Meyer M, Kenter T, Plessl C. Multi-FPGA Designs and Scaling of HPC Challenge Benchmarks via MPI and Circuit-Switched Inter-FPGA Networks. ACM Transactions on Reconfigurable Technology and Systems. Published online 2023. doi:10.1145/3576200

Hansmeier T. XCS for Self-Awareness in Autonomous Computing Systems.; 2023.

Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Heinz Nixdorf Institut, Universität Paderborn; 2023. doi:10.17619/UNIPB/1-1797

Hansmeier T, Kenter T, Meyer M, Riebler H, Platzner M, Plessl C. Compute Centers I: Heterogeneous Execution Environments. In: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:165-182. doi:10.5281/zenodo.8068642

Mehlich F. An Evaluation of XCS on the OpenAI Gym. Paderborn University; 2023.

Hansmeier T, Platzner M. Integrating Safety Guarantees into the Learning Classifier System XCS. In: Applications of Evolutionary Computation, EvoApplications 2022, Proceedings. Vol 13224. Lecture Notes in Computer Science. Springer International Publishing; 2022:386-401. doi:10.1007/978-3-031-02462-7_25

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

Ahmed QA. Hardware Trojans in Reconfigurable Computing.10.17619/UNIPB/1-1271__Paderborn University, Paderborn, Germany; 2022. doi:10.17619/UNIPB/1-1271

Kashikar C. A Comparison of Machine Learning Techniques for the On-Line Characterization of Tasks Executed on Heterogeneous Compute Nodes. Paderborn University; 2021.

Brede M. Implementation and Profiling of XCS in the Context of Embedded Systems. Paderborn: Paderborn University; 2021.

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

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

Hansmeier T, Kaufmann P, Platzner M. An Adaption Mechanism for the Error Threshold of XCSF. In: GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery (ACM); 2020:1756-1764. doi:10.1145/3377929.3398106

Hansmeier T, Kaufmann P, Platzner M. Enabling XCSF to Cope with Dynamic Environments via an Adaptive Error Threshold. In: GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York, NY, United States: Association for Computing Machinery (ACM); 2020:125-126. doi:10.1145/3377929.3389968

Karl H, Kundisch D, Meyer auf der Heide F, Wehrheim H. A Case for a New IT Ecosystem: On-The-Fly Computing. Business &; Information Systems Engineering. 2020;62(6):467-481. doi:10.1007/s12599-019-00627-x

Riebler H, Vaz GF, Kenter T, Plessl C. Transparent Acceleration for Heterogeneous Platforms with Compilation to OpenCL. ACM Trans Archit Code Optim (TACO). 2019;16(2):14:1–14:26. doi:10.1145/3319423

Vaz GF. Using Just-in-Time Code Generation to Transparently Accelerate Applications in Heterogeneous Systems. Universität Paderborn; 2019.

Hansmeier T. Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn; 2019.

Riebler H. Efficient Parallel Branch-and-Bound Search on FPGAs Using Work Stealing and Instance-Specific Designs.; 2019. doi:10.17619/UNIPB/1-830

Lösch A, Wiens A, Platzner M. Ampehre: An Open Source Measurement Framework for Heterogeneous Compute Nodes. In: Proceedings of the International Conference on Architecture of Computing Systems (ARCS). Vol 10793. Lecture Notes in Computer Science. Cham: Springer International Publishing; 2018:73-84. doi:10.1007/978-3-319-77610-1_6