OpenMP taskloop dependences

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.This research has received funding from the European Union’s Horizon 2020/EuroHPC research and innovation programme under grant agreement No 955606 (DEEP-SEA); and the support of the Spanish Ministry of Science and Innovation (Computacion de Altas Prestaciones VIII: PID2019-107255GB).Peer ReviewedPostprint (author's final draft