Understanding the Impact of Synchronous, Asynchronous, and Hybrid In-Situ Techniques in Computational Fluid Dynamics Applications
Ju Y, Perez A, Markidis S, Schlatter P, Laure E (2022)
Publication Type: Conference contribution
Publication year: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 295-305
Conference Proceedings Title: Proceedings - 2022 IEEE 18th International Conference on e-Science, eScience 2022
Event location: Salt Lake City, UT, USA
ISBN: 9781665461245
DOI: 10.1109/eScience55777.2022.00043
Abstract
High-Performance Computing (HPC) systems provide input/output (IO) performance growing relatively slowly compared to peak computational performance and have limited storage capacity. Computational Fluid Dynamics (CFD) applications aiming to leverage the full power of Exascale HPC systems, such as the solver Nek5000, will generate massive data for further processing. These data need to be efficiently stored via the IO subsystem. However, limited IO performance and storage capacity may result in performance, and thus scientific discovery, bottlenecks. In comparison to traditional post-processing methods, in-situ techniques can reduce or avoid writing and reading the data through the IO subsystem, promising to be a solution to these problems. In this paper, we study the performance and resource usage of three in-situ use cases: data compression, image generation, and uncertainty quantification. We furthermore analyze three approaches when these in-situ tasks and the simulation are executed synchronously, asynchronously, or in a hybrid manner. In-situ compression can be used to reduce the IO time and storage requirements while maintaining data accuracy. Furthermore, in-situ visualization and analysis can save Terabytes of data from being routed through the IO subsystem to storage. However, the overall efficiency is crucially dependent on the characteristics of both, the in-situ task and the simulation. In some cases, the overhead introduced by the in-situ tasks can be substantial. Therefore, it is essential to choose the proper in-situ approach, synchronous, asynchronous, or hybrid, to minimize overhead and maximize the benefits of concurrent execution.
Authors with CRIS profile
Involved external institutions
Rechenzentrum Garching der Max-Planck-Gesellschaft (MPCDF) / Max Planck Computing & Data Facility
Germany (DE)
Royal Institute of Technology / Kungliga Tekniska Högskolan (KTH)
Sweden (SE)
Germany (DE)
Royal Institute of Technology / Kungliga Tekniska Högskolan (KTH)
Sweden (SE)
How to cite
APA:
Ju, Y., Perez, A., Markidis, S., Schlatter, P., & Laure, E. (2022). Understanding the Impact of Synchronous, Asynchronous, and Hybrid In-Situ Techniques in Computational Fluid Dynamics Applications. In Proceedings - 2022 IEEE 18th International Conference on e-Science, eScience 2022 (pp. 295-305). Salt Lake City, UT, USA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Ju, Yi, et al. "Understanding the Impact of Synchronous, Asynchronous, and Hybrid In-Situ Techniques in Computational Fluid Dynamics Applications." Proceedings of the 18th IEEE International Conference on e-Science, eScience 2022, Salt Lake City, UT, USA Institute of Electrical and Electronics Engineers Inc., 2022. 295-305.
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