Abstract
This paper concentrates on an OpenMP implementation of the TVD–Hopmoc method with executions performed on Intel® Many Integrated Core and Xeon® Scalable Processor architectures. Specifically, this paper evaluates an improved OpenMP implementation of the TVD–Hopmoc method based on a cluster of points when applied to the convection–diffusion equation in 1–D. Aiming at avoiding fine-grained parallelism employed in a basic OpenMP implementation of the TVD–Hopmoc method, this approach groups variables (located at stencil points) to be calculated simultaneously in parallel instead of calculating them individually. Numerical experiments performed on Intel® Many Integrated Core and Scalable Processor architectures show that the improved OpenMP implementation of the TVD–Hopmoc method based on a cluster of points provides further worthwhile gains when compared both with our previous implementation based only on parallel chunk loops and a basic OpenMP implementation of this method.
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Acknowledgement
The Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), and Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) supported this work. We would like to thank the Núcleo de Computação Científica at Universidade Estadual Paulista (NCC/UNESP) for letting us execute our simulations on its heterogeneous multi-core cluster. These resources were partially funded by Intel® through the projects entitled Intel Parallel Computing Center, Modern Code Partner, and Intel/Unesp Center of Excellence in Machine Learning.
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Cabral, F. et al. (2019). An Improved OpenMP Implementation of the TVD–Hopmoc Method Based on a Cluster of Points. In: Senger, H., et al. High Performance Computing for Computational Science – VECPAR 2018. VECPAR 2018. Lecture Notes in Computer Science(), vol 11333. Springer, Cham. https://doi.org/10.1007/978-3-030-15996-2_10
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DOI: https://doi.org/10.1007/978-3-030-15996-2_10
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