Pruners: Providing reproducibility for uncovering non-deterministic errors in runs on supercomputers
Large scientific simulations must be able to achieve the full-system potential of supercomputers. When they tap into high-performance features, however, a phenomenon known as non-determinism may be introduced in their program execution, which significantly hampers application development. Pruners is...
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| Veröffentlicht in: | The international journal of high performance computing applications 2019-09, Vol.33 (5), p.777-783 |
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| container_title | The international journal of high performance computing applications |
| container_volume | 33 |
| creator | Sato, Kento Laguna, Ignacio Lee, Gregory L Schulz, Martin Chambreau, Christopher M Atzeni, Simone Bentley, Michael Gopalakrishnan, Ganesh Rakamaric, Zvonimir Sawaya, Geof Protze, Joachim Ahn, Dong H |
| description | Large scientific simulations must be able to achieve the full-system potential of supercomputers. When they tap into high-performance features, however, a phenomenon known as non-determinism may be introduced in their program execution, which significantly hampers application development. Pruners is a new toolset to detect and remedy non-deterministic bugs and errors in large parallel applications. To show the capabilities of Pruners for large application development, we also demonstrate their early usage on real-world production applications. |
| doi_str_mv | 10.1177/1094342019834621 |
| format | Article |
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| identifier | ISSN: 1094-3420 |
| ispartof | The international journal of high performance computing applications, 2019-09, Vol.33 (5), p.777-783 |
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| language | eng |
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| source | SAGE Complete; Alma/SFX Local Collection |
| subjects | Pruning Reproducibility Shears Supercomputers |
| title | Pruners: Providing reproducibility for uncovering non-deterministic errors in runs on supercomputers |
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