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

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...

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Bibliographic Details
Published in:The Journal of supercomputing 2018-04, Vol.74 (4), p.1422-1434
Main Authors: Thoman, Peter, Dichev, Kiril, Heller, Thomas, Iakymchuk, Roman, Aguilar, Xavier, Hasanov, Khalid, Gschwandtner, Philipp, Lemarinier, Pierre, Markidis, Stefano, Jordan, Herbert, Fahringer, Thomas, Katrinis, Kostas, Laure, Erwin, Nikolopoulos, Dimitrios S.
Format: Article
Language:English
Subjects:
API
Compilers
Computation
Computer memory
Computer Science
Fault tolerance
High-performance computing
Interpreters
Monitoring framework
Parallel programming
Processor Architectures
Programming Languages
Run time (computers)
Runtime system
Scheduler
Servers
Task-based parallelism
Taxonomy
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Summary: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.
ISSN:0920-8542
1573-0484
1573-0484
DOI:10.1007/s11227-018-2238-4