Publications

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

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2023

Parsimony: Enabling SIMD/Vector Programming in Standard Compiler Flows
Vijay Kandiah, Daniel Lustig, Oreste Villa, David Nellans, Nikos Hardavellas

2022

Towards Precision-Aware Fault Tolerance Approaches for Mixed-Precision Applications
Bo Fang, Siva Hari, Timothy Tsai, Xinyi Li, Ganesh Gopalakrishnan, Ignacio Laguna, Kevin Barker, Ang Li

2021

GPS: A Global Publish-Subscribe Model for Multi-GPU Memory Management
Harini Muthukrishnan, Daniel Lustig, David Nellans, Thomas Wenisch
Best Paper nominee
IEEE Micro Top Picks in Computer Architecture (Honorable Mention)
EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal in GPUs
Seung Won Min, Vikram Sharma Mailthody, Zaid Qureshi, Jinjun Xiong, Eiman Ebrahimi, Wen-mei Hwu
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoglu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu
Efficient Multi-GPU Shared Memory via Automatic Optimization of Fine-Grained Transfers
Harini Muthukrishnan, David Nellans, Daniel Lustig, Jeffrey Fessler, Thomas Wenisch
Demystifying GPU Reliability: Comparing and Combining Beam Experiments, Fault Simulation, and Profiling
Fernando Fernandes dos Santos, Siva Hari, Pedro Martins Basso, Luigi Carro, Paolo Rech
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
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoglu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu

2020

Locality-Centric Data and Threadblock Management for Massive GPUs
Mahmoud Khairy, Vadim Nikiforov, David Nellans, Timothy G. Rogers
EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal In GPUs
Seung Won Min, Vikram Sharma Mailthody, Zaid Qureshi, Jinjun Xiong, Eiman Ebrahimi, Wen-mei Hwu
Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs
Esha Chouske, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Steve Keckler
An In-Network Architecture for Accelerating Shared-Memory Multiprocessor Collectives
Benjamin Klenk, Ted Jiang, Greg Thorson, Larry Dennison

2019

Near-Memory Data Transformation for Efficient Sparse Matrix Multi-Vector Multiplication
Daichi Fujiki, Niladrish Chatterjee, Donghyuk Lee, Mike O'Connor
Optimizing Multi-GPU Parallelization Strategies for Deep Learning Training
Saptadeep Pal, Eiman Ebrahimi, Arslan Zulfiqar, Yaosheng Fu, Victor Zhang, Szymon Migacz, David Nellans, Puneet Gupta
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)
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
Sangkug Lym, Donghyuk Lee, Mike O'Connor, Niladrish Chatterjee, Mattan Erez

2018

Exploiting Idle Resources in a High-Radix Switch for Supplemental Storage
Matthias Blumrich, Ted Jiang, Larry Dennison

2017

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
SASSIFI: An Architecture-level Fault Injection Tool for GPU Application Resilience Evaluation
Siva Hari, Timothy Tsai, Mark Stephenson, Steve Keckler, Joel Emer

2016

vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design.
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, Steve Keckler
Approxilyzer: Towards A Systematic Framework for Instruction-Level Approximate Computing and its Application to Hardware Resiliency
Radha Venkatagiri, Abdulrahman Mahmoud, Siva Hari, Sarita Adve
All-Inclusive ECC: Thorough End-to-End Protection for Reliable Computer Memory
Jungrae Kim, Michael B. Sullivan, Sangkug Lym, Mattan Erez
Selective GPU Caches to Eliminate CPU-GPU HW Cache Coherence
Neha Agarwal, David Nellans, Eiman Ebrahimi, Thomas F. Wenisch, John Danskin, Steve Keckler
Towards High Performance Paged Memory for GPUs
Tianhao Zheng, David Nellans, Arslan Zulfiqar, Mark Stephenson, Steve Keckler
A Case for Toggle-Aware Compression for GPU Systems
Gennady Pekhimenko, Evgeny Bolotin, Nandita Vijaykumar, Onur Mutlu, Todd C. Mowry, Steve Keckler

2015

In-Memory Graph Databases for Web-Scale Data
Vito Giovanni Castellana, Alessandro Morari, Jesse Weaver, Antonino Time, David Haglin, Oreste Villa, John Feo

2014

Scaling the Power Wall: A Path to Exascale
Oreste Villa, Daniel Johnson, Mike O'Connor, Evgeny Bolotin, David Nellans, Justin Luitjens, Nikolai Sakharnykh, Peng Wang, Paulius Micikevicius, Anthony Scudiero, Steve Keckler, William Dally