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Computer Architecture

2021

Heterogeneous Dataflow Accelerators for Multi-DNN Workloads

Hyoukjun Kwon, Liangzhen Lai, Michael Pellauer, Tushar Krishna, Yu-Hsin Chen, Vikas Chandra

SNAP: An Efficient Sparse Neural Acceleration Processor for Unstructured Sparse Deep Neural Network Inference

Jie-Fang Zhang, Ching-En Lee, Chester Liu, Yakun Sophia Shao, Steve Keckler, Zhengya Zhang

Hardware Abstractions for Targeting EDDO Architectures with the Polyhedral Model

Angshuman Parashar, Prasanth Chatarasi, Po-An Tsai

Flexion: A Quantitative Metric for Flexibility in DNN Accelerators

Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna

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