News

19 May 2026

The SIGMOD 2026 PC chairs have awarded me Distinguished PC Member. I'm very honored to receive this recognition!

21 May 2025

Together with Thomas Graves (NVIDIA), I'll be giving a talk at the Databricks Data + AI Summit 2025 in San Francisco. The talk is about "Tracing the Path of a Row Through a GPU-Enabled Query Engine on the Grace Blackwell Architecture", in which you'll get a first glimpse of our new prototype query engine.

Service

VLDB'26

Industrial Track PC Member

SIGMOD'26  Distinguished Reviewer

Research Track PC Member and Industrial Track PC Member

SIGMOD'25

Industrial Track PC Member

ICDE'24  Outstanding Reviewer

Research Track PC Member

Publications

EDBT'25
 Paper  Code

Efficiently Indexing Large Data on GPUs with Fast Interconnects Josef Schmeißer, Clemens Lutz, Volker Markl, in the 28th International Conference on Extending Database Technology, March 25–28, 2025, Barcelona, Spain.

BTW'25
 Short Paper

Scalable Data Management using GPUs with Fast Interconnects — A Brief Overview Clemens Lutz, in Database Systems for Business, Technology and Web, March 3–7, 2025, Bamberg, Germany.

Springer
 Book Chapter

Query Processing on Heterogeneous Hardware Anastasiia Kozar, Janis von Bleichert, Sebastian Breß, Philipp M. Grulich, Clemens Lutz, Tilmann Rabl, Viktor Rosenfeld, Jonas Traub, Steffen Zeuch, Volker Markl, book chapter, Springer, Cham, Switzerland, January 24, 2025.

EDBT'24
 Paper  Code

Benchmarking Stream Join Algorithms on GPUs: A Framework and its Application to the State of the Art Dwi P. A. Nugroho, Philipp M. Grulich, Steffen Zeuch, Clemens Lutz, Stefano Bortoli, Volker Markl, in the 27th International Conference on Extending Database Technology, March 25–28, 2024, Paestum, Italy.

 DBIS Dissertation Award
PhD 2022
 Thesis  Slides

Scalable Data Management using GPUs with Fast Interconnects. Clemens Lutz, PhD thesis, Faculty IV, TU Berlin, Berlin, Germany, November 2022.

SIGMOD'22
 Paper  Code
 YouTube  Slides
 Poster

Triton Join: Efficiently Scaling to a Large Join State 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 12–17, 2022, Philadelphia, PA, USA.

DaMoN'21
 Paper  Code
 Slides

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.

BTW'21
 Best Paper
 Reproducible
 Paper  Slides

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, September 13–17, 2021, Dresden, Germany.

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.

PVLDB'19
 Paper  Code

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.

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.

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.

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.

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

Cooperative Heterogeneous Query Execution. Apostolos Planas, MSc thesis, Faculty IV (EECS), TU Berlin, Berlin, Germany, February 2022

 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