M. Lass, Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations. Paderborn: Universität Paderborn, 2022.
LibreCat: /record/32414
DOI: 10.17619/UNIPB/1-1281

S. Thiele, Implementing Machine Learning Functions as PYNQ FPGA Overlays. 2020.
LibreCat: /record/20820

V. Jaganath, Extension and Evaluation of Python-based High-Level Synthesis Tool Flows. 2020.
LibreCat: /record/20821

F. P. Jentzsch, Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture. 2020.
LibreCat: /record/21433

G. F. Vaz, Using Just-in-Time Code Generation to Transparently Accelerate Applications in Heterogeneous Systems. Universität Paderborn, 2019.
LibreCat: /record/14849

H. Riebler, Efficient parallel branch-and-bound search on FPGAs using work stealing and instance-specific designs. 2019.
LibreCat: /record/34167
DOI: 10.17619/UNIPB/1-830

T. Filmwala, Study Effects of Approximation on Conjugate Gradient Algorithm and Accelerate it on FPGA Platform. Universität Paderborn, 2018.
LibreCat: /record/5414

O. Gadewar, Programmable Programs? - Designing FPGA Overlay Architectures with OpenCL. Universität Paderborn, 2018.
LibreCat: /record/5421

A. Ramaswami, Accelerating Molecular Dynamic Simulations by Offloading Fast Fourier Transformations to FPGA. Universität Paderborn, 2018.
LibreCat: /record/5417

C. Tölke, Sicherheit von hybriden FPGA-Systemen in der industriellen Automatisierungstechnik -- Anforderungen und Umsetzung. Universität Paderborn, 2016.
LibreCat: /record/5418