Cache-aware Schedulability Analysis of PREM Compliant Tasks
| Autor: | Rashid, Syed Aftab, Awan, Muhammad Ali, Souto, Pedro, Bletsas, Konstantinos, Tovar, Eduardo |
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| Přispěvatelé: | Repositório Científico do Instituto Politécnico do Porto |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Popis: | The Predictable Execution Model (PREM) is useful for mitigating inter-core interference due to shared resources such as the main memory. However, it is cache-agnostic, which makes schedulabulity analysis pessimistic, via overestimation of prefetches and write-backs. In response, we present cache-aware schedulability analysis for PREM tasks on fixed-task-priority partitioned multicores, that bounds the number of cache prefetches and write-backs. Our approach identifies memory blocks loaded in the execution of a previous scheduling interval of each task, that remain in the cache until its next scheduling interval. Doing so, greatly reduces the estimated prefetches and write backs. In experimental evaluations, our analysis improves the schedulability of PREM tasks by up to 55 percentage points. This work was partially supported by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology), within the CISTER Research Unit (UIDP/UIDB/04234/2020); also by the Operational Competitiveness Programme and Internationalization (COMPETE 2020) under the PT2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by national funds through the FCT, within project PREFECT (POCI-01-0145-FEDER-029119); also by the European Union’s Horizon 2020 - The EU Framework Programme for Research and Innovation 2014-2020, under grant agreement No. 732505. Project ”TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145- FEDER000020” financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement |
| Databáze: | OpenAIRE |
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