World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
23970
World Ranking
1573
National Ranking
821

Research.com Recognitions

  • 2011 - ACM Fellow For contributions to computer architectures and technology modeling.
  • 2011 - IEEE Fellow For contributions to computer architectures and memory systems
  • 2006 - ACM Senior Member
  • 2003 - ACM Grace Murray Hopper Award For ground-breaking analysis of technology scaling for high-performance processors that sheds new light on the methods required to maintain performance improvement trends in computer architecture, and on the design implications for future high-performance processors and systems.
  • 2002 - Fellow of Alfred P. Sloan Foundation

Overview

Stephen W. Keckler is affiliated with Nvidia in the United States. Their research contributions span multiple areas within computer science and engineering, focusing on electrical and electronic engineering, artificial intelligence, computer vision and pattern recognition, hardware and architecture, and computer networks and communications.

Keckler's recent publications demonstrate a focus on neural network accelerators, sparse neural processing, and memory safety in CUDA applications. Notable papers include:

  • "A 0.32-128 TOPS, Scalable Multi-Chip-Module-Based Deep Neural Network Inference Accelerator With Ground-Referenced Signaling in 16 nm" (2020, IEEE Journal of Solid-State Circuits)
  • "SNAP: An Efficient Sparse Neural Acceleration Processor for Unstructured Sparse Deep Neural Network Inference" (2020, IEEE Journal of Solid-State Circuits)
  • "Simba" (2021, Communications of the ACM)
  • "HarDNN: Feature Map Vulnerability Evaluation in CNNs" (2020, arXiv [Cornell University])
  • "cuCatch: A Debugging Tool for Efficiently Catching Memory Safety Violations in CUDA Applications" (2023, Proceedings of the ACM on Programming Languages)

The primary research topics addressed by Keckler include:

  • Advanced Neural Network Applications
  • Radiation Effects in Electronics
  • Parallel Computing and Optimization Techniques
  • Advanced Memory and Neural Computing
  • CCD and CMOS Imaging Sensors
  • Adversarial Robustness in Machine Learning
  • Ferroelectric and Negative Capacitance Devices

Keckler has collaborated frequently with the following coauthors:

  • Siva Kumar Sastry Hari
  • Timothy Tsai
  • Michael B. Sullivan
  • Joel Emer
  • Jason Clemons

Their work has been published in a range of venues, with multiple contributions to arXiv (Cornell University), IEEE Journal of Solid-State Circuits, Communications of the ACM, Proceedings of the ACM on Programming Languages, and IEEE Micro.

Throughout their career, Keckler has been recognized with several awards, including:

  • ACM Fellow (2011) for contributions to computer architectures and technology modeling
  • IEEE Fellow (2011) for contributions to computer architectures and memory systems
  • ACM Senior Member (2006)
  • ACM Grace Murray Hopper Award (2003) for analysis of technology scaling impacting high-performance processor design
  • Fellow of the Alfred P. Sloan Foundation (2002)

Best Publications

  • Modeling the effect of technology trends on the soft error rate of combinational logic

    P. Shivakumar;M. Kistler;S.W. Keckler;D. Burger

  • An adaptive, non-uniform cache structure for wire-delay dominated on-chip caches

    Changkyu Kim;Doug Burger;Stephen W. Keckler

  • SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks

    Angshuman Parashar;Minsoo Rhu;Anurag Mukkara;Antonio Puglielli

  • Clock rate versus IPC: the end of the road for conventional microarchitectures

    Vikas Agarwal;M. S. Hrishikesh;Stephen W. Keckler;Doug Burger

  • Exploiting ILP, TLP, and DLP with the polymorphous trips architecture

    K. Sankaralingam;R. Nagarajan;Haiming Liu;Changkyu Kim

  • GPUs and the Future of Parallel Computing

    S. W. Keckler;W. J. Dally;B. Khailany;M. Garland

  • A NUCA Substrate for Flexible CMP Cache Sharing

    J. Jaehyuk Huh;C. Changkyu Kim;H. Shafi;L. Lixin Zhang

  • Research Challenges for On-Chip Interconnection Networks

    J.D. Owens;W.J. Dally;R. Ho;D.N. Jayasimha

  • Scaling to the end of silicon with EDGE architectures

    D. Burger;S.W. Keckler;K.S. McKinley;M. Dahlin

  • Measuring experimental error in microprocessor simulation

    Rajagopalan Desikan;Doug Burger;Stephen W. Keckler

  • The M-Machine multicomputer

    Marco Fillo;Stephen W. Keckler;William J. Dally;Nicholas P. Carter

  • Regional congestion awareness for load balance in networks-on-chip

    P. Gratz;B. Grot;S.W. Keckler

  • Timeloop: A Systematic Approach to DNN Accelerator Evaluation

    Angshuman Parashar;Priyanka Raina;Yakun Sophia Shao;Yu-Hsin Chen

  • Understanding error propagation in deep learning neural network (DNN) accelerators and applications

    Guanpeng Li;Siva Kumar Sastry Hari;Michael Sullivan;Timothy Tsai

  • vDNN: virtualized deep neural networks for scalable, memory-efficient neural network design

    Minsoo Rhu;Natalia Gimelshein;Jason Clemons;Arslan Zulfiqar

  • Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture

    Yakun Sophia Shao;Jason Clemons;Rangharajan Venkatesan;Brian Zimmer

  • The optimal logic depth per pipeline stage is 6 to 8 FO4 inverter delays

    M. S. Hrishikesh;Doug Burger;Norman P. Jouppi;Stephen W. Keckler

  • Energy-efficient mechanisms for managing thread context in throughput processors

    Mark Gebhart;Daniel R. Johnson;David Tarjan;Stephen W. Keckler

  • SCNN

    Unknown

  • Kilo-NOC: a heterogeneous network-on-chip architecture for scalability and service guarantees

    Boris Grot;Joel Hestness;Stephen W. Keckler;Onur Mutlu

  • Express Cube Topologies for on-Chip Interconnects

    Boris Grot;Joel Hestness;Stephen W. Keckler;Onur Mutlu

Frequent Co-Authors

Doug Burger
Doug Burger Microsoft (United States)
William J. Dally
William J. Dally Nvidia (United Kingdom)
Karthikeyan Sankaralingam
Karthikeyan Sankaralingam University of Wisconsin–Madison
Brucek Khailany
Brucek Khailany Nvidia (United States)
Changkyu Kim
Changkyu Kim Facebook (United States)
David Nellans
David Nellans Nvidia (United States)
Kathryn S. McKinley
Kathryn S. McKinley Google (United States)
Onur Mutlu
Onur Mutlu ETH Zurich
Calvin Lin
Calvin Lin The University of Texas at Austin

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