Paper
19 July 2024 Heterogeneous many-core optimization method for PipeBCGs solver in PETSc on SW26010-pro
Author Affiliations +
Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 1318132 (2024) https://doi.org/10.1117/12.3031092
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China
Abstract
The PETSc (Portable, Extensible Toolkit for Scientific Computation) library is one of the fundamental general-purpose numerical libraries in high-performance computing environments. It is widely employed for solving problems related to partial differential equations, sparse linear algebra, and other related issues. PETSc plays a crucial role in assisting developers in rapidly creating parallel programs, thereby enhancing the computational efficiency of high-performance computing. This paper initially ports the PETSc program onto the SW26010-pro processor. Following that, we choose a representative solver from the KSP module of PETSc. Addressing four hotspot functions invoked by this solver, we implement many-core optimization for its execution under the Sunway heterogeneous architecture. The experimental results show that the maximum speedup on a single node can reach 62.3 after many-core optimizations of core hotspot functions. This indicates that the many-core optimization of hotspot functions for PETSc linear solvers demonstrates excellent parallel efficiency on the Sunway supercomputer.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xinhua Wang, Jingshan Pan, Min Tian, Chaoshuai Xu, Huazeng Liu, and Zhenguo Wei "Heterogeneous many-core optimization method for PipeBCGs solver in PETSc on SW26010-pro", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 1318132 (19 July 2024); https://doi.org/10.1117/12.3031092
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KEYWORDS
Mathematical optimization

Matrices

Data communications

Data modeling

Parallel computing

Linear algebra

Mathematics

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