Publications

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

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2023

CircuitOps: An ML Infrastructure Enabling Generative AI for VLSI Circuit Optimization
Rongjian Liang, Anthony Agnesina, Geraldo Pradipta, Vidya A. Chhabria, Mark Haoxing 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, Mark Haoxing Ren
Late Breaking Results: Test Selection For RTL Coverage By Unsupervised Learning From Fast Functional Simulation
Rongjian Liang, Nathaniel Pinckney, Yuji Chai, Mark Haoxing 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, Mark Haoxing Ren
DREAM-GAN: Advancing DREAMPlace towards Commercial-Quality using Generative Adversarial Learning
Yi-Chen Lu, Mark Haoxing 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, Mark Haoxing Ren
AutoDMP: Automated DREAMPlace-based Macro Placement
Anthony Agnesina, Puranjay Rajvanshi, Tian Yang, Geraldo Pradipta, Austin Jiao, Ben Keller, Brucek Khailany, Mark Haoxing Ren
Enabling Scalable AI Computational Lithography with Physics-Inspired Models
Haoyu Yang, Mark Haoxing 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