Publications

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

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2019

GPU-Accelerated Atari Emulation for Reinforcement Learning
Steven Dalton, Iuri Frosio, Michael Garland
Temporally Dense Ray Tracing
Pontus Ebelin, Jim Nilsson, Marco Salvi, Josef Spjut, Tomas Akenine-Möller
Dynamic Many-Light Sampling for Real-Time Ray Tracing
Pierre Moreau, Matt Pharr, Petrik Clarberg
Deep Hierarchical Multi-label Classification of Chest X-ray Images
Haomin Chen, Shun Miao, Daguang Xu, Gregory D. Hager, Adam P. Harrison
Kayotee: A Fault Injection-based System to Assess the Safety and Reliability of Autonomous Vehicles to Faults and Errors
Saurabh Jha, Timothy Tsai, Siva Hari, Michael B. Sullivan, Zbigniew Kalbarczyk, Steve Keckler, Ravishankar K. Iyer
ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
Saurabh Jha, Subho S. Banerjee, Timothy Tsai, Siva Hari, Michael B. Sullivan, Zbigniew T. Kalbarczyk, Steve Keckler, Ravishankar K. Iyer
GPU Snapshot: Checkpoint Offloading for GPU-Dense Systems
Kyushick Lee, Michael B. Sullivan, Siva Hari, Timothy Tsai, Steve Keckler, Mattan Erez
On the Trend of Resilience for GPU-Dense Systems
Kyushick Lee, Michael B. Sullivan, Siva Hari, Timothy Tsai, Steve Keckler, Mattan Erez
Best of SELSE (Workshop on Silicon Errors in Logic - System Effects)
ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
Saurabh Jha, Subho Banerjee, Timothy Tsai, Siva Hari, Michael B. Sullivan, Zbigniew T. Kalbarczyk, Steve Keckler, Ravishankar K. Iyer
Translation Ranger: Operating System Support for Contiguity-Aware TLBs
Zi Yan, Daniel Lustig, David Nellans, Abhishek Bhattacharjee
Adaptive Memory-Side Last-Level GPU Caching
Xia Zhao, Almutaz Adileh, Zhibin Yu, Zhiying Wang, Aamer Jaleel, Lieven Eeckhout
Neural RGB->D Sensing: Depth and Uncertainty from a Video Camera
Chao Liu, Jinwei Gu, Kihwan Kim, Srinivasa Narasimhan, Jan Kautz
PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image
Chen Liu, Kihwan Kim, Jinwei Gu, Yasutaka Furukawa, Jan Kautz
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras, Samuli Laine, Timo Aila
SIDOD: A Synthetic Image Dataset for 3D Object Pose Recognition with Distractors
Mona Jalal, Josef Spjut, Ben Boudaoud, Margrit Betke
Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments
Xueting Li, Sifei Liu, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz
Pixel-Adaptive Convolutional Neural Networks
Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik-Learned Miller, Jan Kautz
Semantic Image Synthesis with Spatially-Adaptive Normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu
STEP: Spatio-Temporal Progressive Learning for Video Action Detection
Xitong Yang, Xiaodong Yang, Ming-Yu Liu, Fanyi Xiao, Larry Davis, Jan Kautz
CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification
Zheng Tang, Milind Naphade, Ming-Yu Liu, Xiaodong Yang, Stan Birchfield, Shuo Wang, Ratnesh Kumar, David Anastasiu, Jenq-Neng Hwan
SCOPS: Self-Supervised Co-Part Segmentation
Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang , Jan Kautz
Joint Discriminative and Generative Learning for Person Re-identification
Zhedong Zheng, Xiaodong Yang, Zhiding Yu, Liang Zheng, Yi Yang, Jan Kautz
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation
Anurag Ranjan, Varun Jampani, Lukas Balles, Kihwan Kim, Deqing Sun, Jonas Wulff, Michael J. Black
Importance Estimation for Neural Network Pruning
Pavlo Molchanov, Arun Mallya, Stephen Tyree, Iuri Frosio, Jan Kautz
SNAP: A 1.67 – 21.55 TOPS/W Sparse Neural Acceleration Processor for Unstructured Sparse Deep Neural Network Inference in 16nm CMOS
Jie-Fang Zhang, Ching-En Lee, Chester Liu, Yakun Sophia Shao, Steve Keckler, Zhengya Zhang
A 0.11 pJ/Op, 0.32-128 TOPS, Scalable Multi-Chip-Module-based Deep Neural Network Accelerator with Ground-Reference Signaling in 16nm
Brian Zimmer, Rangharajan Venkatesan, Sophia Shao, Jason Clemons, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Steve Keckler, Brucek Khailany
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
A Fine-Grained GALS SoC with Pausible Adaptive Clocking in 16 nm FinFET
Matt Fojtik, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Stephen Tell, Brian Zimmer, Tezaswi Raja, Kevin Zhou, William Dally, Brucek Khailany
ASYNC 2019 Best Paper Award
Dynamic Diffuse Global Illumination with Ray-Traced Irradiance Fields
Zander Majercik, Jean-Philippe Guertin, Derek Nowrouzezahrai, Morgan McGuire