Cpp-Taskflow: A General-Purpose Parallel Task Programming System at Scale

This article introduces Cpp-Taskflow, a high-performance parallel task programming system, to streamline the building of large and complex parallel applications. Cpp-Taskflow leverages the power of modern C++ and task-based approaches to enable efficient implementations of parallel decomposition str...

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Vydané v:IEEE transactions on computer-aided design of integrated circuits and systems Ročník 40; číslo 8; s. 1687 - 1700
Hlavní autori: Huang, Tsung-Wei, Lin, Yibo, Lin, Chun-Xun, Guo, Guannan, Wong, Martin D. F.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.08.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
C++ languages
Computer-aided design (CAD)
Dynamic control
Heuristic algorithms
Libraries
Parallel processing
parallel programming systems
Programming
Task analysis
task parallelism
Timing
ISSN:0278-0070, 1937-4151
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Shrnutí:This article introduces Cpp-Taskflow, a high-performance parallel task programming system, to streamline the building of large and complex parallel applications. Cpp-Taskflow leverages the power of modern C++ and task-based approaches to enable efficient implementations of parallel decomposition strategies. Our programming model can quickly handle not only traditional loop-level parallelism but also irregular patterns, such as graph algorithms and dynamic control flows. Compared with existing libraries, Cpp-Taskflow is more cost efficient in performance scaling and software integration. We have evaluated Cpp-Taskflow on both micro-benchmarks and large-scale design automation problems of million-scale tasking. In a particular timing analysis workload, Cpp-Taskflow outperformed OpenMP by <inline-formula> <tex-math notation="LaTeX">2\times </tex-math></inline-formula> faster using <inline-formula> <tex-math notation="LaTeX">2\times </tex-math></inline-formula> fewer lines of code. We have also shown Cpp-Taskflow achieved up to 47.81% speed-up with 28.5% less code over the industrial-strength library, Intel Threading Building Blocks, on a detailed placement problem.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0278-0070
1937-4151
DOI:10.1109/TCAD.2020.3025075