Effects of mesh loop modes on performance of unstructured finite volume GPU simulations
Abstract In unstructured finite volume method, loop on different mesh components such as cells, faces, nodes, etc is used widely for the traversal of data. Mesh loop results in direct or indirect data access that affects data locality significantly. By loop on mesh, many threads accessing the same d...
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Online Access: | https://doi.org/10.1186/s42774-021-00073-y |
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doaj-10e08d555343458c8f4bc6a103d70b9a2021-07-25T11:47:05ZengSpringerOpenAdvances in Aerodynamics2524-69922021-07-013112310.1186/s42774-021-00073-yEffects of mesh loop modes on performance of unstructured finite volume GPU simulationsYue Weng0Xi Zhang1Xiaohu Guo2Xianwei Zhang3Yutong Lu4Yang Liu5School of Computer Science and Engineering, Sun Yat-sen UniversitySchool of Computer Science and Engineering, Sun Yat-sen UniversityHartree Centre, STFC Daresbury LaboratorySchool of Computer Science and Engineering, Sun Yat-sen UniversitySchool of Computer Science and Engineering, Sun Yat-sen UniversityChina Aerodynamics Research and Development CenterAbstract In unstructured finite volume method, loop on different mesh components such as cells, faces, nodes, etc is used widely for the traversal of data. Mesh loop results in direct or indirect data access that affects data locality significantly. By loop on mesh, many threads accessing the same data lead to data dependence. Both data locality and data dependence play an important part in the performance of GPU simulations. For optimizing a GPU-accelerated unstructured finite volume Computational Fluid Dynamics (CFD) program, the performance of hot spots under different loops on cells, faces, and nodes is evaluated on Nvidia Tesla V100 and K80. Numerical tests under different mesh scales show that the effects of mesh loop modes are different on data locality and data dependence. Specifically, face loop makes the best data locality, so long as access to face data exists in kernels. Cell loop brings the smallest overheads due to non-coalescing data access, when both cell and node data are used in computing without face data. Cell loop owns the best performance in the condition that only indirect access of cell data exists in kernels. Atomic operations reduced the performance of kernels largely in K80, which is not obvious on V100. With the suitable mesh loop mode in all kernels, the overall performance of GPU simulations can be increased by 15%-20%. Finally, the program on a single GPU V100 can achieve maximum 21.7 and average 14.1 speed up compared with 28 MPI tasks on two Intel CPUs Xeon Gold 6132.https://doi.org/10.1186/s42774-021-00073-yGPUCFDFinite volumeUnstructured meshMesh loop modesData locality |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yue Weng Xi Zhang Xiaohu Guo Xianwei Zhang Yutong Lu Yang Liu |
spellingShingle |
Yue Weng Xi Zhang Xiaohu Guo Xianwei Zhang Yutong Lu Yang Liu Effects of mesh loop modes on performance of unstructured finite volume GPU simulations Advances in Aerodynamics GPU CFD Finite volume Unstructured mesh Mesh loop modes Data locality |
author_facet |
Yue Weng Xi Zhang Xiaohu Guo Xianwei Zhang Yutong Lu Yang Liu |
author_sort |
Yue Weng |
title |
Effects of mesh loop modes on performance of unstructured finite volume GPU simulations |
title_short |
Effects of mesh loop modes on performance of unstructured finite volume GPU simulations |
title_full |
Effects of mesh loop modes on performance of unstructured finite volume GPU simulations |
title_fullStr |
Effects of mesh loop modes on performance of unstructured finite volume GPU simulations |
title_full_unstemmed |
Effects of mesh loop modes on performance of unstructured finite volume GPU simulations |
title_sort |
effects of mesh loop modes on performance of unstructured finite volume gpu simulations |
publisher |
SpringerOpen |
series |
Advances in Aerodynamics |
issn |
2524-6992 |
publishDate |
2021-07-01 |
description |
Abstract In unstructured finite volume method, loop on different mesh components such as cells, faces, nodes, etc is used widely for the traversal of data. Mesh loop results in direct or indirect data access that affects data locality significantly. By loop on mesh, many threads accessing the same data lead to data dependence. Both data locality and data dependence play an important part in the performance of GPU simulations. For optimizing a GPU-accelerated unstructured finite volume Computational Fluid Dynamics (CFD) program, the performance of hot spots under different loops on cells, faces, and nodes is evaluated on Nvidia Tesla V100 and K80. Numerical tests under different mesh scales show that the effects of mesh loop modes are different on data locality and data dependence. Specifically, face loop makes the best data locality, so long as access to face data exists in kernels. Cell loop brings the smallest overheads due to non-coalescing data access, when both cell and node data are used in computing without face data. Cell loop owns the best performance in the condition that only indirect access of cell data exists in kernels. Atomic operations reduced the performance of kernels largely in K80, which is not obvious on V100. With the suitable mesh loop mode in all kernels, the overall performance of GPU simulations can be increased by 15%-20%. Finally, the program on a single GPU V100 can achieve maximum 21.7 and average 14.1 speed up compared with 28 MPI tasks on two Intel CPUs Xeon Gold 6132. |
topic |
GPU CFD Finite volume Unstructured mesh Mesh loop modes Data locality |
url |
https://doi.org/10.1186/s42774-021-00073-y |
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