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P runers : Providing reproducibility for uncovering non-deterministic errors in runs on supercomputers.

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Title: P runers : Providing reproducibility for uncovering non-deterministic errors in runs on supercomputers.
Authors: Sato, Kento1,2 (AUTHOR) kento.sato@riken.jp, Laguna, Ignacio1 (AUTHOR), Lee, Gregory L1 (AUTHOR), Schulz, Martin3 (AUTHOR), Chambreau, Christopher M1 (AUTHOR), Atzeni, Simone4,5 (AUTHOR), Bentley, Michael4 (AUTHOR), Gopalakrishnan, Ganesh4 (AUTHOR), Rakamaric, Zvonimir4 (AUTHOR), Sawaya, Geof6 (AUTHOR), Protze, Joachim7 (AUTHOR), Ahn, Dong H1 (AUTHOR), Mascagni, Michael (AUTHOR)
Source: International Journal of High Performance Computing Applications. Sep2019, Vol. 33 Issue 5, p777-783. 7p.
Subjects: Supercomputers, Debugging, Running, Deterministic algorithms
Abstract: 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. P runers is a new toolset to detect and remedy non-deterministic bugs and errors in large parallel applications. To show the capabilities of P runers for large application development, we also demonstrate their early usage on real-world production applications. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of High Performance Computing Applications is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: P runers : Providing reproducibility for uncovering non-deterministic errors in runs on supercomputers.
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  Data: <searchLink fieldCode="AR" term="%22Sato%2C+Kento%22">Sato, Kento</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> kento.sato@riken.jp</i><br /><searchLink fieldCode="AR" term="%22Laguna%2C+Ignacio%22">Laguna, Ignacio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lee%2C+Gregory+L%22">Lee, Gregory L</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schulz%2C+Martin%22">Schulz, Martin</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chambreau%2C+Christopher+M%22">Chambreau, Christopher M</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Atzeni%2C+Simone%22">Atzeni, Simone</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bentley%2C+Michael%22">Bentley, Michael</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gopalakrishnan%2C+Ganesh%22">Gopalakrishnan, Ganesh</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rakamaric%2C+Zvonimir%22">Rakamaric, Zvonimir</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sawaya%2C+Geof%22">Sawaya, Geof</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Protze%2C+Joachim%22">Protze, Joachim</searchLink><relatesTo>7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ahn%2C+Dong+H%22">Ahn, Dong H</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mascagni%2C+Michael%22">Mascagni, Michael</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+High+Performance+Computing+Applications%22">International Journal of High Performance Computing Applications</searchLink>. Sep2019, Vol. 33 Issue 5, p777-783. 7p.
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  Data: 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. P runers is a new toolset to detect and remedy non-deterministic bugs and errors in large parallel applications. To show the capabilities of P runers for large application development, we also demonstrate their early usage on real-world production applications. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of High Performance Computing Applications is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Running
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