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Hazel Hen – leading HPC technology and its impact on science in Germany and Europe.

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Title: Hazel Hen – leading HPC technology and its impact on science in Germany and Europe.
Authors: Bönisch, Thomas1 boenisch@hlrs.de, Resch, Michael1, Schwitalla, Thomas2, Meinke, Matthias3, Wulfmeyer, Volker2, Warrach-Sagi, Kirsten2
Source: Parallel Computing. May2017, Vol. 64, p3-11. 9p.
Subjects: High performance computing, LINPACK (Computer system), Application software, Computer users, Conjugate gradient methods
Geographic Terms: Germany, Europe
Abstract: The new HLRS flagship system Hazel Hen (a Cray XC40) is Europe's fastest system in the High Performance Conjugate Gradients (HPCG) benchmarking list. Designed to provide maximum sustainable performance to the users of HLRS - ignoring both peak and Linpack performance numbers - it has even climbed to number 8 in the TOP500 list and is one of the fastest systems in the world used both by research and industry. This paper will present insight into the strategy that was at the heart of the HLRS decision. It will further show how Hazel Hen can and has already impacted research and industry by providing high sustained performance for real world applications. In this paper we will show two applications and discuss the industrial uptake of the system. [ABSTRACT FROM AUTHOR]
Copyright of Parallel Computing is the property of Elsevier B.V. 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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Header DbId: egs
DbLabel: Engineering Source
An: 123257231
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Hazel Hen – leading HPC technology and its impact on science in Germany and Europe.
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  Data: <searchLink fieldCode="DE" term="%22High+performance+computing%22">High performance computing</searchLink><br /><searchLink fieldCode="DE" term="%22LINPACK+%28Computer+system%29%22">LINPACK (Computer system)</searchLink><br /><searchLink fieldCode="DE" term="%22Application+software%22">Application software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+users%22">Computer users</searchLink><br /><searchLink fieldCode="DE" term="%22Conjugate+gradient+methods%22">Conjugate gradient methods</searchLink>
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  Data: The new HLRS flagship system Hazel Hen (a Cray XC40) is Europe's fastest system in the High Performance Conjugate Gradients (HPCG) benchmarking list. Designed to provide maximum sustainable performance to the users of HLRS - ignoring both peak and Linpack performance numbers - it has even climbed to number 8 in the TOP500 list and is one of the fastest systems in the world used both by research and industry. This paper will present insight into the strategy that was at the heart of the HLRS decision. It will further show how Hazel Hen can and has already impacted research and industry by providing high sustained performance for real world applications. In this paper we will show two applications and discuss the industrial uptake of the system. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Parallel Computing is the property of Elsevier B.V. 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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        Value: 10.1016/j.parco.2017.02.002
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        Text: English
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              Text: May2017
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