M. Lass, T. Kenter, C. Plessl, and M. Brehm, “Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations,”10.3390/e26040322__Entropy, vol. 26, no. 4, Art. no. 322, 2024, doi:10.3390/e26040322 .

K. Olgu, T. Kenter, J. Nunez-Yanez, and S. Mcintosh-Smith, “Optimisation and Evaluation of Breadth First Search with oneAPI/SYCL on Intel FPGAs: from Describing Algorithms to Describing Architectures,”10.1145/3648115.3648134__2024, doi:10.1145/3648115.3648134 .

C. Bauer et al., “Noctu Supercomputer,”10.17815/jlsrf-8-187 __Journal of large-scale research facilities, vol. 9, 2024, doi:10.17815/jlsrf-8-187  .

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

T. Hansmeier, T. Kenter, M. Meyer, H. Riebler, M. Platzner, and C. Plessl, “Compute Centers I: Heterogeneous Execution Environments,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 165–182.

J.-O. Opdenhövel, C. Plessl, and T. Kenter, “Mutation Tree Reconstruction of Tumor Cells on FPGAs Using a Bit-Level Matrix Representation,”10.1145/3597031.3597050__2023, doi:10.1145/3597031.3597050 .

X. Wu, T. Kenter, R. Schade, T. Kühne, and C. Plessl, “Computing and Compressing Electron Repulsion Integrals on FPGAs,”10.1109/FCCM57271.2023.00026__in 2023 IEEE 31st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2023, pp. 162–173, doi:10.1109/FCCM57271.2023.00026 .

R. Schade, T. Kenter, H. Elgabarty, M. Lass, T. Kühne, and C. Plessl, “Breaking the exascale barrier for the electronic structure problem in ab-initio molecular dynamics,”10.1177/10943420231177631__The International Journal of High Performance Computing Applications, Art. no. 109434202311776, 2023, doi:10.1177/10943420231177631 .

C. Alt et al., “Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline,” in Lecture Notes in Computer Science, Cham: Springer Nature Switzerland, 2023.

L. Van Hirtum et al., “A computation of D(9) using FPGA Supercomputing,” arXiv:2304.03039. 2023.

J. Faj, T. Kenter, S. Faghih-Naini, C. Plessl, and V. Aizinger, “Scalable Multi-FPGA Design of a Discontinuous Galerkin Shallow-Water Model on Unstructured Meshes,”10.1145/3592979.3593407__2023, doi:10.1145/3592979.3593407 .

C. Prouveur, M. Haefele, T. Kenter, and N. Voss, “FPGA Acceleration for HPC Supercapacitor Simulations,”10.1145/3592979.3593419__2023, doi:10.1145/3592979.3593419 .

M. Lass, Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations. Paderborn: Universität Paderborn, 2022.

V. Gavini et al., “Roadmap on Electronic Structure Codes in the Exascale Era,” arXiv:2209.12747. 2022.

M. Karp et al., “A High-Fidelity Flow Solver for Unstructured Meshes on Field-Programmable Gate Arrays: Design, Evaluation, and Future Challenges,”10.1145/3492805.3492808__2022, doi:10.1145/3492805.3492808 .

T. Kühne, C. Plessl, R. Schade, and O. Schütt, “CK on the road to exascale,” arXiv:2205.14741. 2022.

R. Schade, C. Bauer, K. Tamoev, L. Mazur, C. Plessl, and T. Kühne, “Parallel quantum chemistry on noisy intermediate-scale quantum computers,”10.1103/PhysRevResearch.4.033160__Phys. Rev. Research, vol. 4, p. 033160, 2022, doi:10.1103/PhysRevResearch.4.033160 .

R. Schade et al., “Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms,”10.1016/j.parco.2022.102920__Parallel Computing, vol. 111, Art. no. 102920, 2022, doi:10.1016/j.parco.2022.102920 .

M. Meyer, T. Kenter, and C. Plessl, “In-depth FPGA Accelerator Performance Evaluation with Single Node Benchmarks from the HPC Challenge Benchmark Suite for Intel and Xilinx FPGAs using OpenCL,”10.1016/j.jpdc.2021.10.007__Journal of Parallel and Distributed Computing, 2022, doi:10.1016/j.jpdc.2021.10.007 .

J. Menzel, C. Plessl, and T. Kenter, “The Strong Scaling Advantage of FPGAs in HPC for N-body Simulations,”10.1145/3491235__ACM Transactions on Reconfigurable Technology and Systems, vol. 15, no. 1, pp. 1–30, 2021, doi:10.1145/3491235 .

M. Karp et al., “High-Performance Spectral Element Methods on Field-Programmable Gate Arraysf: Implementation, Evaluation, and Future Projection,”10.1109/ipdps49936.2021.00116__2021, doi:10.1109/ipdps49936.2021.00116 .

S. Alhaddad et al., “HighPerMeshes – A Domain-Specific Language for Numerical Algorithms on Unstructured Grids,” in Euro-Par 2020: Parallel Processing Workshops, Cham, 2021.

A. Ramaswami, T. Kenter, T. Kühne, and C. Plessl, “Evaluating the Design Space for Offloading 3D FFT Calculations to an FPGA for High-Performance Computing,” in Applied Reconfigurable Computing. Architectures, Tools, and Applications, Cham: Springer International Publishing, 2021.

S. Alhaddad et al., “The HighPerMeshes framework for numerical algorithms on unstructured grids,”10.1002/cpe.6616__Concurrency and Computation: Practice and Experience, p. e6616, 2021, doi:10.1002/cpe.6616 .

M. Karp et al., “High-Performance Spectral Element Methods on Field-Programmable Gate Arraysf: Implementation, Evaluation, and Future Projection,”10.1109/ipdps49936.2021.00116__2021, doi:10.1109/ipdps49936.2021.00116 .

T. Kenter, A. Shambhu, S. Faghih-Naini, and V. Aizinger, “Algorithm-hardware co-design of a discontinuous Galerkin shallow-water model for a dataflow architecture on FPGA,”10.1145/3468267.3470617__2021, doi:10.1145/3468267.3470617 .

T. Kühne et al., “CK: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations,”10.1063/5.0007045__The Journal of Chemical Physics, vol. 152, no. 19, Art. no. 194103, 2020, doi:10.1063/5.0007045 .

M. Lass, R. Schade, T. Kühne, and C. Plessl, “A Submatrix-Based Method for Approximate Matrix Function Evaluation in the Quantum Chemistry Code CK,”10.1109/SC41405.2020.00084__in Proc. International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Atlanta, GA, US, 2020, pp. 1127–1140, doi:10.1109/SC41405.2020.00084 .

M. Meyer, T. Kenter, and C. Plessl, “Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite,”10.1109/h2rc51942.2020.00007__2020, doi:10.1109/h2rc51942.2020.00007 .

V. Rengaraj, M. Lass, C. Plessl, and T. Kühne, “Accurate Sampling with Noisy Forces from Approximate Computing,”10.3390/computation8020039__Computation, vol. 8, no. 2, Art. no. 39, 2020, doi:10.3390/computation8020039 .

H. Riebler, G. F. Vaz, T. Kenter, and C. Plessl, “Transparent Acceleration for Heterogeneous Platforms with Compilation to OpenCL,” ACM Trans. Archit. Code Optim. (TACO), vol. 16, no. 2, pp. 14:1–14:26, 2019.

P. Gorlani, T. Kenter, and C. Plessl, “OpenCL Implementation of Cannon’s Matrix Multiplication Algorithm on Intel Stratix 10 FPGAs,” in Proceedings of the International Conference on Field-Programmable Technology (FPT), 2019.

G. F. Vaz, Using Just-in-Time Code Generation to Transparently Accelerate Applications in Heterogeneous Systems. Universität Paderborn, 2019.

D. Richters, M. Lass, A. Walther, C. Plessl, and T. Kühne, “A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices,”10.4208/cicp.OA-2018-0053__Communications in Computational Physics, vol. 25, no. 2, pp. 564–585, 2019, doi:10.4208/cicp.OA-2018-0053 .

M. Platzner and C. Plessl, “FPGAs im Rechenzentrum,”10.1007/s00287-019-01187-w__Informatik Spektrum, 2019, doi:10.1007/s00287-019-01187-w .

M. Lass, T. Kühne, and C. Plessl, “Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots,” Embedded Systems Letters, vol. 10, no. 2, pp. 33–36, 2018.

T. Filmwala, Study Effects of Approximation on Conjugate Gradient Algorithm and Accelerate it on FPGA Platform. Universität Paderborn, 2018.

O. Gadewar, Programmable Programs? - Designing FPGA Overlay Architectures with OpenCL. Universität Paderborn, 2018.

J. C. Mertens, A. Boschmann, M. Schmidt, and C. Plessl, “Sprint diagnostic with GPS and inertial sensor fusion,” Sports Engineering, vol. 21, no. 4, pp. 441–451, 2018.

A. Ramaswami, Accelerating Molecular Dynamic Simulations by Offloading Fast Fourier Transformations to FPGA. Universität Paderborn, 2018.

T. Kenter et al., “OpenCL-based FPGA Design to Accelerate the Nodal Discontinuous Galerkin Method for Unstructured Meshes,”10.1109/FCCM.2018.00037__presented at the Proc. Int. Symp. on Field-Programmable Custom Computing Machines (FCCM), 2018, doi:10.1109/FCCM.2018.00037 .

M. Lass, S. Mohr, H. Wiebeler, T. Kühne, and C. Plessl, “A Massively Parallel Algorithm for the Approximate Calculation of Inverse p-th Roots of Large Sparse Matrices,”10.1145/3218176.3218231__presented at the Platform for Advanced Scientific Computing Conference (PASC), Basel, Switzerland, 2018, doi:10.1145/3218176.3218231 .

H. Riebler, G. F. Vaz, T. Kenter, and C. Plessl, “Automated Code Acceleration Targeting Heterogeneous OpenCL Devices,”10.1145/3178487.3178534__2018, doi:10.1145/3178487.3178534 .

H. Riebler, M. Lass, R. Mittendorf, T. Löcke, and C. Plessl, “Efficient Branch and Bound on FPGAs Using Work Stealing and Instance-Specific Designs,”10.1145/3053687__ACM Transactions on Reconfigurable Technology and Systems (TRETS), vol. 10, no. 3, p. 24:1-24:23, 2017, doi:10.1145/3053687 .

T. Kenter, J. Förstner, and C. Plessl, “Flexible FPGA design for FDTD using OpenCL,”10.23919/FPL.2017.8056844__2017, doi:10.23919/FPL.2017.8056844 .

J. Schumacher, C. Plessl, and W. Vandelli, “High-Throughput and Low-Latency Network Communication with NetIO,”10.1088/1742-6596/898/8/082003__Journal of Physics: Conference Series, vol. 898, Art. no. 082003, 2017, doi:10.1088/1742-6596/898/8/082003 .

M. Lass, D. Leibenger, and C. Sorge, “Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension,” in Proc. 41st Conference on Local Computer Networks (LCN), 2016.

C. Tölke, Sicherheit von hybriden FPGA-Systemen in der industriellen Automatisierungstechnik -- Anforderungen und Umsetzung. Universität Paderborn, 2016.

G. Wüllrich, Dynamic OpenCL Task Scheduling for Energy and Performance in a Heterogeneous Environment. Universität Paderborn, 2016.

T. Kenter, Reconfigurable Accelerators in the World of General-Purpose Computing. Universität Paderborn, 2016.