Invasive computing for timing-predictable stream processing on MPSoCs

Stefan Wildermann 1 , Michael Bader 2 , Lars Bauer 3 , Marvin Damschen 3 , Dirk Gabriel 4 , Michael Gerndt 5 , Michael Glaß 6 , Jörg Henkel 3 , Johny Paul 4 , Alexander Pöppl 2 , Sascha Roloff 1 , Tobias Schwarzer 1 , Gregor Snelting 7 , Walter Stechele 4 , Jürgen Teich 1 , Andreas Weichslgartner 1 , and Andreas Zwinkau 7
  • 1 Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Hardware/Software Co-Design, Cauerstr. 11, 91058 Erlangen, Germany, Germany
  • 2 Technical University of Munich (TUM), Hardware-aware algorithms and software for HPC, Boltzmannstr. 3, 85748 Garching, Germany, Germany
  • 3 Karlsruhe Institute of Technology (KIT), Chair for Embedded Systems, Haid-und-Neu-Str. 7, 76131 Karlsruhe, Germany, Germany
  • 4 Technical University of Munich (TUM), Intstitute for Integrated Systems, Arcisstr. 21, 80290 Munich, Germany, Germany
  • 5 Technical University of Munich (TUM), Chair for Computer Architecture, Boltzmannstr. 3, 85748 Garching, Germany, Germany
  • 6 Ulm University, Institute of Embedded Systems/Real-Time Systems, Albert-Einstein-Allee 11, 89081 Ulm, Germany, Germany
  • 7 Karlsruhe Institute of Technology (KIT), Institute for Program Structures and Data Organisation (IPD), Am Fasanengarten 5, 76131 Karlsruhe, Germany, Germany

Abstract

Multi-Processor Systems-on-a-Chip (MPSoCs) provide sufficient computing power for many applications in scientific as well as embedded applications. Unfortunately, when real-time requirements need to be guaranteed, applications suffer from the interference with other applications, uncertainty of dynamic workload and state of the hardware. Composable application/architecture design and timing analysis is therefore a must for guaranteeing real-time applications to satisfy their timing requirements independent from dynamic workload. Here, Invasive Computing is used as the key enabler for compositional timing analysis on MPSoCs, as it provides the required isolation of resources allocated to each application. On the basis of this paradigm, this work proposes a hybrid application mapping methodology that combines design-time analysis of application mappings with run-time management. Design space exploration delivers several resource reservation configurations with verified real-time guarantees for individual applications. These timing properties can then be guaranteed at run-time, as long as dynamic resource allocations comply with the offline analyzed resource configurations.

This article describes our methodology and presents programming, optimization, analysis, and hardware techniques for enforcing timing predictability. A case study illustrates the timing-predictable management of real-time computer vision applications in dynamic robot system scenarios.

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