Dynamic, automated fulfillment of computer-based resource request provisioning using deep reinforcement learning M Ritter, O Hickey-Moriarty, B Yalcin US Patent 11,423,295, 2022 | 22 | 2022 |
Learning cost-effective sampling strategies for empirical performance modeling M Ritter, A Calotoiu, S Rinke, T Reimann, T Hoefler, F Wolf 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020 | 21 | 2020 |
Generating artificial training data for machine-learning M Ritter, O Hickey-Moriarty, B Yalcin US Patent App. 16/046,863, 2020 | 11 | 2020 |
Noise-resilient empirical performance modeling with deep neural networks M Ritter, A Geiß, J Wehrstein, A Calotoiu, T Reimann, T Hoefler, F Wolf 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2021 | 9 | 2021 |
Extrapeak: Advanced automatic performance modeling for HPC applications A Calotoiu, M Copik, T Hoefler, M Ritter, S Shudler, F Wolf Software for Exascale Computing-SPPEXA 2016-2019, 453-482, 2020 | 9 | 2020 |
Conquering noise with hardware counters on hpc systems M Ritter, A Tarraf, A Geiß, N Daoud, B Mohr, F Wolf 2022 IEEE/ACM Workshop on Programming and Performance Visualization Tools …, 2022 | 4 | 2022 |
Low-Latency Real-Time Applications on Heterogeneous MPSoCs N Coppik, P Becker, M Ritter Sixth Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2025 …, 2025 | | 2025 |
Extra-Deep: Automated Empirical Performance Modeling for Distributed Deep Learning M Ritter, F Wolf Proceedings of the SC'23 Workshops of the International Conference on High …, 2023 | | 2023 |
Dynamic, automated fulfillment of computer-based resource request provisioning using deep reinforcement learning M Ritter, O Hickey-Moriarty, B Yalcin US Patent App. 17/859,883, 2022 | | 2022 |
Empirical Modeling of Spatially Diverging Performance A Calotoiu, M Geisenhofer, F Kummer, M Ritter, J Weber, T Hoefler, ... 2020 IEEE/ACM International Workshop on HPC User Support Tools (HUST) and …, 2020 | | 2020 |