Paper
18 November 2024 MPI toolkit: MPI-based performance analysis software for parallel programs
Chen Yang, Guifa Sun, Xiang Cai, Xiguo Xie, Jianpeng Sun
Author Affiliations +
Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134032M (2024) https://doi.org/10.1117/12.3051762
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China
Abstract
Parallel programs often struggle to achieve ideal computational speed and parallel efficiency on parallel computers, with communication overhead considered one of the primary limiting factors. However, existing communication performance analysis tools struggle to meet programmers' needs in terms of practicality and efficiency, making it difficult to analyze performance issues. In order to analyze the MPI communication performance of parallel programs more conveniently and comprehensively, a lightweight and low-overhead communication analysis software MPI Toolkit is designed and implemented, which consists of four modules, namely MPI function tracing, MPI function data statistics, log output, and data visualization, and encapsulates MPI functions based on the PMPI analysis interface to intercept MPI function calls, collect communication data during program operation, output it in the form of a log file, and provide a variety of visual views. To evaluate the effectiveness of the MPI Toolkit, comparative experiments between the MPI Toolkit and the TAU performance analysis tool are performed on typical parallel applications HPL and VASP. The results show that the tracing results of MPI Toolkit are basically the same as those of TAU, and the performance overhead is lower, which can easily and efficiently help users to analyze communication performance and locate potential bottlenecks.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Chen Yang, Guifa Sun, Xiang Cai, Xiguo Xie, and Jianpeng Sun "MPI toolkit: MPI-based performance analysis software for parallel programs", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134032M (18 November 2024); https://doi.org/10.1117/12.3051762
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KEYWORDS
Data communications

Statistical analysis

Visualization

Parallel computing

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