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handle: 2117/119385
Multicores are becoming ubiquitous in automotive. Yet, the expected benefits on integration are challenged by multicore contention concerns on timing V&V. Worst-case execution time (WCET) estimates are required as early as possible in the software development, to enable prompt detection of timing misbehavior. Factoring in multicore contention necessarily builds on conservative assumptions on interference, independent of co-runners load on shared hardware. We propose a contention model for automotive multicores that balances time-composability with tightness by exploiting available information on contenders. We tailor the model to the AURIX TC27x and provide tight WCET estimates using information from performance monitors and software configurations. The research leading to this work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644080 (SAFURE). This work has also been partially funded by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. The Ministry of Economy and Competitiveness partially supported Jaume Abella under Ramon y Cajal postdoctoral fellowship (RYC-2013-14717) and Enrico Mezzetti under Juan de la Cierva-Incorporación postdoctoral fellowship (IJCI-2016-27396). Peer Reviewed
Computer systems organization, Performance counters,, Programació (Ordinadors), Software performance, Supercomputadors, :Informàtica [Àrees temàtiques de la UPC], AURIX TriCore, Software and its engineering, Multicore contention,, Computer architecture, Computer software, Àrees temàtiques de la UPC::Informàtica, Real-time systems
Computer systems organization, Performance counters,, Programació (Ordinadors), Software performance, Supercomputadors, :Informàtica [Àrees temàtiques de la UPC], AURIX TriCore, Software and its engineering, Multicore contention,, Computer architecture, Computer software, Àrees temàtiques de la UPC::Informàtica, Real-time systems
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 15 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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