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Artificial Intelligence and Machine Learning

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2019

DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement

Yibo Lin, Shounak Dhar, Wuxi Li, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan

DAC 2019 Best Paper Award

High Performance Graph Convolutional Networks with Applications in Testability Analysis

Yuzhe Ma, Haoxing (Mark) Ren, Brucek Khailany, Harbinder Sikka, Lijuan Luo, Karthikeyan Natarajan, Bei Yu

PRIMAL: Power Inference using Machine Learning

Yuan Zhou, Haoxing (Mark) Ren, Yanqing Zhang, Ben Keller, Brucek Khailany, Zhiru Zhang

Analog/Mixed-Signal Hardware Error Modeling for Deep Learning Inference

Angad S. Rekhi, Brian Zimmer, Nikola Nedovic, Nigxi Liu, Rangharajan Venkatesan, Miaorong Wang, Brucek Khailany, William Dally, Tom Gray

Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs

Esha Choukse, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Stephen W. Keckler

DeLTA: GPU Performance Model for Deep Learning Applications with In-depth Memory System Traffic Analysis

Sankug Lym, Donghyuk Lee, Niladrish Chatterjee, Mike O'Connor, Mattan Erez

Routability-Driven Macro Placement with Embedded CNN-Based Prediction Model

Yu-Hung Huang, Zhiyao Xie, Guan-Qi Fang, Tao-Chun Yu, Haoxing (Mark) Ren, Shao-Yun Fang, Yiran Chen, Jiang Hu

Timeloop: A Systematic Approach to DNN Accelerator Evaluation

Angshuman Parashar, Priyanka Raina, Yakun Sophia Shao, Yu-Hsin Chen, Victor A. Ying, Anurag Mukkara, Rangharajan Venkatesan, Brucek Khailany, Steve Keckler, Joel Emer

Informative Object Annotations: Tell Me Something I Don't Know

Lior Bracha, Gal Chechik

Rethinking full connectivity in recurrent neural networks

Matthijs Van keirsbilck, Alex Keller, Xiaodong Yang

Metaoptimization on a Distributed System for Deep Reinforcement Learning

Greg Heinrich, Iuri Frosio

Unsupervised Stylish Image Description Generation via Domain Layer Norm

Cheng-Kuan Chen, Zhu-Feng Pan, Ming-Yu Liu, Min Sun

Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation

Deqing Sun, Xiaodong Yang, Ming-Yu Liu, Jan Kautz

A Fusion Approach for Multi-Frame Optical Flow Estimation

Zhile Ren, Orazio Gallo, Deqing Sun, Ming-Hsuan Yang, Erik B. Sudderth, Jan Kautz