Issue |
E3S Web Conf.
Volume 548, 2024
X International Conference on Advanced Agritechnologies, Environmental Engineering and Sustainable Development (AGRITECH-X 2024)
|
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Article Number | 03006 | |
Number of page(s) | 12 | |
Section | Information Technologies, Automation Engineering and Digitization of Agriculture | |
DOI | https://doi.org/10.1051/e3sconf/202454803006 | |
Published online | 12 July 2024 |
MPI task mapping for multi-cluster HPC systems
1 Department of Computer Science and Engineering, Saint Petersburg Electrotechnical University “LETI”, ul. Professora Popova 5, Saint Petersburg 197022, Russia
2 Computer Systems Department, Siberian State University of Telecommunications and Information Sciences, ul. Kirova 86, Novosibirsk, 630102, Russia
* Corresponding author: apaznikov@gmail.com
Leveraging graph partitioning techniques is a fundamental framework. This research paper presents an innovative method accompanied by heuristic algorithms designed for the mapping of parallel MPI-programs for hierarchical HPC systems. The proposed approach aims to enhance performance by distributing highly interactive processes to processor cores interconnected through high-speed communication channels. Notably, our method takes into meticulous account all hierarchical layers within the communication network of the HPC systems. Additionally, we offer empirical insights derived from the mapping of MPI programs extracted from the SPEC MPI and NAS Parallel Benchmarks collections into a geographically distributed multi-cluster HPC system.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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