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The Journal of Supercomputing

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07-10-2023

Improving CUDA performance of an unstructured high-order CFD application under OP2 framework

Authors: Kangjin Huang, Yonggang Che, Chuanfu Xu, Zhe Dai, Jian Zhang

Published in: The Journal of Supercomputing | Issue 5/2024

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Abstract

OP2 is a domain-specific language-based programming framework for unstructured mesh applications. It supports automatic code generation targeting multiple parallel modes, with CUDA included. However, using OP2 to generate efficient CUDA code for real-world applications is a challenging task. This paper reports our efforts optimizing the CUDA code performance when refactoring an unstructured high-order CFD application (namely HOUR2D) based on OP2. A series of novel methods are realized, including utilizing appropriate execution strategies, using local arrays, and optimizing the OP2 data transfer function, etc. Performance evaluation shows that our optimizations significantly improve the performance of the finally generated CUDA code. The overall performance of our optimized OP2-CUDA code is 13.2 times higher than the unoptimized OP2-CUDA code and 2.4 times higher than the manual CUDA code. Meanwhile, these optimizations do not affect the portability of HOUR2D as an OP2 application.

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Title: Improving CUDA performance of an unstructured high-order CFD application under OP2 framework
Authors: Kangjin Huang
Yonggang Che
Chuanfu Xu
Zhe Dai
Jian Zhang
Publication date: 07-10-2023
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 5/2024
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-023-05679-1

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