World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
9642
World Ranking
7131
National Ranking
3124

Overview

Scott Klasky is affiliated with Oak Ridge National Laboratory in the United States. Their research is primarily situated within the field of Computer Science with a focus on several subfields including Computer Networks and Communications, Information Systems and Management, Computer Vision and Pattern Recognition, Nuclear and High Energy Physics, and Artificial Intelligence.

The main topics of their work include:

  • Advanced Data Storage Technologies
  • Distributed and Parallel Computing Systems
  • Scientific Computing and Data Management
  • Magnetic Confinement Fusion Research
  • Parallel Computing and Optimization Techniques
  • Algorithms and Data Compression
  • Advanced Data Compression Techniques

Their recent published papers showcase active contributions to computational and data science research. Notable publications include:

  • "ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management," 2020, published in SoftwareX
  • "2022 Review of Data-Driven Plasma Science," 2023, in IEEE Transactions on Plasma Science
  • "A terminology for in situ visualization and analysis systems," 2020, in The International Journal of High Performance Computing Applications
  • "MGARD+: Optimizing Multilevel Methods for Error-Bounded Scientific Data Reduction," 2021, in IEEE Transactions on Computers
  • "Ad Hoc File Systems for High-Performance Computing," 2020, in Journal of Computer Science and Technology

Scott Klasky's scholarly output is frequently published in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Parallel and Distributed Systems
  • SoftwareX
  • The International Journal of High Performance Computing Applications
  • Physics of Plasmas

The scientist has collaborated extensively with other researchers, including frequent coauthors:

  • Norbert Podhorszki
  • David Pugmire
  • Lipeng Wan
  • Matthew Wolf
  • Jieyang Chen

Best Publications

  • Terascale direct numerical simulations of turbulent combustion using S3D

    J. H. Chen;A. Choudhary;B. De Supinski;M. Devries

  • Flexible IO and integration for scientific codes through the adaptable IO system (ADIOS)

    Jay F. Lofstead;Scott Klasky;Karsten Schwan;Norbert Podhorszki

  • DataSpaces: an interaction and coordination framework for coupled simulation workflows

    Ciprian Docan;Manish Parashar;Scott Klasky

  • DataStager: scalable data staging services for petascale applications

    Hasan Abbasi;Matthew Wolf;Greg Eisenhauer;Scott Klasky

  • DataStager: scalable data staging services for petascale applications

    Hasan Abbasi;Matthew Wolf;Greg Eisenhauer;Scott Klasky

  • Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks

    Qing Liu;Jeremy Logan;Yuan Tian;Hasan Abbasi

  • PreDatA – preparatory data analytics on peta-scale machines

    Fang Zheng;Hasan Abbasi;Ciprian Docan;Jay Lofstead

  • Combining in-situ and in-transit processing to enable extreme-scale scientific analysis

    Janine C. Bennett;Hasan Abbasi;Peer-Timo Bremer;Ray Grout

  • Managing Variability in the IO Performance of Petascale Storage Systems

    Jay Lofstead;Fang Zheng;Qing Liu;Scott Klasky

  • Adaptable, metadata rich IO methods for portable high performance IO

    Jay Lofstead;Fang Zheng;Scott Klasky;Karsten Schwan

  • Compressing the incompressible with ISABELA: in-situ reduction of spatio-temporal data

    Sriram Lakshminarasimhan;Neil Shah;Stephane Ethier;Scott Klasky

  • ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management

    William F. Godoy;Norbert Podhorszki;Ruonan Wang;Chuck Atkins

  • In situ methods, infrastructures, and applications on high performance computing platforms

    A. C. Bauer;H. Abbasi;J. Ahrens;H. Childs

  • Spatiotemporal data mining in the era of big spatial data: algorithms and applications

    Ranga Raju Vatsavai;Auroop Ganguly;Varun Chandola;Anthony Stefanidis

  • Scientific Process Automation and Workflow Management

    Bertram Ludäscher;Ilkay Altintas;Shawn Bowers;Julian Cummings

  • Six degrees of scientific data: reading patterns for extreme scale science IO

    Jay Lofstead;Milo Polte;Garth Gibson;Scott Klasky

  • Exploring automatic, online failure recovery for scientific applications at extreme scales

    Marc Gamell;Daniel S. Katz;Hemanth Kolla;Jacqueline Chen

  • Characterizing output bottlenecks in a supercomputer

    Bing Xie;Jeffrey Chase;David Dillow;Oleg Drokin

  • ISABELA for effective in situ compression of scientific data

    Sriram Lakshminarasimhan;Sriram Lakshminarasimhan;Neil Shah;Stéphane Ethier;Seung-Hoe Ku

  • Enabling In-situ Execution of Coupled Scientific Workflow on Multi-core Platform

    Fan Zhang;Ciprian Docan;Manish Parashar;Scott Klasky

  • Scientific Data Analysis.

    Chandrika Kamath;Nikil Wale;George Karypis;Gaurav Pandey

  • Terascale direct numerical simulations of turbulent combustion using S3D.

    Ramanan Sankaran;J. Mellor-Crummy;M. DeVries;Chun Sang Yoo

Frequent Co-Authors

Norbert Podhorszki
Norbert Podhorszki Oak Ridge National Laboratory
Manish Parashar
Manish Parashar University of Utah
Karsten Schwan
Karsten Schwan Georgia Institute of Technology
Nagiza F. Samatova
Nagiza F. Samatova North Carolina State University
Kesheng Wu
Kesheng Wu Lawrence Berkeley National Laboratory
Tahsin Kurc
Tahsin Kurc Stony Brook University
Robert Ross
Robert Ross Argonne National Laboratory
Arie Shoshani
Arie Shoshani Lawrence Berkeley National Laboratory
Mladen A. Vouk
Mladen A. Vouk North Carolina State University
Jacqueline H. Chen
Jacqueline H. Chen Sandia National Laboratories

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