World's Best Scientists 2026 revealed!
Michael Karl Gschwind

Michael Karl Gschwind

D-Index & Metrics

Computer Science

D-Index
51
Citations
12013
World Ranking
5285
National Ranking
2433

Overview

Michael Karl Gschwind is affiliated with Facebook in the United States. Their research focuses primarily within the field of Computer Science, with significant attention to various subfields including Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering, Computer Science Applications, and Information Systems.

Their work covers several main topics consistently documented across their publications. These include Green IT and Sustainability, IoT and Edge/Fog Computing, Mobile Crowdsensing and Crowdsourcing, Distributed and Parallel Computing Systems, Web Data Mining and Analysis, Scientific Computing and Data Management, and Machine Learning and Data Classification.

Among recent publications authored or coauthored by Michael Karl Gschwind are:

  • "Sustainable AI: Environmental Implications, Challenges and Opportunities," 2021, arXiv (Cornell University)
  • "First-Generation Inference Accelerator Deployment at Facebook," 2021, arXiv (Cornell University)
  • "ScaDL 2022 Invited Talk 4: Sustainable AI @ Scale: Accelerating AI models for billions of users," 2022, 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
  • "AI: It's All About Inference Now," 2025, Queue

Frequent coauthors in these works include Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, and Newsha Ardalani.

Publication venues where Michael Karl Gschwind has contributed include arXiv (Cornell University), the 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), and Queue. Notably, arXiv features prominently with two publications in recent years.

Best Publications

  • Synergistic Processing in Cell's Multicore Architecture

    M. Gschwind;H.P. Hofstee;B. Flachs;M. Hopkin

  • Multi-petascale highly efficient parallel supercomputer

    Sameh Asaad;Ralph E. Bellofatto;Michael A. Blocksome;Matthias A. Blumrich

  • The IBM Blue Gene/Q Compute Chip

    Ruud A. Haring;Martin Ohmacht;Thomas W. Fox;Michael K. Gschwind

  • Sustainable AI: Environmental Implications, Challenges and Opportunities.

    Carole-Jean Wu;Ramya Raghavendra;Udit Gupta;Bilge Acun

  • Processor implementation having unified scalar and SIMD datapath

    Michael Gschwind;Harm Hofstee;Martin Hopkins

  • Optimizing Compiler for the CELL Processor

    A.E. Eichenberger;K. O'Brien;Peng Wu;Tong Chen

  • Dynamic binary translation and optimization

    K. Ebcioglu;E. Altman;M. Gschwind;S. Sathaye

  • Using advanced compiler technology to exploit the performance of the Cell Broadband Engine TM architecture

    A. E. Eichenberger;J. K. O'Brien;K. M. O'Brien;P. Wu

  • IBM POWER8 processor core microarchitecture

    B. Sinharoy;J. A. Van Norstrand;R. J. Eickemeyer;H. Q. Le

  • Chip multiprocessing and the cell broadband engine

    Michael Gschwind

  • Dynamic and transparent binary translation

    M. Gschwind;E.R. Altman;S. Sathaye;P. Ledak

  • Methods and apparatus for reordering and renaming memory references in a multiprocessor computer system

    Erik Altman;Kemal Ebcioglu;Michael Gschwind;Sumedh Sathaye

  • Optimizing pipelines for power and performance

    Viji Srinivasan;David Brooks;Michael Gschwind;Pradip Bose

  • The cell broadband engine: exploiting multiple levels of parallelism in a chip multiprocessor

    Michael Gschwind

  • New methodology for early-stage, microarchitecture-level power-performance analysis of microprocessors

    D. Brooks;P. Bose;V. Srinivasan;M. K. Gschwind

  • System supporting multiple partitions with differing translation formats

    Michael K. Gschwind

  • Logical partitioning and virtualization in a heterogeneous architecture

    Michael Norman Day;Michael Karl Gschwind;Mark Richard Nutter;James Xenidis

  • Symmetric multi-processing system with attached processing units being able to access a shared memory without being structurally configured with an address translation mechanism

    Erik R. Altman;Peter G. Capek;Michael Gschwind;Harm Peter Hofstee

  • Advances and future challenges in binary translation and optimization

    E.R. Altman;K. Ebcioglu;M. Gschwind;S. Sathaye

  • Multi-Addressable Register File

    Michael K. Gschwind;Brett Olsson

Frequent Co-Authors

Valentina Salapura
Valentina Salapura Google (United States)
Maged M. Michael
Maged M. Michael Facebook (United States)
Alexandre E. Eichenberger
Alexandre E. Eichenberger IBM (United States)
Alan Gara
Alan Gara IBM (United States)
Balaram Sinharoy
Balaram Sinharoy IBM (United States)
David Brooks
David Brooks Harvard University
John A. Gunnels
John A. Gunnels Nvidia (United States)
Pradip Bose
Pradip Bose IBM (United States)
José E. Moreira
José E. Moreira IBM (United States)
Paul W. Coteus
Paul W. Coteus IBM (United States)

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