World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
12618
World Ranking
3853
National Ranking
1824

Research.com Recognitions

  • 2016 - ACM Fellow For contributions to software prefetching and thread-level speculation.
  • 1999 - Fellow of Alfred P. Sloan Foundation

Overview

Todd C. Mowry is affiliated with Carnegie Mellon University in the United States, focusing their research primarily in the field of Computer Science. Their work spans a range of subfields including Computer Vision and Pattern Recognition, Computer Networks and Communications, Hardware and Architecture, Artificial Intelligence, and Computational Mathematics.

The scientist's research addresses several main topics, including:

  • Advanced Neural Network Applications
  • Parallel Computing and Optimization Techniques
  • Tensor decomposition and applications
  • Multimodal Machine Learning Applications
  • Advanced Database Systems and Queries
  • Data Management and Algorithms
  • Distributed systems and fault tolerance

Their recent publications include:

  • Permutable compiled queries, 2020, Proceedings of the VLDB Endowment
  • Cortex: A Compiler for Recursive Deep Learning Models, 2020, arXiv (Cornell University)
  • The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding, 2021, arXiv (Cornell University)
  • The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding, 2022, arXiv (Cornell University)
  • Relax: Composable Abstractions for End-to-End Dynamic Machine Learning, 2023, arXiv (Cornell University)

Frequent venues for publication include arXiv (Cornell University), with multiple papers published there, as well as Proceedings of the VLDB Endowment and IEEE Computer Architecture Letters.

The scientist often collaborates with a group of co-authors who have contributed repeatedly to their work. These frequent collaborators are:

  • Tianqi Chen
  • Pratik Fegade
  • Phillip B. Gibbons
  • Andrew Pavlo
  • Prashanth Menon

Todd C. Mowry has been recognized by professional organizations, including being named an ACM Fellow in 2016 for contributions to software prefetching and thread-level speculation. Additionally, they are a fellow of the Alfred P. Sloan Foundation since 1999.

Best Publications

  • Design and evaluation of a compiler algorithm for prefetching

    Todd C. Mowry;Monica S. Lam;Anoop Gupta

  • Compiler-based prefetching for recursive data structures

    Chi-Keung Luk;Todd C. Mowry

  • A scalable approach to thread-level speculation

    J. Greggory Steffan;Christopher B. Colohan;Antonia Zhai;Todd C. Mowry

  • The potential for using thread-level data speculation to facilitate automatic parallelization

    J.G. Steffan;T.C. Mowry

  • Ambit: in-memory accelerator for bulk bitwise operations using commodity DRAM technology

    Vivek Seshadri;Donghyuk Lee;Thomas Mullins;Hasan Hassan

  • Base-delta-immediate compression: practical data compression for on-chip caches

    Gennady Pekhimenko;Vivek Seshadri;Onur Mutlu;Michael A. Kozuch

  • Programmable matter

    S.C. Goldstein;J.D. Campbell;T.C. Mowry

  • Tolerating latency through software-controlled prefetching in shared-memory multiprocessors

    Todd Mowry;Anoop Gupta

  • RowClone: fast and energy-efficient in-DRAM bulk data copy and initialization

    Vivek Seshadri;Yoongu Kim;Chris Fallin;Donghyuk Lee

  • Reducing Memory and Traffic Requirements for Scalable Directory-Based Cache Coherence Schemes*

    Anoop Gupta;Wolf-Dietrich Weber;Todd C. Mowry

  • Tolerating latency through software-controlled data prefetching

    Todd Carl Mowry

  • Automatic compiler-inserted I/O prefetching for out-of-core applications

    Todd C. Mowry;Angela K. Demke;Orran Krieger

  • Comparative evaluation of latency reducing and tolerating techniques

    Anoop Gupta;John Hennessy;Kourosh Gharachorloo;Todd Mowry

  • Improving hash join performance through prefetching

    Shimin Chen;Anastassia Ailamaki;Phillip B. Gibbons;Todd C. Mowry

  • Scheduling threads for constructive cache sharing on CMPs

    Shimin Chen;Phillip B. Gibbons;Michael Kozuch;Vasileios Liaskovitis

  • Fast Bulk Bitwise AND and OR in DRAM

    Vivek Seshadri;Kevin Hsieh;Amirali Boroumand;Donghyuk Lee

  • Self-Driving Database Management Systems.

    Andrew Pavlo;Gustavo Angulo;Joy Arulraj;Haibin Lin

  • The STAMPede approach to thread-level speculation

    J. Gregory Steffan;Christopher Colohan;Antonia Zhai;Todd C. Mowry

  • Improving index performance through prefetching

    Shimin Chen;Phillip B. Gibbons;Todd C. Mowry

  • Flexible Hardware Acceleration for Instruction-Grain Program Monitoring

    Shimin Chen;Michael Kozuch;Theodoros Strigkos;Babak Falsafi

  • The evicted-address filter: a unified mechanism to address both cache pollution and thrashing

    Vivek Seshadri;Onur Mutlu;Michael A. Kozuch;Todd C. Mowry

Frequent Co-Authors

Phillip B. Gibbons
Phillip B. Gibbons Carnegie Mellon University
Michael Kozuch
Michael Kozuch Intel (United States)
Onur Mutlu
Onur Mutlu ETH Zurich
Gennady Pekhimenko
Gennady Pekhimenko University of Toronto
Seth Copen Goldstein
Seth Copen Goldstein Carnegie Mellon University
Donghyuk Lee
Donghyuk Lee Nvidia (United States)
Babak Falsafi
Babak Falsafi École Polytechnique Fédérale de Lausanne
Bruce M. Maggs
Bruce M. Maggs Duke University
Padmanabhan Pillai
Padmanabhan Pillai Intel (United States)
Anthony Tomasic
Anthony Tomasic Carnegie Mellon University

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