Rengaraj, V., Lass, M., Plessl, C., &; Kühne, T. (2020). Accurate Sampling with Noisy Forces from Approximate Computing. Computation, 8(2), Article 39.https://doi.org/10.3390/computation8020039 

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

Gorlani, P., Kenter, T., &; Plessl, C. (2019). OpenCL Implementation of Cannon’s Matrix Multiplication Algorithm on Intel Stratix 10 FPGAs. In Proceedings of the International Conference on Field-Programmable Technology (FPT). IEEE.https://doi.org/10.1109/ICFPT47387.2019.00020 

Riebler, H. (2019). Efficient parallel branch-and-bound search on FPGAs using work stealing and instance-specific designs.https://doi.org/10.17619/UNIPB/1-830 

Richters, D., Lass, M., Walther, A., Plessl, C., &; Kühne, T. (2019). A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices. Communications in Computational Physics, 25(2), 564–585.https://doi.org/10.4208/cicp.OA-2018-0053 

Platzner, M., &; Plessl, C. (2019). FPGAs im Rechenzentrum. Informatik Spektrum.https://doi.org/10.1007/s00287-019-01187-w 

Lass, M., Kühne, T., &; Plessl, C. (2018). Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots. Embedded Systems Letters, 10(2), 33–36.https://doi.org/10.1109/LES.2017.2760923 

Keller, A. (2018). A Data Structure for Planning Based Workload Management of Heterogeneous HPC Systems. In D. Klusádek, W. Cirne, &; N. Desai (Eds.), Proc. Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP) (Vol. 10773, pp. 132–151). Orlando, FL, USA: Springer.https://doi.org/10.1007/978-3-319-77398-8_8 

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

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