Abstract
The amount of data generated by numerical simulations in various scientific domains led to a fundamental redesign of how the analysis and visualization of simulation outputs are performed. The throughput and capacity of storage subsystems have not evolved as fast as the computing power in extreme-scale supercomputers, making the classical post-hoc approach highly inefficient. In situ processing has then emerged as a solution in which simulation and data analysis/visualization are intertwined for better performance and greater interactivity. Determining the best allocation, i.e., how many resources to allocate to simulation and analysis respectively, mapping, i.e., where and at which frequency to run the analysis/visualization, and data transfer mode is a complex task whose performance assessment is crucial to the efficient execution of in situ processing. However, such a performance evaluation of different strategies usually relies either on directly running them on the targeted execution environments, which can rapidly become extremely time- and resource-consuming, or on resorting to simplified models of the components of an in situ application, which can lack of realism. In both cases, the validity of the performance evaluation is limited. In this paper, we present SIM-SITU, a framework for the faithful performance evaluation of in situ processing strategies. We designed SIM-SITU to reflect the typical features of in situ processing systems. Thanks to its modular design, Sim-Situ has the necessary flexibility to easily and faithfully evaluate the behavior and performance of various allocation, mapping, and data transfer strategies. We illustrate the capabilities of SIM-SITU on a Molecular Dynamics use case. We study the impact of different strategies on performance and show how users can leverage SIM-SITU to determine interesting tradeoffs when adding analysis/visualization components to their application.
Original language | English |
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Title of host publication | Proceedings - 2022 IEEE 18th International Conference on e-Science, eScience 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 182-191 |
Number of pages | 10 |
ISBN (Electronic) | 9781665461245 |
DOIs | |
State | Published - 2022 |
Event | 18th IEEE International Conference on e-Science, eScience 2022 - Salt Lake City, United States Duration: Oct 10 2022 → Oct 14 2022 |
Publication series
Name | Proceedings - 2022 IEEE 18th International Conference on e-Science, eScience 2022 |
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Conference
Conference | 18th IEEE International Conference on e-Science, eScience 2022 |
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Country/Territory | United States |
City | Salt Lake City |
Period | 10/10/22 → 10/14/22 |
Funding
This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a non-exclusive, paid up, irrevocable, world-wide license to publish or reproduce the published form of the manuscript, or allow others to do so, for U.S. Government purposes. The DOE will provide public access to these results in accordance with the DOE Public Access Plan (http://energy.gov/ downloads/doe-public-access-plan). Experiments presented in this paper were carried out using the Grid'5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations (see https://www.grid5000. fr). This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. out using the Grid’5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations (see https://www.grid5000. fr). This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.