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dc.contributor.author | Segarra, Juan | es_ES |
dc.contributor.author | Martí-Campoy, Antonio | es_ES |
dc.date.accessioned | 2023-06-16T18:02:02Z | |
dc.date.available | 2023-06-16T18:02:02Z | |
dc.date.issued | 2022 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/194306 | |
dc.description.abstract | [EN] In real-time systems, analyzing the worst-case execution time (WCET) of a task in the presenceof data caches is hard. The ACDC is a data cache that provides predictability, facilitating WCET analysis.It works by granting data cache replacement permission to speci_c load/store instructions. Nonetheless,knowing how to select these instructions to minimize the WCET, i.e., con_guring the ACDC, is not trivial. In this paper, we propose four new methods to con_gure the ACDC, and compare them with existingmethods. Unlike those in previous studies, our proposed methods provide speci_c ACDC con_gurationsfor the different phases of a given task, instead of a single ACDC con_guration per task. We evaluate theWCET bounds obtained when using different ACDC con_guration methods on the TACLeBench benchmark suite. Our results show that the most complex benchmarks work better with multiple-content con_gurations,which indicates that realistic tasks may also bene_t from this kind of con_guration. The methods proposedin this study improve the WCET in more than 60% of cases, with an average WCET improvement of nearly5% and up to 50% in some cases. | es_ES |
dc.description.sponsorship | This work was supported in part by the Ministerio de Ciencia e Innovacion (MCIN)/Agencia Estatal de Investigacion (AIE)/10.13039/501100011033 under Grant PID2019-105660RB-C21 and Grant PID2020-117713RB-I00; and in part by the Government of Aragon, Research Group, under Grant T5820R. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation.ispartof | IEEE Access | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | ACDC | es_ES |
dc.subject | WCET | es_ES |
dc.subject | Data cache | es_ES |
dc.subject | Real-time | es_ES |
dc.subject | Genetic algorithms | es_ES |
dc.subject | Static analysis | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | Improving the Configuration of the Predictable ACDC Data Cache for Real-Time Systems | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1109/ACCESS.2022.3230068 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105660RB-C21/ES/JERARQUIA DE MEMORIA, GESTION DE TAREAS Y OPTIMIZACION DE APLICACIONES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Gobierno de Aragón//T58 20R/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-117713RB-I00/ES/WIMOSA. SISTEMA WIRELESS DE MONITORIZACION CONTINUA PARA LA SALVAGUARDA DEL PATRIMONIO/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica | es_ES |
dc.description.bibliographicCitation | Segarra, J.; Martí-Campoy, A. (2022). Improving the Configuration of the Predictable ACDC Data Cache for Real-Time Systems. IEEE Access. 10:132708-132724. https://doi.org/10.1109/ACCESS.2022.3230068 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/ACCESS.2022.3230068 | es_ES |
dc.description.upvformatpinicio | 132708 | es_ES |
dc.description.upvformatpfin | 132724 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 10 | es_ES |
dc.identifier.eissn | 2169-3536 | es_ES |
dc.relation.pasarela | S\479885 | es_ES |
dc.contributor.funder | Gobierno de Aragón | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |