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.

Clemens Lutz
+49 30 23895 1855
DIMA
Faculty EECS (IV)
sec. E-N 7
Einsteinufer 17
10587 Berlin
Germany
TU Berlin E-N 739
DFKI G.5.007

News

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.
23 Nov 2020
I gave a talk on Scalable Co-processing using GPUs with Fast Interconnects at the EPFL DIAS Lab.
20 Nov 2020
Our work on Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing has been accepted at BTW'21.
31 Jul 2020
I gave a talk on Processing Large Data on GPUs with Fast Interconnects at the CWI Database Architectures group. The talk is available on  YouTube.
9 Jul 2020
I gave a talk on Processing Large Data on GPUs with Fast Interconnects at Snowflake.
17 Jun 2020
I presented our work on Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects at SIGMOD'20. Check out the talk on  Vimeo and my recording on  YouTube.
20 May 2020
I gave a talk on Processing Large Data on GPUs with Fast Interconnects at the HPI Data Engineering Systems group.
18 May 2020
Our paper on Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects received the SIGMOD Best Paper Award.

Publications

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.

SIGMOD'20  Best Paper  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

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