Wolfgang Schröder-Preikschat
University of Erlangen-Nuremberg
215 Papers
921 Citations
Wolfgang Schröder-Preikschat is an academic researcher from University of Erlangen-Nuremberg. The author has contributed to research in topics: Computer science & System software. The author has an hindex of 28, co-authored 209 publications. Previous affiliations of Wolfgang Schröder-Preikschat include University of California, Irvine & Free University of Berlin.
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Papers
Enabling Wireless Network Support for Gain Scheduled Control
Sebastian Gallenmuller,René Glebke,Stephan M. Gunther,Eric Hauser,Maurice Leclaire,Stefan Reif,Jan Rüth,Andreas Schmidt,Georg Carle,Thorsten Herfet,Wolfgang Schröder-Preikschat,Klaus Wehrle +11 more
- 25 Mar 2019
TL;DR: This work presents a system based on a real-time transport protocol that is aware of application-level constraints and applies run-time measurements for channel properties and demonstrates predictability of latency and potential limits for wireless networked control.
4
A Wait-Free Dynamic Storage Allocator by Adopting the Helping Queue Pattern
TL;DR: This work designs a wait-free dynamic storage allocator (DSA), which can guarantee progress of threads and does not influence other threads to make progress, and is the first known approach using a scalable and bounded nonblocking synchronization strategy.
Memory protection at option
Michael Stilkerich,Daniel Lohmann,Wolfgang Schröder-Preikschat +2 more
- 27 Apr 2010
TL;DR: The claim that the best-suited memory protection type depends on the application is supported by a preliminary evaluation and a system suited for deeply embedded systems is proposed.
AI Waste Prevention: Time and Power Estimation for Edge Tensor Processing Units: Poster
Stefan Reif,Benedict Herzog,Judith Hemp,Wolfgang Schröder-Preikschat,Timo Hönig +4 more
- 22 Jun 2021
TL;DR: Precious as discussed by the authors is an approach, as well as practical implementation, that estimates execution time and power draw of neural networks that execute on a commercially available off-the-shelf accelerator hardware (i.e., Google Coral Edge TPU).
3
Shallow Water Waves on a Deep Technology Stack: Accelerating a Finite Volume Tsunami Model Using Reconfigurable Hardware in Invasive Computing
Alexander Pöppl,Marvin Damschen,Florian Schmaus,Andreas Fried,Manuel Mohr,Matthias Blankertz,Lars Bauer,Jorg Henkel,Wolfgang Schröder-Preikschat,Michael Bader +9 more
- 28 Aug 2017
TL;DR: This work demonstrates the feasibility of invasive computing for HPC scenarios by accelerating a proxy application for the simulation of shallow water waves using the i-Core, a reconfigurable processor that is part of the invasive computing multiprocessor system-on-chip.