PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows
| Autor: | Vickie E. Lynch, Jeffrey S. Vetter, Anirban Mandal, Jeremy S. Meredith, Christopher D. Carothers, Ilya Baldin, Brian Tierney, Benjamin Mayer, Rafael Ferreira da Silva, Ewa Deelman, Thomas Proffen, Paul Ruth, Dariusz Król, Gideon Juve, Claris Castillo |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Panorama
Computer science Process (engineering) Testbed 020206 networking & telecommunications 02 engineering and technology Complex calculation Data science Theoretical Computer Science Domain (software engineering) Workflow Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing Software Workflow management system |
| Zdroj: | The International Journal of High Performance Computing Applications. 31:4-18 |
| ISSN: | 1741-2846 1094-3420 |
| DOI: | 10.1177/1094342015594515 |
| Popis: | Computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Thus, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation and data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|