Viktor Rosenfeld

Research associate at the Database Systems and Information Management group at the Technische Universität Berlin.

My research interests are data management on modern hardware, focusing on heterogeneous CPU/GPU systems; data processing with user-defined functions, focusing on integrating JVM-based and native programming languages; adaptive query execution and auto-tuning techniques.

Recently, I successfully defended my PhD thesis at TU Berlin under the supervision of Volker Markl, where I also collaborated with Sebastian Breß, Steffen Zeuch, and Tilmann Rabl. During my PhD studies, I was fortunate to work at IBM Research Almaden as a student intern, under the mentorship of Pınar Tözün, Rene Mueller, and Fatma Özcan. Before, I received my Diplom-Informatik degree from Humboldt University Berlin, under the supervision of Ulf Leser.

Contact

viktor.rosenfeld@tu-berlin.de

Technische Universität Berlin
Building EN, Room 721
Einsteinufer 17
10587 Berlin, Germany

Publications

DEBS 2024
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Using and Enhancing NebulaStream – A Tutorial. Steffen Zeuch, Ankit Chaudhary, Viktor Rosenfeld, Taha Tekdogan, Adrian Michalke, Matthis Gördel, Ariane Ziehn, and Volker Markl. 2024. In The 18th ACM International Conference on Distributed and Event-based Systems (DEBS ’24), June 24–28, 2024, Villeurbanne, France.

PhD thesis
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Query Processing on Heterogeneous Systems (draft). Viktor Rosenfeld. 2023. Technische Universität Berlin.

ACM CSUR 2022
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Query Processing on Heterogeneous CPU/GPU Systems. Viktor Rosenfeld, Sebastian Breß, and Volker Markl. 2022. In ACM Comput. Surv. 55, 1, Article 11 (January 2023).

DATE 2020
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Efficient Compilation and Execution of JVM-Based Data Processing Frameworks on Heterogeneous Co-Processors. C. Kotselidis, I. Komnios, O. Akrivopoulos, S. Bress, K. Doka, H. Mohammed, G. Mylonas, V. Spitadakis, D. Strimpel, J. Fumero, F. S. Zakkak, M. Papadimitriou, M. Xekalaki, N. Foutris, A. Stratikopoulos, N. Koziris, I. Konstantinou, I. Mytilinis, C. Bitsakos, C. Tsalidis, C. Tselios, N. Kanakis, C. Lutz, V. Rosenfeld, and V. Markl. 2020. 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), Grenoble, France, 2020, pp. 175-179.

DaMoN 2019
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Performance Analysis and Automatic Tuning of Hash Aggregation on GPUs. Viktor Rosenfeld, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, and Volker Markl. 2019. In Proceedings of the 15th International Workshop on Data Management on New Hardware (DaMoN'19). Association for Computing Machinery, New York, NY, USA, Article 8, 1–11.

EDBT 2018
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Efficient SIMD Vectorization for Hashing in OpenCL. Tobias Behrens, Viktor Rosenfeld, Jonas Traub, Sebastian Breß, and Volker Markl. 2018. Proceedings of the 21st International Conference on Extending Database Technology, EDBT 2018, Vienna, Austria, March 26-29.

SoCC 2017
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Processing Java UDFs in a C++ environment. Viktor Rosenfeld, Rene Mueller, Pinar Tözün, and Fatma Özcan. 2017. In Proceedings of the 2017 Symposium on Cloud Computing (SoCC '17). Association for Computing Machinery, New York, NY, USA, 419–431.

ADMS 2015
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The Operator Variant Selection Problem on Heterogeneous Hardware. Viktor Rosenfeld, Max Heimel, Christoph Viebig, and, Volker Markl. 2015. In the Proceedings of the Sixth International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures.

Diplom thesis
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A Linguistic Query Language On Top Of A Column-Oriented Main-Memory Database. Viktor Rosenfeld. 2012. Humboldt-Universität zu Berlin.

Student project
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An Implementation Of The Annis 2 Query Language. Viktor Rosenfeld. 2010. Humboldt-Universität zu Berlin.

DGfS 2009
 Poster  BibTeX

Search and visualization of richly annotated corpora with ANNIS2. Christian Chiarcos, Thomas Krause, Anke Lüdeling, Julia Ritz, Viktor Rosenfeld, Manfred Stede, Amir Zeldes, and Florian Zipser. 2009. In 31. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft (Poster).

Scientific Community Service

• PC member: ADMS 2022. ADMS 2016.
• External reviewer: VLDB 2022.

Thesis supervision

• Daniel Castro. Execution of User-Defined Functions Across Programming Language Boundaries in Data Processing Systems. Master thesis. 2023.
• Christoph Schulte. Modeling Memory Contention on GPUs. Master thesis. 2021.
• Bhavesh Kumar. Machine Learning Based Automatic Tuning of Hash Aggregation on GPUs. Master thesis. 2020.
• Christoph Schulte. Modeling Memory Contention on GPUs. Master thesis. 2016.
• Larissa Granowsky. Laufzeitanalyse von daten-parallelen Systemen auf Multicore-Prozessoren im Vergleich zu serieller Implementierung. Bachelor thesis. 2016.