Venkatesan, Haoxing (Mark) Ren, Brian Zimmer, William Dally, Brucek Khailany