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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).
[ URL ]
 

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).