Eugen Betke

• Bull I/O Cooperation

• Automatisches Lernen der Leistungscharakteristika von Paralleler Ein-/Ausgabe, Eugen Betke (Master's Thesis), Advisors: Dr. Julian Kunkel, 2015-06-27, Thesis Presentation BibTeX

• Projekt „Big Data“ (Ansprechpartner: Dr. Julian Kunkel)
• Seminar „Neueste Trends in Big Data Analytics“ (Ansprechpartner: Dr. Julian Kunkel)

• Proseminar „Programmierung in R“ (Ansprechpartner: Dr. Julian Kunkel)

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• Wissenschaftliches Rechnen - Scientific Computing - 2016 (Yevhen Alforov, Eugen Betke, Konstantinos Chasapis, Anna Fuchs, Fabian Große, Nabeeh Jumah, Michael Kuhn, Julian Kunkel, Hermann Lenhart, Jakob Lüttgau, Philipp Neumann, Anastasiia Novikova, Jannek Squar, Thomas Ludwig), Research Group: Scientific Computing, University of Hamburg (Deutsches Klimarechenzentrum GmbH, Bundesstraße 45a, D-20146 Hamburg), 2017-06-19
  BibTeX Publication

• Poster: Using Machine Learning to Predict the Performance of Non-Contiguous I/O (Julian Kunkel, Michaela Zimmer, Eugen Betke), Frankfurt, Germany, 2015-07-13
  BibTeX URL

• Predicting Performance of Non-Contiguous I/O with Machine Learning (Julian Kunkel, Eugen Betke, Michaela Zimmer), In High Performance Computing, 30th International Conference, ISC High Performance 2015, Lecture Notes in Computer Science (9137), pp. 257–273, (Editors: Julian Martin Kunkel, Thomas Ludwig), ISC High Performance, Frankfurt, ISSN: 0302-9743, 2015
  BibTeX

• Predicting Performance of Non-Contiguous I/O with Machine Learning (Julian Kunkel, Eugen Betke, Michaela Zimmer), In Parallel Data Storage Workshop (PDSW), Work in progress session, pp. 43–48, SC14, New Orleans, 2014
  BibTeX URL

• Database VOL-plugin for HDF5, Olga Perevalova (Bachelor's Thesis), Advisors: Dr. Michael Kuhn, Eugen Betke, 2017-07-05, Thesis BibTeX