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Using Segmentation to Improve Schedulability of Real-Time Traffic over RRA-based NoCs
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-9736-8490
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1276-3609
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1687-930X
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-6132-7945
2016 (English)In: ACM SIGBED Review. Special Issue on 14th International Workshop on Real-Time Networks (RTN 2016) SIGBED Review, ISSN 1551-3688, Vol. 13, no 4, p. 20-24Article in journal (Refereed) Published
Abstract [en]

Network-on-Chip (NoC) is the interconnect of choice for many- core processors and system-on-chips in general. Most of the existing NoC designs focus on the performance with respect to average throughput, which makes them less applicable for real-time applications especially when applications have hard timing requirements on the worst-case scenarios. In this paper, we focus on a Round- Robin Arbitration (RRA) based wormhole-switched NoC which is a common architecture used in most of the existing implementations. We propose a novel segmentation algorithm targeting RRA-based NoCs in order to improve the schedulability of real-time traffic without modifying the hardware architecture. According to the evaluation results, the proposed segmentation solution can signifi- cantly improve the schedulability of the whole network.

Place, publisher, year, edition, pages
France: ACM , 2016. Vol. 13, no 4, p. 20-24
Keywords [en]
Many-CoreNoCSegmentationRound Robin
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-33814DOI: 10.1145/3015037.3015040OAI: oai:DiVA.org:mdh-33814DiVA, id: diva2:1048576
Projects
PREMISE - Predictable Multicore SystemsDPAC - Dependable Platforms for Autonomous systems and ControlAvailable from: 2016-11-21 Created: 2016-11-21 Last updated: 2016-12-01Bibliographically approved

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Liu, MengBecker, MatthiasBehnam, MorisNolte, Thomas
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