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D-Index & Metrics

Computer Science

D-Index
61
Citations
12649
World Ranking
3118
National Ranking
1516

Research.com Recognitions

  • 2006 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2003 - ACM Fellow For contributions to high-performance computing.

Overview

Daniel A. Reed is affiliated with the University of Utah in the United States. Their primary field of research is computer science, with a focus on subfields such as computer networks and communications, information systems, hardware and architecture, media technology, and transportation.

Their research work covers several main topics, including:

  • Distributed and Parallel Computing Systems
  • Cloud Computing and Resource Management
  • Advanced Data Storage Technologies
  • Parallel Computing and Optimization Techniques
  • Smart Cities and Technologies
  • Human Mobility and Location-Based Analysis
  • Innovative Human-Technology Interaction

Some of their recent papers include:

  • "Reinventing High Performance Computing: Challenges and Opportunities," 2022, arXiv (Cornell University)
  • "HPC Forecast," 2023, Communications of the ACM
  • "Hands-On Computer Science: The Array of Things Experimental Urban Instrument," 2022, Computing in Science & Engineering
  • "High-performance computing at a crossroads," 2025, Science
  • "XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing," 2024, Computing in Science & Engineering

Frequent coauthors in their research include Jack Dongarra, Pete Beckman, Dennis Gannon, Torsten Hoefler, and Marcin Copik.

The venues where they publish most often include:

  • The Shandean.
  • Computing in Science & Engineering
  • arXiv (Cornell University)
  • Communications of the ACM
  • Science

Daniel A. Reed has been recognized with several awards, notably being named an ACM Fellow for contributions to high-performance computing and being elected a Fellow of the American Association for the Advancement of Science (AAAS).

Best Publications

  • The International Exascale Software Project roadmap

    Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts

  • Exascale computing and big data

    Daniel A. Reed;Jack Dongarra

  • The GrADS Project: Software Support for High-Level Grid Application Development

    Francine Berman;Andrew Chien;Keith Cooper;Jack Dongarra

  • Scalable performance analysis: the Pablo performance analysis environment

    D.A. Reed;P.C. Roth;R.A. Aydt;K.A. Shields

  • Autopilot: adaptive control of distributed applications

    R.L. Ribler;J.S. Vetter;H. Simitci;D.A. Reed

  • NCSA's World Wide Web server: design and performance

    T.T. Kwan;R.E. McGrath;D.A. Reed

  • Multicomputer Networks: Message-Based Parallel Processing

    Daniel A. Reed;Richard M. Fujimoto

  • PPFS: a high performance portable parallel file system

    James V. Huber;Andrew A. Chien;Christopher L. Elford;David S. Blumenthal

  • Input/Output Characteristics of Scalable Parallel Applications

    Phyllis E. Crandall;Ruth A. Aydt;Andrew A. Chien;Daniel A. Reed

  • TeraGrid: Analysis of organization, system architecture, and middleware enabling new types of applications

    Charlie Catlett;William E. Allcock;Phil Andrews;Ruth A. Aydt

  • Context-sensitive query enrichment

    Marc E. Davis;Matthew G. Dyor;William Gates;Xuedong Huang

  • New grid scheduling and rescheduling methods in the GrADS project

    F. Berman;H. Casanova;A. Chien;K. Cooper

  • Performance measurement intrusion and perturbation analysis

    Allen D. Malony;Daniel A. Reed;Harry A. J. Wijshoff

  • An Integrated Compilation and Performance Analysis Environment for Data Parallel Programs

    Vikram S. Adve;John Mellor-Crummey;Mark Anderson;Jhy-Chun Wang

  • The Autopilot performance-directed adaptive control system

    Randy L. Ribler;Randy L. Ribler;Huseyin Simitci;Daniel A. Reed

  • Toward a framework for preparing and executing adaptive grid programs

    K. Kennedy;M. Mazina;J. Mellor-Crummey;K. Cooper

  • Service-Oriented Environments for Dynamically Interacting with Mesoscale Weather

    Kelvin K. Droegemeier;Dennis Gannon;Daniel Reed;Beth Plale

  • Automatic ARIMA time series modeling for adaptive I/O prefetching

    N. Tran;D.A. Reed

  • New grid scheduling and rescheduling methods in the GrADS project

    K. Cooper;A. Dasgupta;K. Kennedy;C. Koelbel

  • Performance Contracts: Predicting and Monitoring Grid Application Behavior

    Fredrik Vraalsen;Ruth A. Aydt;Celso L. Mendes;Daniel A. Reed

  • Computational Science: Ensuring America's Competitiveness

    Daniel A. Reed;Ruzena Bajcsy;Manuel A. Fernandez;Jose-Marie Griffiths

Frequent Co-Authors

Roderick A. Hyde
Roderick A. Hyde Lawrence Livermore National Laboratory
Clarence T. Tegreene
Clarence T. Tegreene Microsoft (United States)
Jack Dongarra
Jack Dongarra University of Tennessee at Knoxville
Jordin T. Kare
Jordin T. Kare Microsoft (United States)
Allen D. Malony
Allen D. Malony University of Oregon
Xuedong Huang
Xuedong Huang Microsoft (United States)
Marc Davis
Marc Davis Microsoft (United States)
Edward K. Y. Jung
Edward K. Y. Jung Nortel (Canada)
Mark A. Malamud
Mark A. Malamud Microsoft (United States)
Dennis Gannon
Dennis Gannon Indiana University

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