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M. Lass, Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations. Paderborn: Universität Paderborn, 2022.
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L. Altenkort, A. M. Eller, O. Kaczmarek, L. Mazur, G. D. Moore, and H.-T. Shu, “Lattice QCD noise reduction for bosonic correlators through blocking,”10.1103/physrevd.105.094505__Physical Review D, vol. 105, no. 9, Art. no. 094505, 2022, doi:10.1103/physrevd.105.094505 .
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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 .
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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 .
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N. Borghini, M. Borrell, N. Feld, H. Roch, S. Schlichting, and C. Werthmann, “Statistical analysis of initial state and final state response in  heavy-ion collisions,”10.1103/PhysRevC.107.034905__Phys. Rev. C 107 (2023) 034905, 2022, doi:10.1103/PhysRevC.107.034905 .
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E. Lesch et al., “Plant mitochondrial RNA editing factors can perform targeted C-to-U editing of nuclear transcripts in human cells,”10.1093/nar/gkac752__Nucleic Acids Research, vol. 50, no. 17, pp. 9966–9983, 2022, doi:10.1093/nar/gkac752 .
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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 .
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T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts,” in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, Hawaii, 2021, pp. 1994–2002.
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