A taxonomy of task-based parallel programming technologies for high-performance computing

被引:0
|
作者
Peter Thoman
Kiril Dichev
Thomas Heller
Roman Iakymchuk
Xavier Aguilar
Khalid Hasanov
Philipp Gschwandtner
Pierre Lemarinier
Stefano Markidis
Herbert Jordan
Thomas Fahringer
Kostas Katrinis
Erwin Laure
Dimitrios S. Nikolopoulos
机构
[1] University of Innsbruck,
[2] Queen’s University of Belfast,undefined
[3] University of Erlangen-Nürnberg,undefined
[4] KTH Royal Institute of Technology,undefined
[5] IBM Ireland,undefined
来源
The Journal of Supercomputing | 2018年 / 74卷
关键词
High-performance computing; Task-based parallelism; Taxonomy; API; Runtime system; Scheduler; Monitoring framework; Fault tolerance;
D O I
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中图分类号
学科分类号
摘要
Task-based programming models for shared memory—such as Cilk Plus and OpenMP 3—are well established and documented. However, with the increase in parallel, many-core, and heterogeneous systems, a number of research-driven projects have developed more diversified task-based support, employing various programming and runtime features. Unfortunately, despite the fact that dozens of different task-based systems exist today and are actively used for parallel and high-performance computing (HPC), no comprehensive overview or classification of task-based technologies for HPC exists. In this paper, we provide an initial task-focused taxonomy for HPC technologies, which covers both programming interfaces and runtime mechanisms. We demonstrate the usefulness of our taxonomy by classifying state-of-the-art task-based environments in use today.
引用
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页码:1422 / 1434
页数:12
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