Publications

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

Filters

Filters

Publication Year

Research Areas

Events

No Results Available

2020

The Architectural Implications of Distributed Reinforcement Learning on CPU-GPU Systems
Ahmet Inci, Evgeny Bolotin, Yaosheng Fu, Gal Dalal, Shie Mannor, David Nellans, Diana Marculescu
GPU-Trident: Efficient Modeling of Error Propagation in GPU Programs
Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Michael B. Sullivan, Timothy Tsai, Siva Hari
CaSA: End-to-end Quantitative Security Analysis of Randomly Mapped Caches
Thomas Bourgeat, Jules Drean, Yuheng Yang, Lillian Tsai, Joel Emer, Mengjia Yan
Locality-Centric Data and Threadblock Management for Massive GPUs
Mahmoud Khairy, Vadim Nikiforov, David Nellans, Timothy G. Rogers
HarDNN: Fine-Grained Vulnerability Evaluation and Protection for Convolutional Neural Networks
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
How to Evaluate Deep Neural Network Processors: TOPS/W (Alone) Considered Harmful
Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer
Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks
Soroush Ghodrati, Byung Hoon Ahn, Joon Kyung Kim, Sean Kinzer, Brahmendra Reddy Yatham, Navateja Alla, Hardik Sharma, Mohammad Alian, Eiman Ebrahimi, Nam Sung Kim, Cliff Young, Hadi Esmaeilzadeh
PyTorchFI: A Runtime Perturbation Tool for DNNs
Abdulrahman Mahmoud, Neeraj Aggarwal, Alex Nobbe, Jose Rodrigo Sanchez Vicarte, Sarita V. Adve, Christopher W. Fletcher, Iuri Frosio, Siva Hari
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
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler
There’s Plenty of Room at the Top: What Will Drive Computer Performance after Moore’s Law?
Charles E. Leiserson, Neil C. Thompson, Joel Emer, Bradley C. Kuszmaul, Butler W. Lampson, Daniel Sanchez , Tao B. Schardl
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
Estimating Silent Data Corruption Rates Using a Two-Level Model
Siva Hari, Paolo Rech, Timothy Tsai, Mark Stephenson, Arslan Zulfiqar, Michael B. Sullivan, Philip Shirvani, Paul Racunas, Joel Emer, Steve Keckler
MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings
Hyoukjun Kwon, Prasanth Chatarasi, Vivek Sarkar, Tushar Krishna, Michael Pellauer, Angshuman Parashar
BYOC: A "Bring Your Own Core" Framework for Heterogeneous-ISA Research
Jonathan Balkind, Katie Lim, Michael Schaffner, Fei Gao, Grigory Chirkov, Ang Li, Alexey Lavrov, Tri M. Nguyen, Yaosheng Fu, Florian Zaruba, Kunal Gulati, Luca Benini, David Wentzlaf
Safecracker: Leaking Secrets through Compressed Caches
Po-An Tsai, Andres Sanchez, Christopher W. Fletcher, Daniel Sanchez
IEEE Micro Top Picks in Computer Architecture
RealityCheck: Bringing Modularity, Hierarchy, and Abstraction to Automated Microarchitectural Memory Consistency Verification
Yatin A. Manerkar, Daniel Lustig, Margaret Martonosi
Feature Map Vulnerability Evaluation in CNNs
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
HarDNN: Feature Map Vulnerability Evaluation in CNNs
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
HMG: Extending Cache Coherence Protocols Across Modern Hierarchical Multi-GPU Systems
Xiaowei Ren, Daniel Lustig, Evgeny Bolotin, Aamer Jaleel, Oreste Villa, David Nellans
Speculative Reconvergence for Improved SIMT Efficiency
Sana Damani, Daniel Johnson, Mark Stephenson, Eddie Yan, Olivier Giroux, Michael McKeown, Steve Keckler

2018

Optimizing Software-Directed Instruction Replication for GPU Error Detection
Abdulrahman Mahmoud, Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler
Exploiting Idle Resources in a High-Radix Switch for Supplemental Storage
Matthias Blumrich, Ted Jiang, Larry Dennison
PipeProof: Automated Memory Consistency Proofs for Microarchitectural Specifications
Yatin A. Manerkar, Daniel Lustig, Margaret Martonosi, Aarti Gupta
IEEE Micro Top Picks in Computer Architecture (Honorable Mention)
Best Paper nominee
SwapCodes: Error Codes for Hardware-Software Cooperative GPU Pipeline Error Detection
Michael B. Sullivan, Siva Hari, Brian Zimmer, Timothy Tsai, Stephen W. Keckler
Harmonizing Speculative and Non-Speculative Execution in Architectures for Ordered Parallelism
Mark C. Jeffrey, Victor A. Ying, Suvinay Subramanian, Hyun Ryong Lee, Joel Emer, Daniel Sanchez
DAWG: A Defense Against Cache Timing Attacks in Speculative Execution Processors
Vladimir Kiriansky, Ilia Lebedev, Saman Amarasinghe, Srinivas Devadas, Joel Emer
CheckMate: Automated Synthesis of Hardware Exploits and Security Litmus Tests
Caroline Trippel, Daniel Lustig, Margaret Martonosi
IEEE Micro Top Picks in Computer Architecture
Combining HW/SW Mechanisms to Improve NUMA Performance of Multi-GPU Systems
Vinson Young, Aamer Jaleel, Evgeny Bolotin, Eiman Ebrahimi, David Nellans, Oreste Villa
Exposing Memory Access Patterns to Improve Instruction and Memory Efficiency in GPUs
Neal Crago, Mark Stephenson, Steve Keckler
Software-Directed Techniques for Improved GPU Register File Utilization
Dani Voitsechov, Arslan Zulfiqar, Mark Stephenson, Mark Gebhart, Steve Keckler