D-Index & Metrics Best Publications

Barbara Chapman

Stony Brook University
United States

D-Index & Metrics 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.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 32 Citations 9,833 291 World Ranking 8882 National Ranking 4078

Overview

What is she best known for?

The fields of study Barbara Chapman is best known for:

Visual cortex
Visual system
Retina

Barbara Chapman carries out multidisciplinary research, doing studies in Neuroscience and Biological neural network. By researching both Biological neural network and Neuroscience, she produces research that crosses academic boundaries. Her work often combines Visual cortex and Cortex (anatomy) studies. Barbara Chapman integrates Cortex (anatomy) and Visual cortex in her research. Striate cortex is closely attributed to Orientation column in her research. Her research on Orientation column frequently connects to adjacent areas such as Striate cortex. Barbara Chapman combines Lateral geniculate nucleus and Binocular neurons in her research. She incorporates Binocular neurons and Receptive field in her research. Barbara Chapman applies her multidisciplinary studies on Receptive field and Visual perception in her research.

Her most cited work include:

Mechanisms Underlying Development of Visual Maps and Receptive Fields (538 citations)
Relation of cortical cell orientation selectivity to alignment of receptive fields of the geniculocortical afferents that arborize within a single orientation column in ferret visual cortex (281 citations)
Development of Orientation Preference Maps in Ferret Primary Visual Cortex (275 citations)

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

Her study on Genetics is often connected to Molecular biology as part of broader study in Gene. Genetics and Gene are two areas of study in which she engages in interdisciplinary research. Barbara Chapman combines Neuroscience and Electrophysiology in her research. She combines Electrophysiology and Neuroscience in her research. Barbara Chapman performs integrative study on Retina and Receptive field in her works. Barbara Chapman merges Receptive field with Visual cortex in her research. Her Ocular dominance research extends to the thematically linked field of Visual cortex. She combines Lateral geniculate nucleus and Visual system in her research. Visual system and Lateral geniculate nucleus are two areas of study in which she engages in interdisciplinary research.

Barbara Chapman most often published in these fields:

Neuroscience (52.38%)
Retina (33.33%)
Lateral geniculate nucleus (30.95%)

What were the highlights of her more recent work (between 2015-2022)?

Programming language (100.00%)
Parallel computing (100.00%)
Operating system (100.00%)

In recent works Barbara Chapman was focusing on the following fields of study:

Barbara Chapman conducts interdisciplinary study in the fields of Programming language and Implementation through her research. In her works, Barbara Chapman conducts interdisciplinary research on Implementation and Programming language. Her research brings together the fields of Intrinsics and Parallel computing. Her research is interdisciplinary, bridging the disciplines of Parallel computing and Intrinsics. Operating system is closely attributed to CUDA in her work. Her CUDA study frequently draws connections to adjacent fields such as Operating system. Barbara Chapman incorporates Compiler and Porting in her studies. As part of her studies on Porting, Barbara Chapman frequently links adjacent subjects like Software. In her articles, Barbara Chapman combines various disciplines, including Software and Compiler.

Between 2015 and 2022, her most popular works were:

Experience Report: Writing a Portable GPU Runtime with OpenMP 5.1 (6 citations)
Concurrent Execution of Deferred OpenMP Target Tasks with Hidden Helper Threads (6 citations)

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)

1883 Citations

Supercompilers for parallel and vector computers

Hans Zima;Barbara Chapman.
(1990)

1292 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)

906 Citations

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

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

565 Citations

Professional CUDA C Programming

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

500 Citations

Programming in Vienna Fortran

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

434 Citations

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

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

262 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)

259 Citations

Compiling for distributed-memory systems

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

214 Citations

OpenUH: an optimizing, portable OpenMP compiler

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

181 Citations

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