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Main Authors: Loi, Chung Ming, Bockhorst, Heinrich, Weinzierl, Tobias
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2306.16731
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author Loi, Chung Ming
Bockhorst, Heinrich
Weinzierl, Tobias
author_facet Loi, Chung Ming
Bockhorst, Heinrich
Weinzierl, Tobias
contents We discuss three SYCL realisations of a simple Finite Volume scheme over multiple Cartesian patches. The realisation flavours differ in the way how they map the compute steps onto loops and tasks: We compare an implementation that is exclusively using a sequence of for-loops to a version that uses nested parallelism, and finally benchmark these against a version modelling the calculations as task graph. Our work proposes realisation idioms to realise these flavours within SYCL. The results suggest that a mixture of classic task and data parallelism performs if we map this hybrid onto a solely data-parallel SYCL implementation, taking into account SYCL specifics and the problem size.
format Preprint
id arxiv_https___arxiv_org_abs_2306_16731
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle SYCL compute kernels for ExaHyPE
Loi, Chung Ming
Bockhorst, Heinrich
Weinzierl, Tobias
Mathematical Software
Distributed, Parallel, and Cluster Computing
We discuss three SYCL realisations of a simple Finite Volume scheme over multiple Cartesian patches. The realisation flavours differ in the way how they map the compute steps onto loops and tasks: We compare an implementation that is exclusively using a sequence of for-loops to a version that uses nested parallelism, and finally benchmark these against a version modelling the calculations as task graph. Our work proposes realisation idioms to realise these flavours within SYCL. The results suggest that a mixture of classic task and data parallelism performs if we map this hybrid onto a solely data-parallel SYCL implementation, taking into account SYCL specifics and the problem size.
title SYCL compute kernels for ExaHyPE
topic Mathematical Software
Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2306.16731