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Real-Time GPU Resource Management with Loadable Kernel Modules.

, , , , and . IEEE Trans. Parallel Distributed Syst., 28 (6): 1715-1727 (2017)

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Anomaly Prediction Based on k-Means Clustering for Memory-Constrained Embedded Devices., , and . ICMLA, page 26-33. IEEE, (2017)LET Paradigm Scheduling Algorithm Considering Parallel Processing on Clustered Many-core Processor., , and . J. Inf. Process., (2022)Deadline Miss Early Detection Method for Mixed Timer-Driven and Event-Driven DAG Tasks., and . IEEE Access, (2023)HRMP3+TECS: Component Framework for Multiprocessor Real-time Operating System with Memory Protection., , , and . ISORC, page 86-96. IEEE, (2023)Exploring the performance of ROS2., , and . EMSOFT, page 5:1-5:10. ACM, (2016)IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink., , , and . ASD@DATE, volume 68 of OASIcs, page 3:1-3:9. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2019)Anomaly Prediction Based on Machine Learning for Memory-Constrained Devices., , and . IEICE Trans. Inf. Syst., 102-D (9): 1797-1807 (2019)Autoware_Perf: A tracing and performance analysis framework for ROS 2 applications., , and . J. Syst. Archit., (2022)Work-in-Progress: Federated and Bundled-Based DAG Scheduling., and . RTSS, page 443-446. IEEE, (2023)Autoware on board: enabling autonomous vehicles with embedded systems., , , , , , , , , and . ICCPS, page 287-296. IEEE Computer Society / ACM, (2018)