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Enhancing MPI+OpenMP Task based Applications for Heterogenous Architectures with GPU support

Abstract : Heterogeneous supercomputers are widespread over HPC systems and programming efficient applications on these architectures is a challenge. Task-based programming models are a promising way to tackle this challenge. Since OpenMP 4.0 and 4.5, the target directives enable to offload pieces of code to GPUs and to express it as tasks with dependencies. Therefore, heterogeneous machines can be programmed using MPI+OpenMP(task+target) to exhibit a very high level of concurrent asynchronous operations for which data transfers, kernel executions, communications and CPU computations can be overlapped. Hence, it is possible to suspend tasks performing these asynchronous operations on the CPUs and to overlap their completion with another task execution. Suspended tasks can resume once the associated asynchronous event is completed in an opportunistic way at every scheduling point. We have integrated this feature into the MPC framework and validated it on a AXPY microbenchmark and evaluated on a MPI+OpenMP(tasks) implementation of the LULESH proxy applications. The results show that we are able to improve asynchronism and the overall HPC performance, allowing applications to benefit from asynchronous execution on heterogeneous machines.
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Contributor : Adrien Roussel Connect in order to contact the contributor
Submitted on : Wednesday, August 10, 2022 - 4:44:19 PM
Last modification on : Sunday, August 14, 2022 - 3:21:35 AM


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  • HAL Id : cea-03749364, version 1


Manuel Ferat, Romain Pereira, Adrien Roussel, Patrick Carribault, Luiz Angelo Steffenel, et al.. Enhancing MPI+OpenMP Task based Applications for Heterogenous Architectures with GPU support. IWOMP 2022 - 18th International Workshop on OpenMP, Sep 2022, Chattanooga, United States. pp.1-14. ⟨cea-03749364⟩



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