Dates and Events:
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OSADL Articles:
2023-11-12 12:00
Open Source License Obligations Checklists even better now
Import the checklists to other tools, create context diffs and merged lists
2022-07-11 12:00
Call for participation in phase #4 of Open Source OPC UA open62541 support project
Letter of Intent fulfills wish list from recent survey
2022-01-13 12:00
Phase #3 of OSADL project on OPC UA PubSub over TSN successfully completed
Another important milestone on the way to interoperable Open Source real-time Ethernet has been reached
2021-02-09 12:00
Open Source OPC UA PubSub over TSN project phase #3 launched
Letter of Intent with call for participation is now available |
OSADL Generalversammlung 2026 (online) / OSADL General Assembly 2026 (online)
e-mobil BW: EU Cyber Resilience Act (CRA) – Was bedeutet er für die Automobilindus-trie?
OSADL Networking Day 2026 in Heidelberg, Germany
Cyber Resilience Act Summit 2026
Real Time Linux Workshops
1999 - 2000 - 2001 - 2002 - 2003 - 2004 - 2005 - 2006 - 2007 - 2008 - 2009 - 2010 - 2011 - 2012 - 2013 - 2014 - 2015
13th Real-Time Linux Workshop from October 20 to 22 at the Faculty of Electrical Engineering, Czech Technical University in Prague
Announcement - Hotels - Directions - Agenda - Paper Abstracts - Presentations - Registration - Abstract Submission - Sponsoring - Gallery
Realtime scheduling using GPUs - proof of feasibility
Peter Fodrek, Slovak University of Technology
Pavol Baliga, Slovak University of Technology
Jaroslav Bazi, Slovak University of Technology
This paper will report our evaluation to use nVidia CUDA and AMD Accelerated Parallel Processing as platform for hard realtime scheduling. Specifically, we evaluated which types of tasks are faster on GPGPU than on CPU. We investigated computational tasks, memory intensive tasks (especially tasks using low latency GDDR memory) and disk intensive tasks. This study is the first part of a larger research program to design an innovative Linux scheduler subsystem that runs on GPGPU and schedules tasks running on GPGPU as well as on CPU.
Based on the results obtained from benchmarking the various types of tasks, we found that some of them are faster on GPGPU than on CPU and should, therefore, preferably be executed on GPGPU. Preliminary data suggest that we can expect a speedup of up to 10-fold with respect to execution time and latency.
