Clausing L, Platzner M. ReconO: A Hardware Operating System for Modern Platform FPGAs with 64-Bit Support. In: 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE; 2022:120-127. doi:10.1109/ipdpsw55747.2022.00029

Hansmeier T, Brede M, Platzner M. XCS on Embedded Systems: An Analysis of Execution Profiles and Accelerated Classifier Deletion. In: GECCO ’22: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery (ACM); 2022:2071-2079. doi:10.1145/3520304.3533977

Lienen C, Platzner M. ReconROS Executor: Event-Driven Programming of FPGA-accelerated ROS 2 Applications. Published online 2022.

Lienen C, Platzner M. Task Mapping for Hardware-Accelerated Robotics Applications using ReconROS.

Lienen C, Platzner M. Event-Driven Programming of FPGA-accelerated ROS 2 Robotics Applications. In: 2022 25th Euromicro Conference on Digital System Design (DSD). doi:10.1109/DSD57027.2022.00088

Ahmed QA, Platzner M. On the Detection and Circumvention of Bitstream-Level Trojans in FPGAs. In: IEEE Computer Society Annual Symposium on VLSI (ISVLSI,2022); 2022.

Awais M, Ghasemzadeh Mohammadi H, Platzner M. LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis. In: Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021. ACM; 2021:27-32. doi:https://doi.org/10.1145/3453688.3461506

Awais M, Platzner M. MCTS-Based Synthesis Towards Efficient Approximate Accelerators. In: Proceedings of IEEE Computer Society Annual Symposium on VLSI. IEEE; 2021:384-389.

Witschen LM, Wiersema T, Raeisi Nafchi M, Bockhorn A, Platzner M. Timing Optimization for Virtual FPGA Configurations. In: Hannig F, Derrien S, Diniz P, Chillet D, eds. Proceedings of International Symposium on Applied Reconfigurable Computing (ARC’21). Reconfigurable Computing: Architectures, Tools, and Applications. Springer Lecture Notes in Computer Science. doi:10.1007/978-3-030-79025-7_4

Hansmeier T. Self-aware Operation of Heterogeneous Compute Nodes using the Learning Classifier System XCS. In: HEART ’21: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies. Association for Computing Machinery (ACM); 2021. doi:10.1145/3468044.3468055

Lienen C, Platzner M. Design of Distributed Reconfigurable Robotics Systems with ReconROS. arXiv:210707208. Published online 2021.

Hansmeier T, Platzner M. An Experimental Comparison of Explore/Exploit Strategies for the Learning Classifier System XCS. In: GECCO ’21: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery (ACM); 2021:1639–1647. doi:10.1145/3449726.3463159

Ahmed QA. Hardware Trojans in Reconfigurable Computing. In: 2021 IFIP/IEEE 29th International Conference on Very Large Scale Integration (VLSI-SoC). ; 2021. doi:10.1109/vlsi-soc53125.2021.9606974

Ahmed QA, Wiersema T, Platzner M. Malicious Routing: Circumventing Bitstream-level Verification for FPGAs. In: 2021 Design, Automation &; Test in Europe Conference &; Exhibition (DATE). 2021 Design, Automation and Test in Europe Conference (DATE); 2021. doi:10.23919/DATE51398.2021.9474026

Clausing L. ReconO: High-Performance Embedded Computing for Industrial Analytics on a Reconfigurable System-on-Chip. In: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies. ACM; 2021. doi:10.1145/3468044.3468056

Ghasemzadeh Mohammadi H, Jentzsch F, Kuschel M, et al. FLight: FPGA Acceleration of Lightweight DNN Model Inference in Industrial Analytics. In: https://doi.org/10.1007/978-3-030-93736-2_27__Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Springer; 2021. doi:https://doi.org/10.1007/978-3-030-93736-2_27

Guetttatfi Z, Kaufmann P, Platzner M. Optimal and Greedy Heuristic Approaches for Scheduling and Mapping of Hardware Tasks to Reconfigurable Computing Devices. In: Proceedings of the International Workshop on Applied Reconfigurable Computing (ARC). ; 2020.

Gatica CP, Platzner M. Adaptable Realization of Industrial Analytics Functions on Edge-Devices using Reconfigurable Architectures. In: Machine Learning for Cyber Physical Systems (ML4CPS 2017). Berlin, Heidelberg; 2020. doi:10.1007/978-3-662-59084-3_9

Witschen LM, Wiersema T, Platzner M. Search Space Characterization for AxC Synthesis. Fifth Workshop on Approximate Computing (AxC 2020).

Lienen C, Platzner M, Rinner B. ReconROS: Flexible Hardware Acceleration for RO Applications. In: Proceedings of the 2020 International Conference on Field-Programmable Technology (FPT). ; 2020.