Pruners: Providing reproducibility for uncovering non-deterministic errors in runs on supercomputers
Pruners: Providing reproducibility for uncovering non-deterministic errors in runs on supercomputers
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Pruners：提供可重现性，以发现超级计算机上运行中的非确定性错误
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
D. Ahn
中科院分区：
文献类型：
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作者：
Kento Sato;I. Laguna;Gregory L. Lee;M. Schulz;C. Chambreau;Simone Atzeni;Michael Bentley;G. Gopalakrishnan;Zvonimir Rakamaric;G. Sawaya;Joachim Protze;D. Ahn
大型科学模拟必须能够实现超级计算机的全系统潜力。然而，当它们利用高性能特性时，可能会在程序执行中引入一种称为非确定性的现象，这会严重阻碍应用程序的开发。剪枝器是一个新的工具集，用于检测和修复大型并行应用程序中的非确定性错误和错误。为了展示修剪器在大型应用程序开发中的功能，我们还展示了它们在实际生产应用程序中的早期使用。
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.