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.
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