Projecting Performance Data over Simulation Geometry Using SOSflow and ALPINE
| Autor: | Todd Gamblin, Cyrus Harrison, Matthew Larsen, Kevin Huck, Chad Wood, Alfredo Gimenez, Allen D. Malony |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Programming and Performance Visualization Tools ISBN: 9783030178710 ESPT/VPA@SC |
| Popis: | The performance of HPC simulation codes is often tied to their simulated domains; e.g., properties of the input decks, boundaries of the underlying meshes, and parallel decomposition of the simulation space. A variety of research efforts have demonstrated the utility of projecting performance data onto the simulation geometry to enable analysis of these kinds of performance problems. However, current methods to do so are largely ad-hoc and limited in terms of extensibility and scalability. Furthermore, few methods enable this projection online, resulting in large storage and processing requirements for offline analysis. We present a general, extensible, and scalable solution for in-situ (online) visualization of performance data projected onto the underlying geometry of simulation codes. Our solution employs the scalable observation system SOSflow with the in-situ visualization framework ALPINE to automatically extract simulation geometry and stream aggregated performance metrics to respective locations within the geometry at runtime. Our system decouples the resources and mechanisms to collect, aggregate, project, and visualize the resulting data, thus mitigating overhead and enabling online analysis at large scales. Furthermore, our method requires minimal user input and modification of existing code, enabling general and widespread adoption. |
| Databáze: | OpenAIRE |
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