| Analyzing efficient stream processing on modern hardware S Zeuch, BD Monte, J Karimov, C Lutz, M Renz, J Traub, S Breß, T Rabl, ... Proceedings of the VLDB Endowment 12 (5), 516-530, 2019 | 37 | 2019 |
| Generating custom code for efficient query execution on heterogeneous processors S Breß, B Köcher, H Funke, S Zeuch, T Rabl, V Markl The VLDB Journal 27 (6), 797-822, 2018 | 27 | 2018 |
| Adapting tree structures for processing with SIMD instructions S Zeuch, F Huber, J Freytag | 22 | 2014 |
| The NebulaStream Platform: Data and application management for the internet of things S Zeuch, A Chaudhary, B Del Monte, H Gavriilidis, D Giouroukis, ... arXiv preprint arXiv:1910.07867, 2019 | 14 | 2019 |
| Cache-sensitive skip list: Efficient range queries on modern cpus S Sprenger, S Zeuch, U Leser Data Management on New Hardware, 1-17, 2016 | 14 | 2016 |
| Non-invasive progressive optimization for in-memory databases S Zeuch, H Pirk, JC Freytag Proceedings of the VLDB Endowment 9 (14), 1659-1670, 2016 | 11 | 2016 |
| Selection on modern cpus S Zeuch, JC Freytag Proceedings of the 3rd VLDB Workshop on In-Memory Data Mangement and …, 2015 | 8 | 2015 |
| Rhino: Efficient Management of Very Large Distributed State for Stream Processing Engines B Del Monte, S Zeuch, T Rabl, V Markl Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 7 | 2020 |
| Disco: Efficient Distributed Window Aggregation. L Benson, PM Grulich, S Zeuch, V Markl, T Rabl EDBT 20, 423-426, 2020 | 7 | 2020 |
| Grizzly: Efficient Stream Processing Through Adaptive Query Compilation PM Grulich, B Sebastian, S Zeuch, J Traub, J Bleichert, Z Chen, T Rabl, ... Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 6 | 2020 |
| Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects C Lutz, S Breß, S Zeuch, T Rabl, V Markl Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 6 | 2020 |
| Efficient k-means on GPUs C Lutz, S Breß, T Rabl, S Zeuch, V Markl Proceedings of the 14th International Workshop on Data Management on New …, 2018 | 6 | 2018 |
| QTM: modelling query execution with tasks S Zeuch, JC Freytag Proceedings of the VLDB Endowment 7 (14), 2014 | 6 | 2014 |
| Efficient and Scalable k‑Means on GPUs C Lutz, S Breß, T Rabl, S Zeuch, V Markl Datenbank-Spektrum 18 (3), 157-169, 2018 | 3 | 2018 |
| Exploiting automatic vectorization to employ SPMD on SIMD registers S Sprenger, S Zeuch, U Leser 2018 IEEE 34th International Conference on Data Engineering Workshops (ICDEW …, 2018 | 3 | 2018 |
| A Survey of Adaptive Sampling and Filtering Algorithms for the Internet of Things D Giouroukis, A Dadiani, J Traub, S Zeuch, V Markl DEBS'20: 14th ACM International Conference on Distributed and Event-Based …, 2020 | 2 | 2020 |
| Nebulastream: Complex analytics beyond the cloud S Zeuch, ET Zacharatou, S Zhang, X Chatziliadis, A Chaudhary, ... Open Journal of Internet Of Things (OJIOT) 6 (1), 66-81, 2020 | 2 | 2020 |
| Scaling a Public Transport Monitoring System to Internet of Things Infrastructures. H Gavriilidis, A Michalke, L Mons, S Zeuch, V Markl EDBT, 627-630, 2020 | 2 | 2020 |
| Performance Analysis and Automatic Tuning of Hash Aggregation on GPUs V Rosenfeld, S Breß, S Zeuch, T Rabl, V Markl Proceedings of the 15th International Workshop on Data Management on New …, 2019 | 2 | 2019 |
| Governor: Operator Placement for a Unified Fog-Cloud Environment A Chaudhary, S Zeuch, V Markl Fog 6 (F5), F7, 2020 | 1 | 2020 |
