Mike O'Connor

Mike O'Connor currently a Senior Manager and Research Scientist at NVIDIA in the Architecture Research group in the Austin, TX office.

He leads a team of researchers focusing on enabling technologies for high-bandwidth, energy efficient future DRAM/NVRAM systems.

He has broad interests in many areas of computer architecture, including:

High-Performance Memory Systems (DRAM and NVRAM)
GPU Architectures (both processing cores and cache/memory systems)
Low-power datapath design
Reliabilty/Resilience

Research Area(s)

Artificial Intelligence and Machine Learning

High Performance Computing

Resilience and Safety

Main Field of Interest

Computer Architecture

Google Scholar

https://scholar.google.com/citations?user=rc89KiIAAAAJ&hl=en

Publications

2022

Saving PAM4 Bus Energy with SMOREs: Sparse Multi-level Opportunistic Restricted Encodings

Mike O'Connor, Donghyuk Lee, Niladrish Chatterjee, Michael B. Sullivan, Steve Keckler

International Symposium on High-Performance Computer Architecture (HPCA)

Characterizing and Mitigating Soft Errors in GPU DRAM

Michael B. Sullivan, Nirmal R. Saxena, Mike O'Connor, Donghyuk Lee, Paul Racunas, Saurabh Hukerikar, Timothy Tsai, Siva Kumar Sastry Hari, Stephen W. Keckler

IEEE Micro (Top Picks from the 2021 Computer Architecture Conferences)

Selected as a top pick from the 2021 computer architecture conferences

2021

Characterizing and Mitigating Soft Errors in GPU DRAM

Michael B. Sullivan, Nirmal Saxena, Mike O'Connor, Donghyuk Lee, Paul Racunas, Saurabh Hukerikar, Timothy Tsai, Siva Hari, Steve Keckler

International Symposium on Microarchitecture (MICRO)

Learning Sparse Matrix Row Permutations for Efficient SpMM on GPU Architectures

Atefeh Mehrabi, Donghyuk Lee, Niladrish Chatterjee, Danial J. Sorin, Benjamin C. Lee, Mike O'Connor

International Symposium on Performance Analysis of Systems and Software (ISPASS)

Saugata Ghose, Abdullah Giray Yağlıkçı, Raghav Gupta, Donghyuk Lee, Kais Kudrolli, William X. Liu, Hasan Hassan, Kevin Chang, Niladrish Chatterjee, Aditya Agrawal, Mike O'Connor, Onur Mutlu

ACM International Conference on Measurement and Analysis of Computer Systems (S…

Reducing Data Transfer Energy by Exploiting Similarity within a Data Transaction

Donghyuk Lee, Mike O'Connor, Niladrish Chatterjee

International Symposium on High Performance Computer Architecture (HPCA)

Best Paper Nominee

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks

Minsoo Rhu, Mike O'Connor, Niladrish Chatterjee, Jeff Pool, Youngeun Kwon, Steve Keckler

International Symposium on High Performance Computer Architecture (HPCA)

2017

Toward Standardized Near-Data Processing with Unrestricted Data Placement for GPUs

Gwangsun Kim, Niladrish Chatterjee, Mike O'Connor, Kevin Hsieh

International Conference for High-Performance Computing, Networking, Storage, a…

Fine-Grained DRAM: Energy-Efficient DRAM for Extreme Bandwidth Systems

Mike O'Connor, Niladrish Chatterjee, Donghyuk Lee, John Wilson, Aditya Agrawal, Steve Keckler, William Dally

International Symposium on Microarchitecture (MICRO)

Understanding Reduced-Voltage Operation in Modern DRAM Devices: Experimental Characterization, Analysis, and Mechanisms

Kevin Chang, Abdullah Giray Yağlıkçı, Saugata Ghose, Aditya Agrawal, Niladrish Chatterjee, Abhijith Kashyap, Donghyuk Lee, Mike O'Connor, Hasan Hassan, Onur Mutlu

ACM Conference on Measurement and Analysis of Computer Systems (SIGMETRICS 2017)

Architecting an Energy-Efficient DRAM System for GPUs

Niladrish Chatterjee, Mike O'Connor, Donghyuk Lee, Daniel Johnson, Minsoo Rhu, Steve Keckler, William Dally

International Symposium on High Performance Computer Architecture (HPCA)