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Computer Science

D-Index
63
Citations
18860
World Ranking
2723
National Ranking
1353

Overview

John Shalf is affiliated with Lawrence Berkeley National Laboratory in the United States. Their research focuses primarily on computer science and engineering, with significant contributions in subfields such as electrical and electronic engineering, computer networks and communications, hardware and architecture, artificial intelligence, and information systems.

The main topics covered in their work include:

  • Parallel Computing and Optimization Techniques
  • Advanced Data Storage Technologies
  • Cloud Computing and Resource Management
  • Photonic and Optical Devices
  • Optical Network Technologies
  • Distributed and Parallel Computing Systems
  • Neural Networks and Reservoir Computing

John Shalf has contributed to various publication venues, with frequent publications in:

  • Computing in Science & Engineering
  • arXiv (Cornell University)
  • ACM Transactions on Architecture and Code Optimization
  • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • Journal of Optical Communications and Networking

Selected recent papers authored or co-authored by John Shalf include:

  • The future of computing beyond Moore's Law, 2020, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • A Case For Intra-rack Resource Disaggregation in HPC, 2022, ACM Transactions on Architecture and Code Optimization
  • PINE: Photonic Integrated Networked Energy efficient datacenters (ENLITENED Program) [Invited], 2020, Journal of Optical Communications and Networking
  • Temporal Computing With Superconductors, 2021, IEEE Micro
  • Peta-Scale Embedded Photonics Architecture for Distributed Deep Learning Applications, 2023, Journal of Lightwave Technology

Frequent co-authors who have collaborated with John Shalf include:

  • George Michelogiannakis
  • Keren Bergman
  • Madeleine Glick
  • Larry Dennison
  • Anastasiia Butko

Best Publications

  • The Landscape of Parallel Computing Research: A View from Berkeley

    Krste Asanovic;Ras Bodik;Bryan Christopher Catanzaro;Joseph James Gebis

  • Optimization of sparse matrix-vector multiplication on emerging multicore platforms

    Samuel Williams;Leonid Oliker;Richard Vuduc;John Shalf

  • Optimization of sparse matrix-vector multiplication on emerging multicore platforms

    Samuel Williams;Leonid Oliker;Richard Vuduc;John Shalf

  • The International Exascale Software Project roadmap

    Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts

  • Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud

    Keith R. Jackson;Lavanya Ramakrishnan;Krishna Muriki;Shane Canon

  • Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures

    Kaushik Datta;Mark Murphy;Vasily Volkov;Samuel Williams

  • Exascale computing technology challenges

    John Shalf;Sudip Dosanjh;John Morrison

  • The potential of the cell processor for scientific computing

    Samuel Williams;John Shalf;Leonid Oliker;Shoaib Kamil

  • The future of computing beyond Moore's Law.

    John Shalf

  • The cactus framework and toolkit: design and applications

    Tom Goodale;Gabrielle Allen;Gerd Lanfermann;Joan Massó

  • Memory Errors in Modern Systems: The Good, The Bad, and The Ugly

    Vilas Sridharan;Nathan DeBardeleben;Sean Blanchard;Kurt B. Ferreira

  • Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors

    Kaushik Datta;Shoaib Kamil;Samuel Williams;Leonid Oliker

  • The Cactus framework and toolkit: Design and applications

    Tom Goodale;Gabrielle Allen;Gerd Lanfermann;Joan Masso

  • An auto-tuning framework for parallel multicore stencil computations

    Shoaib Kamil;Cy Chan;Leonid Oliker;John Shalf

  • The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Environment

    Gabrielle Allen;David Angulo;Ian Foster;Gerd Lanfermann

  • Computing beyond Moore's Law

    John M. Shalf;Robert Leland

  • Enabling Applications on the Grid: A Gridlab Overview

    Gabrielle Allen;Tom Goodale;Thomas Radke;Michael Russell

  • DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges

    Robert Lucas;James Ang;Keren Bergman;Shekhar Borkar

  • Implicit and explicit optimizations for stencil computations

    Shoaib Kamil;Kaushik Datta;Samuel Williams;Leonid Oliker

  • Using IOR to analyze the I/O Performance for HPC Platforms

    Hongzhang Shan;John Shalf

Frequent Co-Authors

Leonid Oliker
Leonid Oliker Lawrence Berkeley National Laboratory
Samuel Williams
Samuel Williams Lawrence Berkeley National Laboratory
Katherine Yelick
Katherine Yelick University of California, Berkeley
Shoaib Kamil
Shoaib Kamil Adobe Systems (United States)
Edward Seidel
Edward Seidel University of Wyoming
Keren Bergman
Keren Bergman Columbia University
Kurt Stockinger
Kurt Stockinger Zurich University of Applied Sciences
Mahmut Kandemir
Mahmut Kandemir Pennsylvania State University
Bernd Hamann
Bernd Hamann University of California, Davis
Michael F. Wehner
Michael F. Wehner Lawrence Berkeley National Laboratory

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