Developer Technology Engineer at NVIDIA.

My professional 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 successfully achieved my PhD in Computer Science at TU Berlin, where I was mentored by Volker Markl and cooperated with Tilmann Rabl, Sebastian Breß, and Steffen Zeuch.

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.

Clemens Lutz
clutz@nvidia.com
NVIDIA
Europaallee 39
8004 Zurich
Switzerland

News

29 September 2023
Our paper on Benchmarking Stream Join Algorithms on GPUs: A Framework and its Application to the State-of-the-art has been accepted for EDBT 2024! Congratulations to Dwi Nugroho, who led this work.
14 December 2022
My PhD thesis is now published inTU Berlin's institutional repository.
10 November 2022
I successfully defended my PhD on Scalable Data Management using GPUs with Fast Interconnects!
17–21 October 2022
I was kindly invited to hold research talks on my PhD topic Scalable Data Management using GPUs with Fast Interconnects at the EPFL DIAS Lab, the CWI Database Architectures Group, the CompSys Section at VU Amsterdam, and the HPI Data Engineering Systems Group.
15 June 2022
Our Triton join is now published at SIGMOD 2022. Check out our talk on YouTube. We've also released our code on GitHub!

Publications

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, accepted for 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, April 19th - June 21st, 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
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.

Service

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