Photo Dennis Hoppe

Dennis Hoppe

Head, Service Management & Business Processes

Dennis Hoppe leads the HLRS's strategic development in fields related to artificial intelligence, data analytics, and quantum computing.

As a researcher, Hoppe has contributed to multiple funded research projects exploring cloud computing technologies, applications of high-performance computing and data analytics to address global challenges, and the development of workflows that integrate AI and high-performance computing.

Hoppe holds a master's degree from the Bauhaus-University Weimar in computer science and media.

Publications

[ 2021 ] [ 2020 ] [ 2019 ] [ 2018 ] [ 2017 ] [ 2016 ] [ 2015 ] [ 2012 ] [ 2011 ] [ 2010 ] [ 2008 ]

2021 [ to top ]

  • 1.
    Zhou, N., Georgiou, Y., Pospieszny, M., Zhong, L., Zhou, H., Niethammer, C., Pejak, B., Marko, O., Hoppe, D.: Container Orchestration on HPC Systems through Kubernetes. Journal of Cloud Computing: Advances, Systems and Applications. 10, 1–14 (2021).
     
  • 2.
    Zhou, N., Zhong, L., Hoppe, D., Pejak, B., Marko, O., Cardona, J., Czerkawski, M., Andonovic, I., Michie, C., Tachtatzis, C., Alexakis, E., Mavrepis, P., Kyriazis, D., Pospieszny, M.: CYBELE: A Hybrid Architecture for HPC and Big Data for AI Applications in Agriculture. CRC Press (2021).
     
  • 3.
    Zhong, L., Hoppe, D., Zhou, N., Shcherbakov, O.: Hybrid Workflow of Simulation and Deep Learning on HPC: A Case Study for Material Behavior Determination. 2nd Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S) held in conjunction with IEEE Cluster 2021 (2021).
     
  • 4.
    Hoppe, D.: Trends and Emerging Technologies in AI. In: Resch, M. (Hrsg.) Sustained Simulation Performance 2019 and 2020: Proceedings of the Joint Workshop on Sustained Simulation Performance, University of Stuttgart (HLRS) and Tohoku University, 2019 and 2020. S. 163–181. Springer International Publishing (2021).
     

2020 [ to top ]

  • 1.
    Georgiou, Y., Zhou, N., Zhong, L., Hoppe, D., Pospieszny, M., Papadopoulou, N., Nikas, K., Nikolos, O.L., Kranas, P., Karagiorgou, S., Pascolo, E., Mercier, M., Velho, P.: Converging HPC, Big Data and Cloud technologies for precision agriculture data analytics on supercomputers. Springer LNCS (2020).
     
  • 2.
    Hoppe, D., Zhong, L., Andersson, S., Moise, D.: On the Detection and Interpretation of Performance Variations of HPC Applications. Sustained Simulation Performance 2018 and 2019. S. 41–56. Springer (2020).
     
  • 3.
    Gogolenko, S., Groen, D., Suleimenova, D., Mahmood, I., Lawenda, M., De Santos, F.J.N., Hanley, J., Vuvckovi’c, M., Kr"oll, M., Geiger, B., others: Towards Accurate Simulation of Global Challenges on Data Centers Infrastructures via Coupling of Models and Data Sources. International Conference on Computational Science. S. 410–424. Springer (2020).
     

2019 [ to top ]

  • 1.
    Vingione, G., Scarpino, G., Marzell, L., Pettengell, T., Gialampoukidis, I., Andreadis, S., Vrochidis, S., Kompatsiaris, I., Valentin, B., Gale, L., Lee, W.-K., Lee, W., Gienger, M., Hoppe, D., Sitokonstantinou, V., Papoutsis, I., Kontoes, C., Baruffi, F., Ferri, M., Yoon, H., Karppinen, A., Harri, A.-M.: EOPEN: Open Interoperable Platform for Unified Access and Analysis of Earth Observation Data. Conference on Big Data from Space (BiDS’19), Munich (2019).
     

2018 [ to top ]

  • 1.
    Ahlgren, V., Andersson, S., Brandt, J., Cardo, N., Chunduri, S., Enos, J., Fields, P., Gentile, A., Gerber, R., Greenseid, J., Greiner, A., Hadri, B., He, Y., Hoppe, D., Kaila, U., Klein, K., Kristiansen, A., Leak, S., Mason, M., Pedretti, K., Piccinali, J.-G., Repik, J., Rogers, J., Salminen, S., Showerman, M., Whitney, C., William, J.: Cray System Monitoring: Successes, Requirements, and Priorities. In Proceedings of the Cray User Group 2018, Stockholm (2018).
     
  • 2.
    Ahlgren, V., Andersson, S., Brandt, J., Cardo, N.P., Chunduri, S., Enos, J., Fields, P., Gentile, A., Gerber, R., Gienger, M., Greenseid, J., Greiner, A., Hadri, B., He, Y. (Helen), Hoppe, D., Kaila, U., Kelly, K., Klein, M., Kristiansen, A., Leak, S., Mason, M., Pedretti, K., Piccinali, J.-G., Repik, J., Rogers, J., Salminen, S., Showerman, M., Whitney, C., Williams, J.: Large-Scale System Monitoring Experiences and Recommendations. Workshop on Monitoring and Analysis for High Performance Computing Systems Plus Applications (HPCMASPA ’18), Belfast (2018).
     

2017 [ to top ]

  • 1.
    Hoppe, D., Sandoval, Y., Sulistio, A., Malawski, M., Balis, B., Pawlik, M., Figiela, K., Krol, D., Orzechowski, M., Kitowski, J., Bubak, M.: Bridging the Gap between HPC and Cloud using HyperFlow and PaaSage. Proceedings of the 12th International Conference on Parallel Processing and Applied Mathematics (PPAM) (2017).
     
  • 2.
    Hoppe, D., Gienger, M., Koller, B.: Bringing eScience to the Cloud with PaaSage. Innovatives Supercomputing in Deutschland (InSiDE). Spring Issue, (2017).
     
  • 3.
    Hoppe, D., Shcherbakov, O., Gienger, M., Bönisch, T., Koller, B.: CATALYST: The Next Generation of Big Data Analytics at HLRS. Innovatives Supercomputing in Deutschland (InSiDE). Spring Issue, (2017).
     
  • 4.
    Hoppe, D., Khabi, D., Pi, F., Küster, U., Gienger, M., Koller, B.: EXCESS Project Presents Energy-Aware Software Stack. Innovatives Supercomputing in Deutschland (InSiDE). Spring Issue, (2017).
     
  • 5.
    Vingione, G., Marzell, L., Cadau, E., Gialampoukidis, I., Vrochidis, S., Kompatsiaris, I., Valentin, B., Melcot, M., Gale, L., Lee, W.-K., Jeon, S.-W., Lee, W., Gienger, M., Hoppe, D., Kontoes, C., Papoutsis, I., Ferri, M., Baruffi, F., Yoon, J., Yoon, H., Karppinen, A., Harri, A.-M.: The H2020-EO EOPEN Project. Poster at the Conference on Big Data from Space (BiDS17). , Toulouse (2017).
     
  • 6.
    Hoppe, D., Gienger, M., Bönisch, T., Shcherbakov, O., Moise, D.: Towards Seamless Integration of Data Analytics into Existing HPC Infrastructures. In Proceedings of the Cray User Group (CUG). , Redmond, WA, USA (2017).
     

2016 [ to top ]

  • 1.
    Malawski, M., Balis, B., Figiela, K., Pawlik, M., Bubak, M., Król, D., Słota, R., Orzechowski, M., Kitowski, J., Hoppe, D.: Molecular Dynamics with HyperFlow and Scalarm on the PaaSage Platform. 5th European Conference on Service-Oriented and Cloud Computing (ESOCC). (2016).
     
  • 2.
    Skvortsov, P., Hoppe, D., Tenschert, A., Gienger, M.: Monitoring in the Clouds: Comparison of ECO2Clouds and EXCESS Monitoring Approaches. 2nd International Workshop on Dynamic Resource Allocation and Management in Embedded, High Performance and Cloud Computing (DREAMCloud ’16). (2016).
     

2015 [ to top ]

  • 1.
    Hoppe, D., Sandoval, Y., Gienger, M.: ATOM: A Near-Real Time Monitoring Framework for HPC and Embedded Systems. PODC. Energy Efficient Distributed and Parallel Computing, (2015).
     
  • 2.
    Sandoval, Y., Hoppe, D., Khabi, D., Gienger, M., Kessler, C., Li, L., Dastgeer, U., Ha, P., Umar, I., Tran, V., Gidenstam, A., Tsigas, P., Renaud-Goud, P., Walulya, I.: EXCESS: Execution Models for Energy-Efficient Computing Systems. PODC. Energy Efficient Distributed and Parallel Computing, (2015).
     

2012 [ to top ]

  • 1.
    Stein, B., Gollub, T., Hoppe, D.: Search Result Presentation Based on Faceted Clustering. In: Chen, X., Lebanon, G., Wang, H., und Zaki, M.J. (Hrsg.) 21st ACM International Conference on Information and Knowledge Management (CIKM 12). S. 1940–1944. ACM (2012).
     
  • 2.
    Stein, B., Hoppe, D., Gollub, T.: The Impact of Spelling Errors on Patent Search. In: Daelemans, W. (Hrsg.) 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL 12). S. 570–579. Association for Computational Linguistics (2012).
     
  • 3.
    Gollub, T., Stein, B., Burrows, S., Hoppe, D.: TIRA: Configuring, Executing, and Disseminating Information Retrieval Experiments. In: Tjoa, A.M., Liddle, S., Schewe, K.-D., und Zhou, X. (Hrsg.) 9th International Workshop on Text-based Information Retrieval (TIR 12) at DEXA. S. 151–155. IEEE, Los Alamitos, California (2012).
     

2011 [ to top ]

  • 1.
    Stein, B., Gollub, T., Hoppe, D.: Beyond Precision@10: Clustering the Long Tail of Web Search Results. In: Berendt, B., de Vries, A., Fan, W., Macdonald, C., Ounis, I., und Ruthven, I. (Hrsg.) 20th ACM International Conference on Information and Knowledge Management (CIKM 11). S. 2141–2144. ACM (2011).
     
  • 2.
    Hoppe, D.: Challenges in Patent Retrieval and Mining. In: Cunningham, H., Etzioni, O., Fuhr, N., und Stein, B. (Hrsg.) Proceedings of the Schloss Dagstuhl Seminar on Challenges in Document Mining. S. 81. Leibniz-Zentrum für Informatik, Wadern, Germany (2011).
     

2010 [ to top ]

  • 1.
    Hoppe, D.: Cluster Labeling: Paradigms and ValidationMaster thesisBauhaus-Universität Weimar, Fakultät Medien, Medieninformatik (2010).
     

2008 [ to top ]

  • 1.
    Hoppe, D.: Automatic detection of edit wars in WikipediaMaster thesisBauhaus-Universität Weimar, Fakultät Medien, Medieninformatik (2008).