World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
10958
World Ranking
10475
National Ranking
4382

Overview

Barbara Chapman is affiliated with Stony Brook University in the United States. Their primary research domain is in computer science, with additional contributions to engineering. The main subfields of study include computer networks and communications, hardware and architecture, information systems, artificial intelligence, and electrical and electronic engineering.

Their research covers a broad range of topics, prominently featuring parallel computing and optimization techniques, distributed and parallel computing systems, cloud computing and resource management, advanced data storage technologies, modular robots and swarm intelligence, molecular communication and nanonetworks, and IoT and edge/fog computing.

Barbara Chapman has published extensively, with 71 publications in computer science and 12 in engineering. Frequent publication venues include:

  • arXiv (Cornell University)
  • Parallel Computing
  • 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • Applied Sciences
  • The Journal of Computational Science Education

Recent papers authored or co-authored by Barbara Chapman include:

  • "OpenMP application experiences: Porting to accelerated nodes" (2021), published in Parallel Computing
  • "Co-Designing an OpenMP GPU Runtime and Optimizations for Near-Zero Overhead Execution" (2022), presented at the 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • "Cross-Feature Transfer Learning for Efficient Tensor Program Generation" (2024), published in Applied Sciences
  • "How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits" (2024), available on arXiv (Cornell University)
  • "FreeCompilerCamp.org: Training for OpenMP Compiler Development from Cloud" (2020), published in The Journal of Computational Science Education

Barbara Chapman frequently collaborates with a group of researchers, including Johannes Doerfert, Shilei Tian, Abid M. Malik, Meifeng Lin, and Baodi Shan.

In addition to research papers, Barbara Chapman has contributed to academic literature through book publications. Notably, they authored "Languages and Compilers for Parallel Computing" published by Springer Science+Business Media in 2022.

Best Publications

  • Using OpenMP: Portable Shared Memory Parallel Programming

    Barbara Chapman;Gabriele Jost;Ruud van der Pas

  • Supercompilers for parallel and vector computers

    Hans Zima;Barbara Chapman

  • The International Exascale Software Project roadmap

    Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts

  • Professional CUDA C Programming

    John Cheng;Max Grossman;Ty McKercher;Barbara Chapman

  • Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)

    Barbara Chapman;Gabriele Jost;Ruud van der Pas

  • Programming in Vienna Fortran

    Barbara Chapman;Piyush Mehrotra;Hans Zima

  • Introducing OpenSHMEM: SHMEM for the PGAS community

    Barbara Chapman;Tony Curtis;Swaroop Pophale;Stephen Poole

  • High performance computing using MPI and OpenMP on multi-core parallel systems

    Haoqiang Jin;Dennis Jespersen;Piyush Mehrotra;Rupak Biswas

  • Compiling for distributed-memory systems

    H.P. Zima;B.M. Chapman

  • OpenUH: an optimizing, portable OpenMP compiler

    Chunhua Liao;Oscar R. Hernandez;Barbara M. Chapman;Wenguang Chen

  • Vienna Fortran—a Fortran language extension for distributed memory multiprocessors

    Barbara M. Chapman;Piyush Mehrotra;Hans P. Zima

  • Openmp Shared Memory Parallel Programming

    Matthias S. Mueller;Barbara M. Chapman;Bronis R. de Supinski;Allen D. Malony

  • Early Experiences with the OpenMP Accelerator Model

    Chunhua Liao;Yonghong Yan;Bronis R. de Supinski;Daniel J. Quinlan

  • Vienna Fortran - A Language Specification. Version 1.1

    Hans Zima;Peter Brezany;Barbara Chapman;Piyush Mehrotra

  • Extending HPF for Advanced Data-Parallel Applications

    B. Chapman;H. Zima;P. Mehrotra

  • Vienna-Fortran/HPF extensions for sparse and irregular problems and their compilation

    M. Ujaldon;E.L. Zapata;B.M. Chapman;H.P. Zima

  • Opusc A Coordination Language for Multidisciplinary Applications

    Barbara Chapman;Matthew Haines;Piyush Mehrota;Hans Zima

  • Vienna Fortran 90

    S. Benkner;B.M. Chapman;H.P. Zima

  • Dynamic data distributions in Vienna Fortran

    Barbara Chapman;Hans Moritsch;Piyush Mehrotra;Hans Zima

  • A Software Architecture for Multidisciplinary Applications: Integrating Task and Data Parallelism

    Barbara M. Chapman;Piyush Mehrotra;John Van Rosendale;Hans P. Zima

  • Extreme Heterogeneity 2018 - Productive Computational Science in the Era of Extreme Heterogeneity: Report for DOE ASCR Workshop on Extreme Heterogeneity

    Jeffrey S Vetter;Ron Brightwell;Maya Gokhale;Pat McCormick

Frequent Co-Authors

Bronis R. de Supinski
Bronis R. de Supinski Lawrence Livermore National Laboratory
Allen D. Malony
Allen D. Malony University of Oregon
Weimin Zheng
Weimin Zheng Tsinghua University
Jeffrey S. Vetter
Jeffrey S. Vetter Oak Ridge National Laboratory
Vivek Sarkar
Vivek Sarkar Georgia Institute of Technology
Guang R. Gao
Guang R. Gao University of Delaware
Eduard Ayguadé
Eduard Ayguadé Barcelona Supercomputing Center
Jack Dongarra
Jack Dongarra University of Tennessee at Knoxville
Laurence T. Yang
Laurence T. Yang St. Francis Xavier University
Steven J.M. Jones
Steven J.M. Jones University of British Columbia

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens doors to several allied disciplines and lucrative career opportunities. Many students interested in this field also consider closely related programs available online, often for increased flexibility and affordability.

Those with an interest in engineering can look into an online degree in mechanical engineering or explore the best online electrical engineering programs USA. Both offer strong technical foundations and share core concepts with computer science.

Students fascinated by theory and research may pursue an online bachelor's degree in physics, which can complement skills learned in computer science.

For those targeting rapidly growing industries, the cheapest data science masters in usa can be a strategic pathway. Data science blends analytical and computational skills for diverse career prospects.

Choosing one of these degrees can expand your expertise, enhance your employability, and allow you to specialize in competitive sectors that value computer science knowledge.

Best Scientists Citing Barbara Chapman

Trending Scientists

Recently Published Articles