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Article

Hybrid Application Mapping for Composable Many-Core Systems: Overview and Future Perspective

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Chair for Hardware/Software Co-Design, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91058 Erlangen, Germany
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Institute of Embedded Systems/Real-Time Systems, Faculty of Engineering, Computer Science and Psychology, Ulm University, 89081 Ulm, Germany
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Chair for Embedded Systems, Department of Computer Science, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany
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Distributed and Parallel Systems Group, Institute of Computer Science, University of Innsbruck, 6020 Innsbruck, Austria
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AUDI AG, 85045 Ingolstadt, Germany
*
Author to whom correspondence should be addressed.
J. Low Power Electron. Appl. 2020, 10(4), 38; https://doi.org/10.3390/jlpea10040038
Received: 25 September 2020 / Revised: 13 November 2020 / Accepted: 13 November 2020 / Published: 17 November 2020
Many-core platforms are rapidly expanding in various embedded areas as they provide the scalable computational power required to meet the ever-growing performance demands of embedded applications and systems. However, the huge design space of possible task mappings, the unpredictable workload dynamism, and the numerous non-functional requirements of applications in terms of timing, reliability, safety, and so forth. impose significant challenges when designing many-core systems. Hybrid Application Mapping (HAM) is an emerging class of design methodologies for many-core systems which address these challenges via an incremental (per-application) mapping scheme: The mapping process is divided into (i) a design-time Design Space Exploration (DSE) step per application to obtain a set of high-quality mapping options and (ii) a run-time system management step in which applications are launched dynamically (on demand) using the precomputed mappings. This paper provides an overview of HAM and the design methodologies developed in line with it. We introduce the basics of HAM and elaborate on the way it addresses the major challenges of application mapping in many-core systems. We provide an overview of the main challenges encountered when employing HAM and survey a collection of state-of-the-art techniques and methodologies proposed to address these challenges. We finally present an overview of open topics and challenges in HAM, provide a summary of emerging trends for addressing them particularly using machine learning, and outline possible future directions. While there exists a large body of HAM methodologies, the techniques studied in this paper are developed, to a large extent, within the scope of invasive computing. Invasive computing introduces resource awareness into applications and employs explicit resource reservation to enable incremental application mapping and dynamic system management. View Full-Text
Keywords: Hybrid Application Mapping (HAM); many-core systems; embedded systems; composability; design space exploration (DSE); resource management; Network-on-Chip (NoC); real-time guarantees; predictability; machine learning Hybrid Application Mapping (HAM); many-core systems; embedded systems; composability; design space exploration (DSE); resource management; Network-on-Chip (NoC); real-time guarantees; predictability; machine learning
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MDPI and ACS Style

Pourmohseni, B.; Glaß, M.; Henkel, J.; Khdr, H.; Rapp, M.; Richthammer, V.; Schwarzer, T.; Smirnov, F.; Spieck, J.; Teich, J.; Weichslgartner, A.; Wildermann, S. Hybrid Application Mapping for Composable Many-Core Systems: Overview and Future Perspective. J. Low Power Electron. Appl. 2020, 10, 38. https://doi.org/10.3390/jlpea10040038

AMA Style

Pourmohseni B, Glaß M, Henkel J, Khdr H, Rapp M, Richthammer V, Schwarzer T, Smirnov F, Spieck J, Teich J, Weichslgartner A, Wildermann S. Hybrid Application Mapping for Composable Many-Core Systems: Overview and Future Perspective. Journal of Low Power Electronics and Applications. 2020; 10(4):38. https://doi.org/10.3390/jlpea10040038

Chicago/Turabian Style

Pourmohseni, Behnaz, Michael Glaß, Jörg Henkel, Heba Khdr, Martin Rapp, Valentina Richthammer, Tobias Schwarzer, Fedor Smirnov, Jan Spieck, Jürgen Teich, Andreas Weichslgartner, and Stefan Wildermann. 2020. "Hybrid Application Mapping for Composable Many-Core Systems: Overview and Future Perspective" Journal of Low Power Electronics and Applications 10, no. 4: 38. https://doi.org/10.3390/jlpea10040038

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