Experiences and Results of Parallelisation of Industrial Hard Real-time Applications for the parMERASA Multi-core
Year: 2015
Type: conference-paper
Abstract: The EC FP-7 project parMERASA (Multi-Core Execution of Parallelised Hard Real-Time Applications Supporting Analysability, Oct. 1, 2011 until Sept. 30, 2014) provides a timing analysable system of parallel hard real-time applications running on a scalable multi-core processor. parMERASA goes one step beyond mixed criticality demands: It targets future complex control algorithms by parallelising hard real-time programs to run on predictable multi-/many-core processors. A software engineering approach was developed to ease sequential to parallel program transformation by developing and supporting suitable parallel design patterns that are analysable. The following sequential hard real-time programs were parallelised by applying the pattern-oriented parallelisation approach: 3D path planning and stereo navigation algorithms (Honeywell International s.r.o.), diesel engine management system (DENSO AUTOMOTIVE Deutschland GmbH), and the control algorithm for a dynamic compaction machine (BAUER Maschinen GmbH). The paper reports on parallelisation approach, experiences made during parallelisation with applications, tools and multi-core architecture, scalability of applications and quantitative results reached.
Source: HAL
Authors: Ungerer, Theo, Bradatsch, Christian, Frieb, Martin, Kluge, Florian, Mische, Jörg, Stegmeier, Alexander, Jahr, Ralf, Gerdes, Mike, Zaykov, Pavel, Matusova, Lucie, Li, Zai Jian Jia, Petrov, Zlatko, Böddeker, Bert, Kehr, Sebastian, Regler, Hans, Hugl, Andreas, Rochange, Christine, Ozaktas, Haluk, Cassé, Hugues, Bonenfant, Armelle, Sainrat, Pascal, Lay, Nick, George, David, Broster, Ian, Quinones, Eduardo, Panic, Milos, Abella, Jaume, Hernandez, Carles, Cazorla, Francisco, Uhrig, Sascha, Rohde, Mathias, Pyka, Arthur
Language: English
Topic: Real-Time Systems Scheduling
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3089380014