Abstract
In recent years, MPI has been widely used as a communication protocol for massively parallel computing tasks, and the performance of MPI interprocess communications has become a major constraint for large-scale scalability. By analyzing the performance characteristics of bandwidth and latency of MPI communications, a transmission optimization method for MPI communications is proposed. For the variables of transmitted data, the communication strategy of MPI is optimized according to the data size and the succession of multiple communications, and the operation of packing or unpacking is automatically selected, which makes the performance of MPI communications significantly improved. For the time-consuming parts of MPI communication in the ocean numerical model Parallel Ocean Program with this method used, at least 2.4x speedup in point-to-point communication with unpacking strategy and at least 1.7x speedup in point-to-point with packing strategy are achieved. By automating file scans and analysis, 1.6x speedup is achieved for some point-to-point communications.
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Acknowledgements
This work was supported by the National Key Research and Development Program of China, Grant/Award Number: 2016YFB0201100. And R &D and application of key technologies of independent and controllable computing power network, Grant/Award Number: 2022JBZ01-01.
Funding
This work was supported by the National Key Research and Development Program of China, Grant/Award Number: 2016YFB0201100. And R &D and application of key technologies of independent and controllable computing power network, Grant/Award Number: 2022JBZ01-01.
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Author 1 was involved in paper writing, data testing and analysis, scanning module development and design, and data testing. Author 2 helped in software package design and development, as well as POP testing, results and analysis. Author 3 (corresponding author) contributed to overall paper conception, participation in the entire development and testing process.
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Wang, J., Zhuang, Y. & Zeng, Y. A transmission optimization method for MPI communications. J Supercomput 80, 6240–6263 (2024). https://doi.org/10.1007/s11227-023-05699-x
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DOI: https://doi.org/10.1007/s11227-023-05699-x