OpenMP taskloop dependences
Visualitza/Obre
10.1007/978-3-030-85262-7_4
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/351494
Tipus de documentText en actes de congrés
Data publicació2021
EditorSpringer
Condicions d'accésAccés obert
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Abstract
Exascale systems will contain multicore/manycore processors with high core count in each node. Therefore, using a model that relaxes the synchronization, such as data-flow, is crucial to adequately exploit the potential of the hardware. The flexibility of the data-flow execution model relies on the dynamic management of data-dependences among tasks.
The OpenMP standard already provides a construct, known as taskloop, that distributes the loop iteration space into several tasks, but this construct does not support the use of the depend clause yet. In this paper we propose the use of the induction variable to define data dependences in tasks created by the taskloop construct. By using the induction variable, each task will contain its own dependences based on the partition of work they received.
We also aim to demonstrate that using taskloop with dependences provides an enhancement in terms of programmability with respect to using stand-alone tasks to parallelize a loop. Our implementation does not introduce any significant overhead on the taskloop implementation and, in certain cases, it outperforms the stand-alone task version.
CitacióMaroñas Bravo, M.; Teruel García, X.; Beltran, V. OpenMP taskloop dependences. A: International Workshop on OpenMP. "OpenMP: Enabling Massive Node-Level Parallelism: 17th International Workshop on OpenMP, IWOMP 2021: Bristol, UK, September 14–16, 2021: proceedings". Springer, 2021, p. 50-64. ISBN 978-3-030-85262-7. DOI 10.1007/978-3-030-85262-7_4.
Forma partPart of the Lecture Notes in Computer Science book series (LNCS, volume 12870)
ISBN978-3-030-85262-7
Versió de l'editorhttps://link.springer.com/chapter/10.1007/978-3-030-85262-7_4
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