Towards task-parallel reductions in OpenMP

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Abstract

Reductions represent a common algorithmic pattern in many scientific applications. OpenMP* has always supported them on parallel and worksharing constructs. OpenMP 3.0’s tasking constructs enable new parallelization opportunities through the annotation of irregular algorithms. Unfortunately the tasking model does not easily allow the expression of concurrent reductions, which limits the general applicability of the programming model to such algorithms. In this work, we present an extension to OpenMP that supports task-parallel reductions on task and taskgroup constructs to improve productivity and programmability. We present specification of the feature and explore issues for programmers and software vendors regarding programming transparency as well as the impact on the current standard with respect to nesting, untied task support and task data dependencies. Our performance evaluation demonstrates comparable results to hand coded task reductions.

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Ciesko, J., Mateo, S., Teruel, X., Martorell, X., Ayguadé, E., Labarta, J., … Eichenberger, A. E. (2015). Towards task-parallel reductions in OpenMP. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9342, pp. 189–201). Springer Verlag. https://doi.org/10.1007/978-3-319-24595-9_14

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