PhD student and research associate at TU Berlin mentored by Volker Markl and cooperating with Tilmann Rabl and Steffen Zeuch.
My research interests are data management using modern hardware and distributed systems. Currently I am investigating how we can use fast, next-generation interconnects such as NVLink to scale data management on GPUs.
Previously, I worked as a researcher at DFKI. Before starting my PhD studies, I received my MSc degree from ETH Zurich in collaboration with IBM Research, Zurich under supervision of Thomas R. Gross and Animesh Trivedi. My Master's was preceded by an exchange at Imperial College London, where I wrote my BSc thesis under supervision of Peter Pietzuch and Paolo Costa, during my Bachelor's studies at ETH Zurich.
+49 30 314 23515
DIMA
Faculty EECS (IV)
sec. E-N 7
Einsteinufer 17
10587 Berlin
Germany
Faculty EECS (IV)
sec. E-N 7
Einsteinufer 17
10587 Berlin
Germany
TU Berlin E-N 709
News
- 14 Dec 2021
- Our paper on the Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects has been accepted for SIGMOD 2022!
- 21 Jun 2021
- Our short paper on An Energy-Efficient Stream Join for the Internet of Things has been published at DaMoN'21. My congrats to Adrian Michalke!
- 18 Jun 2021
- Our paper on Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects has been awarded the SIGMOD Reproducibility badge. You can see the badge in the ACM DL. Thanks to Apostolos Planas for helping to prepare the reproducibility submission, and to the reviewers for their efforts in reproducing our work!
- 19 Apr 2021
- We have received the BTW Best Paper award for our work on Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing.
- 16 Mar 2021
- Our paper on Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing has been awarded the BTW Reproducibility Badge.
Publications
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SIGMOD'22
- Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl, accepted for the ACM International Conference on Management of Data, June 12–17, 2022, Philadelphia, PA, USA.
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DaMoN'21
Paper - An Energy-Efficient Stream Join for the Internet of Things Adrian Michalke, Philipp M. Grulich, Clemens Lutz, Steffen Zeuch, Volker Markl, in the 17th ACM Int. Workshop on Data Management on New Hardware (DaMoN'21), held online with SIGMOD/PODS, June 21st, 2021.
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BTW'21
Best Paper
Reproducible
Paper - Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing Alexander Kumaigorodski, Clemens Lutz, Volker Markl, in Database Systems for Business, Technology and Web, April 19th - June 21st, 2021, Dresden, Germany.
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SIGMOD'20
Best Paper
Reproducible
Paper Blog
YouTube Slides - Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl, in the ACM International Conference on Management of Data, June 14–19, 2020, Portland, OR, USA.
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PVLDB'19
Paper - Analyzing Efficient Stream Processing on Modern Hardware Steffen Zeuch, Bonaventura Del Monte, Jeyhun Karimov, Clemens Lutz, Manuel Renz, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl, in The Proceedings of the VLDB Endowment, Vol. 12, No. 5, Los Angeles, CA, USA, August 26th-30th, 2019.
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Datenbanken Spektrum
Paper Blog Code - Efficient and Scalable k-Means on GPUs Clemens Lutz, Sebastian Breß, Tilmann Rabl, Steffen Zeuch, Volker Markl, in Datenbanken Spektrum 2018.
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DaMoN'18
Paper Code
Slides Poster - Efficient k-Means on GPUs Clemens Lutz, Sebastian Breß, Tilmann Rabl, Steffen Zeuch, Volker Markl, in the 14th ACM Int. Workshop on Data Management on New Hardware (DaMoN'18), colocated with SIGMOD/PODS, Houston, TX, USA, June 11th, 2018.
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ICDCS'15
Paper - RStore: A Direct-Access DRAM-based Data Store Animesh Trivedi, Patrick Stuedi, Bernard Metzler, Clemens Lutz, Martin Schmatz, Thomas R. Gross, in the 35th IEEE Int. Conf. Distributed Computing Systems (ICDCS'15), Columbus, OH, USA, June 29th - July 2nd, 2015.
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MSc 2014
Thesis - Carafe: High-Performance, In-Memory Graph Processing with RDMA. Clemens Lutz, MSc thesis, D-INFK, ETH Zurich, Zurich, Switzerland, October 2014
Theses & Teaching
Thesis Supervision
- Thesis
- Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing. Alexander Kumaigorodski, MSc thesis, Faculty IV (EECS), TU Berlin, Berlin, Germany, July 2020
- Thesis
- Lock-based Data Structures on GPUs with Independent Thread Scheduling. Phillip Grote, BSc thesis, Faculty IV (EECS), TU Berlin, Berlin, Germany, February 2020
Teaching
- In-Memory Databases On Modern Hardware, SS 2021, TU Berlin
- Database Systems Seminar, SS 2021, TU Berlin
- Big Data Analytics Seminar, WS 2020, TU Berlin
- Big Data Analytics Project, WS 2020, TU Berlin
- Information Systems and Data Analysis, SS 2020, TU Berlin
- In-Memory Databases On Modern Hardware, SS 2020, TU Berlin
- Databases Laboratory, WS 2019, TU Berlin
- Information Systems and Data Analysis, SS 2019, TU Berlin
- In-Memory Databases On Modern Hardware, SS 2019, TU Berlin
- Databases Laboratory, WS 2018, TU Berlin
- Information Systems and Data Analysis, SS 2018, TU Berlin
- Databases Laboratory, WS 2017, TU Berlin
- Information Systems and Data Analysis, SS 2017, TU Berlin
- Databases Laboratory, WS 2016, TU Berlin
- Information Management Seminar, SS 2016, TU Berlin
- Databases Seminar, WS 2015, TU Berlin
- Operating Systems and Networks, SS 2011, ETH Zurich