D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 31 Citations 9,702 212 World Ranking 7999 National Ranking 3736

Overview

What is she best known for?

The fields of study she is best known for:

  • Operating system
  • Programming language
  • Central processing unit

The scientist’s investigation covers issues in Parallel computing, Programming language, Fortran, Shared memory and Multi-core processor. Her Parallel computing research incorporates themes from Compiler and Computational science. Her Programming language research is multidisciplinary, relying on both SPMD, Task parallelism and Asynchronous communication.

Barbara Chapman combines subjects such as Uniform memory access and Distributed shared memory with her study of Shared memory. Her Multi-core processor research integrates issues from Node, Petascale computing, Software and Computer architecture. Her biological study spans a wide range of topics, including Interface, Source code, Troubleshooting, Software engineering and Language construct.

Her most cited work include:

  • Using OpenMP: Portable Shared Memory Parallel Programming (769 citations)
  • The International Exascale Software Project roadmap (580 citations)
  • Supercompilers for parallel and vector computers (578 citations)

What are the main themes of her work throughout her whole career to date?

Her primary scientific interests are in Parallel computing, Compiler, Programming paradigm, Programming language and Shared memory. Her Benchmark, Supercomputer, Multi-core processor and CUDA study, which is part of a larger body of work in Parallel computing, is frequently linked to General-purpose computing on graphics processing units, bridging the gap between disciplines. Her Compiler study which covers Thread that intersects with Multiprocessing and CPU cache.

Her Programming paradigm research is multidisciplinary, incorporating perspectives in Computer architecture, Software, Porting and Distributed computing. Her research in Programming language intersects with topics in SPMD and Asynchronous communication. Her study in the field of Distributed memory is also linked to topics like Locality.

She most often published in these fields:

  • Parallel computing (59.65%)
  • Compiler (34.39%)
  • Programming paradigm (32.63%)

What were the highlights of her more recent work (between 2014-2020)?

  • Parallel computing (59.65%)
  • Programming paradigm (32.63%)
  • Compiler (34.39%)

In recent papers she was focusing on the following fields of study:

Barbara Chapman spends much of her time researching Parallel computing, Programming paradigm, Compiler, Distributed computing and Benchmark. In the subject of general Parallel computing, her work in CUDA and Shared memory is often linked to General-purpose computing on graphics processing units, thereby combining diverse domains of study. Her Programming paradigm research incorporates elements of Software, Porting, Directive and Interface.

Her research integrates issues of Supercomputer, Overhead, Memory management, Multi-core processor and Speedup in her study of Compiler. Barbara Chapman has researched Supercomputer in several fields, including Software portability and Software engineering. The concepts of her Distributed computing study are interwoven with issues in Scheduling, Instruction cycle, Scalability and Asynchronous communication.

Between 2014 and 2020, her most popular works were:

  • Extreme Heterogeneity 2018 - Productive Computational Science in the Era of Extreme Heterogeneity: Report for DOE ASCR Workshop on Extreme Heterogeneity (25 citations)
  • Benchmarking and Evaluating Unified Memory for OpenMP GPU Offloading (17 citations)
  • A Comparative Survey of the HPC and Big Data Paradigms: Analysis and Experiments (13 citations)

In her most recent research, the most cited papers focused on:

  • Operating system
  • Programming language
  • Central processing unit

Barbara Chapman focuses on Parallel computing, Compiler, Programming paradigm, Benchmark and Partitioned global address space. In her articles, Barbara Chapman combines various disciplines, including Parallel computing and General-purpose computing on graphics processing units. Her Compiler research is included under the broader classification of Programming language.

The study incorporates disciplines such as Data transmission, Initialization, Directive, Message Passing Interface and Kernel in addition to Programming paradigm. Her research in Benchmark tackles topics such as System software which are related to areas like Uniform memory access. In her research, Distributed computing, Scheme and Fault tolerance is intimately related to Software, which falls under the overarching field of Partitioned global address space.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Using OpenMP: Portable Shared Memory Parallel Programming

Barbara Chapman;Gabriele Jost;Ruud van der Pas.
(2007)

1838 Citations

Supercompilers for parallel and vector computers

Hans Zima;Barbara Chapman.
(1990)

1265 Citations

The International Exascale Software Project roadmap

Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts.
ieee international conference on high performance computing data and analytics (2011)

802 Citations

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

Barbara Chapman;Gabriele Jost;Ruud van der Pas.
(2007)

566 Citations

Professional CUDA C Programming

John Cheng;Max Grossman;Ty McKercher;Barbara Chapman.
(2014)

444 Citations

Programming in Vienna Fortran

Barbara Chapman;Piyush Mehrotra;Hans Zima.
Scientific Programming (1992)

418 Citations

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

Haoqiang Jin;Dennis Jespersen;Piyush Mehrotra;Rupak Biswas.
parallel computing (2011)

245 Citations

Introducing OpenSHMEM: SHMEM for the PGAS community

Barbara Chapman;Tony Curtis;Swaroop Pophale;Stephen Poole.
Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model (2010)

237 Citations

Compiling for distributed-memory systems

H.P. Zima;B.M. Chapman.
Proceedings of the IEEE (1993)

204 Citations

OpenUH: an optimizing, portable OpenMP compiler

Chunhua Liao;Oscar R. Hernandez;Barbara M. Chapman;Wenguang Chen.
Concurrency and Computation: Practice and Experience (2007)

179 Citations

Best Scientists Citing Barbara Chapman

Jack Dongarra

Jack Dongarra

University of Tennessee at Knoxville

Publications: 37

Eduard Ayguadé

Eduard Ayguadé

Barcelona Supercomputing Center

Publications: 30

Jeffrey S. Vetter

Jeffrey S. Vetter

Oak Ridge National Laboratory

Publications: 28

Enrique S. Quintana-Ortí

Enrique S. Quintana-Ortí

Universitat Politècnica de València

Publications: 27

Alok Choudhary

Alok Choudhary

Northwestern University

Publications: 26

Jesús Labarta

Jesús Labarta

Barcelona Supercomputing Center

Publications: 25

David E. Keyes

David E. Keyes

King Abdullah University of Science and Technology

Publications: 21

Ken Kennedy

Ken Kennedy

Rice University

Publications: 20

David Padua

David Padua

University of Illinois at Urbana-Champaign

Publications: 19

Prithviraj Banerjee

Prithviraj Banerjee

Ansys (United States)

Publications: 19

Martin Schulz

Martin Schulz

Technical University of Munich

Publications: 19

Allen D. Malony

Allen D. Malony

University of Oregon

Publications: 19

Xavier Martorell

Xavier Martorell

Barcelona Supercomputing Center

Publications: 19

Joel H. Saltz

Joel H. Saltz

Stony Brook University

Publications: 19

Bronis R. de Supinski

Bronis R. de Supinski

Lawrence Livermore National Laboratory

Publications: 18

Luca Benini

Luca Benini

University of Bologna

Publications: 18

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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