World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
84
Citations
34592
World Ranking
836
National Ranking
452

Electronics and Electrical Engineering

D-Index
73
Citations
30481
World Ranking
737
National Ranking
325

Research.com Recognitions

  • 2016 - ACM Fellow For contributions to power aware computer architecture.
  • 2014 - ACM - IEEE CS Eckert-Mauchly Award For pioneering contributions to low-power computer architecture and its interaction with technology.
  • 1995 - IEEE Fellow For contributions to the design and analysis of high performance processors.

Overview

Trevor Mudge is affiliated with the University of Michigan-Ann Arbor in the United States. Their research primarily focuses on the field of Computer Science with a strong emphasis on Hardware and Architecture. Other subfields of study in their work include Computer Networks and Communications, Electrical and Electronic Engineering, Artificial Intelligence, and Computer Vision and Pattern Recognition.

The main topics covered in Trevor Mudge's research are Parallel Computing and Optimization Techniques, Interconnection Networks and Systems, Embedded Systems Design Techniques, Advanced Graph Neural Networks, Ferroelectric and Negative Capacitance Devices, Advanced Data Storage Technologies, and Caching and Content Delivery.

Trevor Mudge's research output includes multiple papers published in various venues. Recent publications include:

  • "Domain-Specific Architectures: Research Problems and Promising Approaches," 2022, ACM Transactions on Embedded Computing Systems
  • "A 7.3 M Output Non-Zeros/J, 11.7 M Output Non-Zeros/GB Reconfigurable Sparse Matrix-Matrix Multiplication Accelerator," 2020, IEEE Journal of Solid-State Circuits
  • "Demystifying Graph Sparsification Algorithms in Graph Properties Preservation," 2023, Proceedings of the VLDB Endowment
  • "A 507 GMACs/J 256-Core Domain Adaptive Systolic-Array-Processor for Wireless Communication and Linear-Algebra Kernels in 12nm FINFET," 2022, 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
  • "Versa: A 36-Core Systolic Multiprocessor With Dynamically Reconfigurable Interconnect and Memory," 2022, IEEE Journal of Solid-State Circuits

Frequent co-authors in Trevor Mudge's collaborations include Ronald Dreslinski, Haojie Ye, Nishil Talati, Kuan-Yu Chen, and Chaitali Chakrabarti.

Their work has been published repeatedly in venues such as arXiv (Cornell University), IEEE Journal of Solid-State Circuits, Zenodo (CERN European Organization for Nuclear Research), ACM Transactions on Embedded Computing Systems, and the 2022 IEEE International Symposium on Circuits and Systems (ISCAS).

Trevor Mudge has received recognition within the computing community through notable awards. These include being named an ACM Fellow in 2016 for contributions to power aware computer architecture, receiving the ACM - IEEE CS Eckert-Mauchly Award in 2014 for pioneering contributions to low-power computer architecture and its interaction with technology, and being recognized as an IEEE Fellow in 1995 for contributions to the design and analysis of high performance processors.

Best Publications

  • MiBench: A free, commercially representative embedded benchmark suite

    M.R. Guthaus;J.S. Ringenberg;D. Ernst;T.M. Austin

  • Razor: a low-power pipeline based on circuit-level timing speculation

    Dan Ernst;Nam Sung Kim;Shidhartha Das;Sanjay Pant

  • Leakage current: Moore's law meets static power

    N.S. Kim;T. Austin;D. Baauw;T. Mudge

  • Drowsy caches: simple techniques for reducing leakage power

    Krisztián Flautner;Nam Sung Kim;Steve Martin;David Blaauw

  • Near-Threshold Computing: Reclaiming Moore's Law Through Energy Efficient Integrated Circuits

    R.G. Dreslinski;M. Wieckowski;D. Blaauw;D. Sylvester

  • Power: a first-class architectural design constraint

    T. Mudge

  • Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge

    Yiping Kang;Johann Hauswald;Cao Gao;Austin Rovinski

  • Combined dynamic voltage scaling and adaptive body biasing for lower power microprocessors under dynamic workloads

    Steven M. Martin;Krisztian Flautner;Trevor Mudge;David Blaauw

  • Automatic performance setting for dynamic voltage scaling

    Krisztián Flautner;Steve Reinhardt;Trevor Mudge

  • A self-tuning DVS processor using delay-error detection and correction

    S. Das;D. Roberts;Seokwoo Lee;S. Pant

  • Trace-Driven Memory Simulation: A Survey

    Richard Uhlig;Trevor N. Mudge

  • Razor: circuit-level correction of timing errors for low-power operation

    D. Ernst;S. Das;S. Lee;D. Blaauw

  • Disaggregated memory for expansion and sharing in blade servers

    Kevin Lim;Jichuan Chang;Trevor Mudge;Parthasarathy Ranganathan

  • A survey of multicore processors

    G. Blake;R.G. Dreslinski;T. Mudge

  • Improving NAND Flash Based Disk Caches

    Taeho Kgil;David Roberts;Trevor Mudge

  • Recognizing Partially Occluded Parts

    Jerry L. Turney;Trevor N. Mudge;Richard A. Volz

  • Improving data cache performance by pre-executing instructions under a cache miss

    James Dundas;Trevor Mudge

  • Improving code density using compression techniques

    Charles Lefurgy;Peter Bird;I-Cheng Chen;Trevor Mudge

  • The bi-mode branch predictor

    Chih-Chieh Lee;I-Cheng K. Chen;Trevor N. Mudge

  • SODA: A Low-power Architecture For Software Radio

    Yuan Lin;Hyunseok Lee;Mark Woh;Yoav Harel

Frequent Co-Authors

David Blaauw
David Blaauw University of Michigan–Ann Arbor
Ronald G. Dreslinski
Ronald G. Dreslinski University of Michigan–Ann Arbor
Krisztian Flautner
Krisztian Flautner University of Michigan–Ann Arbor
Dennis Sylvester
Dennis Sylvester University of Michigan–Ann Arbor
Scott Mahlke
Scott Mahlke University of Michigan–Ann Arbor
Chaitali Chakrabarti
Chaitali Chakrabarti Arizona State University
Nam Sung Kim
Nam Sung Kim University of Illinois at Urbana-Champaign
Todd Austin
Todd Austin University of Michigan–Ann Arbor
Richard B. Brown
Richard B. Brown University of Utah
Bruce Jacob
Bruce Jacob University of Maryland, College Park

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