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Thiele S. Implementing Machine Learning Functions as PYNQ FPGA Overlays.; 2020.

Jaganath V. Extension and Evaluation of Python-Based High-Level Synthesis Tool Flows.; 2020.

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

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

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

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

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

Lass M. Localization and Analysis of Code Paths Suitable for Acceleration Using Approximate Computing. Paderborn: Paderborn University; 2015.

Funke L. An LLVM Based Toolchain for Transparent Acceleration of Digital Image Processing Applications Using FPGA Overlay Architectures. Universität Paderborn; 2015.

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Wallaschek F. Accelerating Programmable Logic Controllers with the Use of FPGAs. Universität Paderborn; 2015.

Beisel T. Management and Scheduling of Accelerators for Heterogeneous High-Performance Computing. Berlin: Logos Verlag Berlin GmbH; 2015.