People

Jason Clemons

Jason Clemons joined NVIDIA in March 2013 and is a member of the Architecture Research Group.  His current work focuses on the intersection of mobile computer vision and computer architecture.

He recieved his Ph.D. from the University of Michigan, Ann Arbor in 2013.  Prior to attending the University of Michigan, Jason worked at Whirlpool Corporation.  During his time there he complete his Masters of Science in Computer Science and Engineering as a part of the Whirlpool Technical Excellence Program.  He recieved his Bachelor Of Science in Electrical Engineering from Michigan Technological University in 2000.

Publications

2022

Augmenting Legacy Networks for Flexible Inference.
Jason Clemons, Iuri Frosio, Maying Shen, Jose M. Alvarez, Steve Keckler
Workshop on Computational Aspects of Deep Learning (CADL)

2021

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
Communications of the ACM
ACM Research Highlight

2020

A 0.32–128 TOPS, Scalable Multi-Chip-Module-Based Deep Neural Network Inference Accelerator With Ground-Referenced Signaling in 16 nm
Brian Zimmer, Rangharajan Venkatesan, Yakun 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
IEEE Journal of Solid-State Circuits (JSSC)
JSSC 2020 Best Paper award

2019

MAGNet: A Modular Accelerator Generator for Neural Networks
Rangharajan Venkatesan, Sophia Shao, Miaorong Wang, Jason Clemons, Steve Dai, Matt Fojtik, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Yanqing Zhang, Brian Zimmer, William Dally, Joel Emer, Steve Keckler, Brucek Khailany
International Conference On Computer Aided Design (ICCAD)
Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture
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
International Symposium on Microarchitecture (MICRO)
Best Paper award, IEEE Micro Top Picks in Computer Architecture (Honorable Mention)
A 0.11 pJ/Op, 0.32-128 TOPS, Scalable Multi-Chip-Module-based Deep Neural Network Accelerator Designed with a High-Productivity VLSI Methodology
Rangharajan Venkatesan, Sophia Shao, Brian Zimmer, 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
Hot Chips: A Symposium on High Performance Chips
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
Symposium on VLSI Circuits
Buffets: An Efficient and Composable Storage Idiom for Explicit Decoupled Data Orchestration
Michael Pellauer, Yakun Sophia Shao, Jason Clemons, Neal Crago, Kartik Hegde, Rangharajan Venkatesan, Steve Keckler, Christopher W. Fletcher, Joel Emer
International Conference on Architectural Support for Programming Languages and…
IEEE Micro Top Picks in Computer Architecture (Honorable Mention)

2018

A Modular Digital VLSI Flow for High-Productivity SoC Design
Brucek Khailany, Evgeni Krimer, Rangharajan Venkatesan, Jason Clemons, Joel Emer, Matt Fojtik, Alicia Klinefelter, Michael Pellauer, Nathaniel Pinckney, Sophia Shao, Shreesha Srinath, Christopher Torng, Sam (Likun) Xi, Yanqing Zhang, Brian Zimmer
Design Automation Conference (DAC)
Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training
Maohua Zhu, Jason Clemons, Jeff Pool, Minsoo Rhu, Steve Keckler, Yuan Xie
arXiv

2017

Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU
Iuri Frosio, Stephen Tyree, Jason Clemons, Jan Kautz, Mohammad Babaeizadeh
Proceeding of ICLR 2017

2016

Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU
Mohammad Babaeizadeh, Iuri Frosio, Stephen Tyree, Jason Clemons, Jan Kautz
arXiv
A Patch Memory System For Image Processing and Computer Vision.
Jason Clemons, Chih-Chi Cheng, Iuri Frosio, Daniel Johnson, Steve Keckler
International Symposium on Microarchitecture (MICRO)
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design.
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, Steve Keckler
International Symposium on Microarchitecture (MICRO)
A Real-time Energy-Efficient Superpixel Hardware Accelerator for Mobile Computer Vision Applications
Injoon Hong, Jason Clemons, Rangharajan Venkatesan, Iuri Frosio, Brucek Khailany, Steve Keckler
Design Automation Conference (DAC)
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, Steve Keckler
arXiv