Lass, Michael, et al. “A Massively Parallel Algorithm for the Approximate Calculation of Inverse P-Th Roots of Large Sparse Matrices.”10.1145/3218176.3218231__Proc. Platform for Advanced Scientific Computing (PASC) Conference, ACM, 2018, doi:10.1145/3218176.3218231.
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Riebler, Heinrich, et al. “Automated Code Acceleration Targeting Heterogeneous OpenCL Devices.”10.1145/3178487.3178534__Proc. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), ACM, 2018, doi:10.1145/3178487.3178534.
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Riebler, Heinrich, et al. “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, Association for Computing Machinery (ACM), 2017, p. 24:1-24:23, doi:10.1145/3053687.
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Kenter, Tobias, et al. “Flexible FPGA Design for FDTD Using OpenCL.”10.23919/FPL.2017.8056844__Proc. Int. Conf. on Field Programmable Logic and Applications (FPL), IEEE, 2017, doi:10.23919/FPL.2017.8056844.
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Schumacher, Jörn, et al. “High-Throughput and Low-Latency Network Communication with NetIO.”10.1088/1742-6596/898/8/082003__Journal of Physics: Conference Series, vol. 898, 082003, IOP Publishing, 2017, doi:10.1088/1742-6596/898/8/082003.
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Lass, Michael, et al. “Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension.”10.1109/lcn.2016.11__Proc. 41st Conference on Local Computer Networks (LCN), IEEE, 2016, doi:10.1109/lcn.2016.11.
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Tölke, Christian. Sicherheit von Hybriden FPGA-Systemen in Der Industriellen Automatisierungstechnik -- Anforderungen Und Umsetzung. Universität Paderborn, 2016.
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Wüllrich, Gunnar. Dynamic OpenCL Task Scheduling for Energy and Performance in a Heterogeneous Environment. Universität Paderborn, 2016.
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Kenter, Tobias. Reconfigurable Accelerators in the World of General-Purpose Computing. Universität Paderborn, 2016.
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Agne, Andreas, et al. “ReconOS.”10.1007/978-3-319-26408-0_13__FPGAs for Software Programmers, edited by Dirk Koch et al., Springer International Publishing, 2016, pp. 227–44, doi:10.1007/978-3-319-26408-0_13.
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Riebler, Heinrich, et al. “Using Just-in-Time Code Generation for Transparent Resource Management in Heterogeneous Systems.” Proc. HiPEAC Workshop on Reonfigurable Computing (WRC), 2016.
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Kenter, Tobias, and Christian Plessl. “Microdisk Cavity FDTD Simulation on FPGA Using OpenCL.” Proc. Workshop on Heterogeneous High-Performance Reconfigurable Computing (RC), 2016.
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Lass, Michael, et al. “Using Approximate Computing in Scientific Codes.” Workshop on Approximate Computing (AC), 2016.
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Riebler, Heinrich, et al. “Using Just-in-Time Code Generation for Transparent Resource Management in Heterogeneous Systems.”10.1109/RTSI.2016.7740545__Proceedings of International Forum on Research and Technologies for Society and Industry (RTSI), IEEE, 2016, pp. 1–5, doi:10.1109/RTSI.2016.7740545.
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Agne, Andreas, et al. “Self-Aware Compute Nodes.”10.1007/978-3-319-39675-0_8__Self-Aware Computing Systems, Springer International Publishing, 2016, pp. 145–65, doi:10.1007/978-3-319-39675-0_8.
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Vaz, Gavin Francis, et al. “Potential and Methods for Embedding Dynamic Offloading Decisions into Application Code.”10.1016/j.compeleceng.2016.04.021__Computers and Electrical Engineering, vol. 55, Elsevier, 2016, pp. 91–111, doi:10.1016/j.compeleceng.2016.04.021.
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Lösch, Achim, et al. “Performance-Centric Scheduling with Task Migration for a Heterogeneous Compute Node in the Data Center.” Proceedings of the 2016 Design, Automation &; Test in Europe Conference &; Exhibition (DATE), EDA Consortium / IEEE, 2016, pp. 912–17.
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Kenter, Tobias, et al. “Opportunities for Deferring Application Partitioning and Accelerator Synthesis to Runtime (Extended Abstract).” Workshop on Reconfigurable Computing (WRC), 2016.
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Torresen, Jim, et al. “Self-Aware and Self-Expressive Systems – Guest Editor’s Introduction.”10.1109/MC.2015.205__IEEE Computer, vol. 48, no. 7, IEEE Computer Society, 2015, pp. 18–20, doi:10.1109/MC.2015.205.
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Lass, Michael. Localization and Analysis of Code Paths Suitable for Acceleration Using Approximate Computing. Paderborn University, 2015.
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