| Time series mining at petascale performance A Raoofy, R Karlstetter, D Yang, C Trinitis, M Schulz High Performance Computing: 35th International Conference, ISC High …, 2020 | 9 | 2020 |
| Turning dynamic sensor measurements from gas turbines into insights: a big data approach R Karlstetter, R Widhopf-Fenk, J Hermann, D Rouwenhorst, A Raoofy, ... Turbo Expo: Power for Land, Sea, and Air 58677, V006T05A021, 2019 | 8 | 2019 |
| Living on the Edge: Efficient Handling of Large Scale Sensor Data R Karlstetter, A Raoofy, M Radev, C Trinitis, J Hermann, M Schulz 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet …, 2021 | 6 | 2021 |
| Data mining on vast data sets as a cluster system benchmark A Heinecke, R Karlstetter, D Pflüger, HJ Bungartz Concurrency and Computation: Practice and Experience 28 (7), 2145-2165, 2016 | 6 | 2016 |
| Overcoming Weak Scaling Challenges in Tree-Based Nearest Neighbor Time Series Mining A Raoofy, R Karlstetter, M Schreiber, C Trinitis, M Schulz International Conference on High Performance Computing, 317-338, 2023 | 2 | 2023 |
| Querying Distributed Sensor Streams in the Edge-to-Cloud Continuum R Karlstetter, R Widhopf-Fenk, M Schulz 2022 IEEE International Conference on Edge Computing and Communications …, 2022 | 2 | 2022 |
| An Industrial Sensor Data Processing and Query System RJ Karlstetter Technische Universität München, 2023 | | 2023 |
| Parameter-Optimierung und Parallelisierung eines adaptiven Dünngitter-Regressors für große Datensätze R Karlstetter | | 2013 |
| Eine virtuelle Hierarchische-Basen-h-Version für PDE-Löser auf SIMD Beschleunigerkarten R Karlstetter | | 2011 |
| 2022 IEEE International Conference on Edge Computing and Communications (EDGE)| 978-1-6654-8140-3/22/$31.00© 2022 IEEE| DOI: 10.1109/EDGE55608. 2022.00036 R Aburukba, AR Al-Ali, M Albano, M Al-Naday, Y AlZahrani, A Ba, ... | | |
