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C

Efficient and Scalable k‑Means on GPUs

Clemens Lutz, Sebastian Breß, Tilmann Rabl, Steffen Zeuch, Volker Markl

Datenbank-Spektrum 18(3), 157-169. 2018

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Efficient k-means on GPUs

Clemens Lutz, Sebastian Breß, Tilmann Rabl, Steffen Zeuch, Volker Markl

Proceedings of the 14th International Workshop on Data Management on New Hardware (DAMON '18), 3:1 - 3:3. 2018

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Benchmarking Distributed Data Processing Systems for Machine Learning Workloads

Christoph Boden, Tilmann Rabl, Sebastian Schelter, Volker Markl

TPCTC 2018, 42-57. 2018

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PEEL: A Framework for benchmarking distributed systems and algorithms

Christoph Boden, Alexander Alexandrov, Andreas Kunft, Tilmann Rabl, Volker Markl

Ninth TPC Technology Conference on Performance Evaluation & Benchmarking (TPCTC 2017) @VLDB 2017 2017

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Benchmarking Data Flow Systems for Scalable Machine Learning

Christoph Boden, Andrea Spina, Tilmann Rabl, Volker Markl.

Proceedings of the 4th ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR'17), Jan Hidders (Ed.). ACM, New York, NY, USA, Article 5, 10 pages., 10. 2017

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Distributed Machine Learning - but at what COST?

Christoph Boden, Tilmann Rabl, Volker Markl

ML Systems Workshop@ NIPS2017 2017

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Extracting a Repository of Events and Event References from News Clusters

Akbik Alan Julinda Silvia Boden Christoph

Association for Computational Linguistics, S. 49-53. 2014

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Fault-Tolerance for Distributed Iterative Dataflows in Action

Chen Xu, Rudi Poepsel Lemaitre, Juan Soto, Volker Markl

PVLDB 11(12), 1990-1993. 2018

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B

Special issue: best papers of VLDB 2008

Peter Buneman and Volker Markl and Beng Chin Ooi and Kenneth A. Ross

VLDB J., 1-2. 2010

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Toward Hardware-Sensitive Database Operations

David Broneske and Sebastian Breß and Max Heimel and Gunter Saake

Proc. 17th International Conference on Extending Database Technology (EDBT), Athens, Greece, March 24-28, 2014., 229–234. 2014

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