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Paper announcement

OpenMP Taskloop Dependences

Authors

 

  • Marcos Maroñas Bravo (Huawei Edinburgh RC, Programming Languages team)
  • Xavier Teruel
  • Vicenç Beltran

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.

 

International Workshop on OpenMP (IWOMP 2021)OpenMP: Enabling Massive Node-Level Parallelism pp 50-64. DOI: 10.1007/978-3-030-85262-7_4

Open access at https://upcommons.upc.edu/handle/2117/351494 

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