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    <completedYear/>
    <publishedYear>2017</publishedYear>
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    <language>eng</language>
    <pageFirst>727</pageFirst>
    <pageLast>745</pageLast>
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    <volume>99</volume>
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    <publishedDate>2017-01-10</publishedDate>
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    <title language="eng">The READEX formalism for automatic tuning for energy efficiency</title>
    <abstract language="eng">Energy efficiency is an important aspect of future exascale systems, mainly due to rising energy cost. Although High performance computing (HPC) applications are compute centric, they still exhibit varying computational characteristics in different regions of the program, such as compute-, memory-, and I/O-bound code regions. Some of today’s clusters already offer mechanisms to adjust the system to the resource requirements of an application, e.g., by controlling the CPU frequency. However, manually tuning for improved energy efficiency is a tedious and painstaking task that is often neglected by application developers. The European Union’s Horizon 2020 project READEX (Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing) aims at developing a tools-aided approach for improved energy efficiency of current and future HPC applications. To reach this goal, the READEX project combines technologies from two ends of the compute spectrum, embedded systems and HPC, constituting a split design-time/runtime methodology. From the HPC domain, the Periscope Tuning Framework (PTF) is extended to perform dynamic auto-tuning of fine-grained application regions using the systems scenario methodology, which was originally developed for improving the energy efficiency in embedded systems. This paper introduces the concepts of the READEX project, its envisioned implementation, and preliminary results that demonstrate the feasibility of this approach.</abstract>
    <parentTitle language="eng">Computing</parentTitle>
    <identifier type="doi">10.1007/s00607-016-0532-7</identifier>
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    <author>Joseph Schuchart</author>
    <author>Michael Gerndt</author>
    <author>Per Gunnar Kjeldsberg</author>
    <author>Kai Diethelm</author>
    <author>Michael Lysaght</author>
    <author>David Horák</author>
    <author>Lubomír Říha</author>
    <author>Andreas Gocht</author>
    <author>Mohammed Sourouri</author>
    <author>Madhura Kumaraswamy</author>
    <author>Anamika Chowdhury</author>
    <author>Magnus Jahre</author>
    <author>Othman Bouizi</author>
    <author>Umbreen Sabir Mian</author>
    <author>Jakub Kružík</author>
    <author>Radim Sojka</author>
    <author>Martin Beseda</author>
    <author>Venkatesh Kannan</author>
    <author>Zakaria Bendifallah</author>
    <author>Daniel Hackenberg</author>
    <author>Wolfgang E. Nagel</author>
  </doc>
  <doc>
    <id>3179</id>
    <completedYear/>
    <publishedYear>2012</publishedYear>
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    <language>eng</language>
    <pageFirst>85</pageFirst>
    <pageLast>97</pageLast>
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    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Berlin, Heidelberg</publisherPlace>
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    <title language="eng">Score-P: A Unified Performance Measurement System for Petascale Applications</title>
    <abstract language="eng">The rapidly growing number of cores on modern supercomputers imposes scalability demands not only on applications but also on the software tools needed for their development. At the same time, increasing application and system complexity makes the optimization of parallel codes more difficult, creating a need for scalable performance-analysis technology with advanced functionality. However, delivering such an expensive technology can hardly be accomplished by single tool developers and requires higher degrees of collaboration within the HPC community. The unified performance-measurement system Score-P is a joint effort of several academic performance-tool builders, funded under the BMBF program HPC-Software für skalierbare Parallelrechner in the SILC project (Skalierbare Infrastruktur zur automatischen Leistungsanalyse paralleler Codes). It is being developed with the objective of creating a common basis for several complementary optimization tools in the service of enhanced scalability, improved interoperability, and reduced maintenance cost.</abstract>
    <parentTitle language="eng">Competence in High Performance Computing 2010</parentTitle>
    <identifier type="doi">10.1007/978-3-642-24025-6_8</identifier>
    <identifier type="isbn">978-3-642-24024-9</identifier>
    <identifier type="isbn">978-3-642-24025-6</identifier>
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    <author>Dieter an Mey</author>
    <author>Scott Biersdorf</author>
    <author>Christian Bischof</author>
    <author>Kai Diethelm</author>
    <author>Dominic Eschweiler</author>
    <author>Michael Gerndt</author>
    <author>Andreas Knüpfer</author>
    <author>Daniel Lorenz</author>
    <author>Allen Malony</author>
    <author>Wolfgang E. Nagel</author>
    <author>Yury Oleynik</author>
    <author>Christian Rössel</author>
    <author>Pavel Saviankou</author>
    <author>Dirk Schmidl</author>
    <author>Sameer Shende</author>
    <author>Michael Wagner</author>
    <author>Bert Wesarg</author>
    <author>Felix Wolf</author>
  </doc>
  <doc>
    <id>3183</id>
    <completedYear/>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>79</pageFirst>
    <pageLast>91</pageLast>
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    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Berlin, Heidelberg</publisherPlace>
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    <title language="eng">Score-P: A Joint Performance Measurement Run-Time Infrastructure for Periscope, Scalasca, TAU, and Vampir</title>
    <abstract language="eng">This paper gives an overview about the Score-P performance measurement infrastructure which is being jointly developed by leading HPC performance tools groups. It motivates the advantages of the joint undertaking from both the developer and the user perspectives, and presents the design and components of the newly developed Score-P performance measurement infrastructure. Furthermore, it contains first evaluation results in comparison with existing performance tools and presents an outlook to the long-term cooperative development of the new system.</abstract>
    <parentTitle language="eng">Tools for High Performance Computing 2011</parentTitle>
    <identifier type="doi">10.1007/978-3-642-31476-6_7</identifier>
    <identifier type="isbn">978-3-642-31475-9</identifier>
    <identifier type="isbn">978-3-642-31476-6</identifier>
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    <author>Andreas Knüpfer</author>
    <author>Christian Rössel</author>
    <author>Dieter an Mey</author>
    <author>Kai Diethelm</author>
    <author>Scott Biersdorf</author>
    <author>Dominic Eschweiler</author>
    <author>Markus Geimer</author>
    <author>Michael Gerndt</author>
    <author>Daniel Lorenz</author>
    <author>Allen Malony</author>
    <author>Wolfgang E. Nagel</author>
    <author>Yury Oleynik</author>
    <author>Peter Philippen</author>
    <author>Pavel Saviankou</author>
    <author>Dirk Schmidl</author>
    <author>Sameer Shende</author>
    <author>Ronny Tschüter</author>
    <author>Michael Wagner</author>
    <author>Bert Wesarg</author>
    <author>Felix Wolf</author>
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  <doc>
    <id>3216</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>113</pageFirst>
    <pageLast>126</pageLast>
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    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Cham</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Run-Time Exploitation of Application Dynamism for Energy-Efficient Exascale Computing</title>
    <abstract language="eng">As in the embedded systems domain, energy efficiency has recently become one of the main design criteria in high performance computing. The European Union Horizon 2020 project READEX (Run-time Exploitation of Application Dynamism for Energy-efficient eXascale computing) has developed a tools-aided auto-tuning methodology inspired by system scenario based design. Applying similar concepts as those presented in earlier chapters of this book, the dynamic behavior of HPC applications is exploited to achieve improved energy efficiency and performance. Driven by a consortium of European experts from academia, HPC resource providers, and industry, the READEX project has developed the first generic framework of its kind for split design-time and run-time tuning while targeting heterogeneous systems at the Exascale level. Using a real-life boundary element application, energy savings of more than 30% can be shown.</abstract>
    <parentTitle language="eng">System-Scenario-based Design Principles and Applications</parentTitle>
    <identifier type="doi">10.1007/978-3-030-20343-6_6</identifier>
    <identifier type="isbn">978-3-030-20342-9</identifier>
    <identifier type="isbn">978-3-030-20343-6</identifier>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <author>Per Gunnar Kjeldsberg</author>
    <author>Robert Schöne</author>
    <author>Michael Gerndt</author>
    <author>Kai Diethelm</author>
    <author>Lubomír Říha</author>
    <author>Venkatesh Kannan</author>
    <author>Marie-Christine Sawley</author>
    <author>Jan Zapletal</author>
    <author>Andreas Gocht</author>
    <author>Nico Reissmann</author>
    <author>Ondrei Vysocky</author>
    <author>Madhura Kumaraswamy</author>
    <author>Wolfgang E. Nagel</author>
    <collection role="institutes" number="fang">Fakultät für angewandte Natur- und Geisteswissenschaften</collection>
  </doc>
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