Publications | Research

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Artificial Intelligence and Machine Learning
Circuits and VLSI Design

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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

Parasitic-Aware Analog Circuit Sizing with Graph Neural Networks and Bayesian Optimization

Mingjie Liu, Walker Turner, George Kokai, David Z. Pan, Brucek Khailany, Haoxing (Mark) Ren

MAVIREC: ML-Aided Vectored IR-Drop Estimation and Classification

Vidya A. Chhabria, Yanqing Zhang, Haoxing (Mark) Ren, Ben Keller, Brucek Khailany, Sachin S. Sapatnekar

Standard Cell Routing with Reinforcement Learning and Genetic Algorithm in Advanced Technology Nodes

Haoxing (Mark) Ren, Matt Fojtik