{"title":"Estimation Method Considering OS Overheads for Embedded Many-Core Platform","authors":"K. Honda, Hiroshi Fujimoto, Takuya Azumi","doi":"10.1109/EUC50751.2020.00011","DOIUrl":null,"url":null,"abstract":"Embedded systems such as automotive systems require high computational power and low power consumption. To meet these requirements, many-core processors have attracted attention. Compared with single-core processors, many-core processors can execute multiple processes in parallel, allowing for improved power consumption and performance. Due to their performance, many-core processors can be used in automotive systems which have strict real-time requirements. Therefore, it is important to obtain accurate hardware and software information. In this paper, we propose a method for estimating the execution time of an application supported by MATLAB/Simulink on a many-core platform. The proposed method considers operating system (OS) overheads with a real-time OS and Kalray MPPA-256 cluster structure which contains many-core processors. The effectiveness, and the experimental results demonstrate that the proposed method is more accurate than existing methods.","PeriodicalId":331605,"journal":{"name":"2020 IEEE 18th International Conference on Embedded and Ubiquitous Computing (EUC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 18th International Conference on Embedded and Ubiquitous Computing (EUC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUC50751.2020.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Embedded systems such as automotive systems require high computational power and low power consumption. To meet these requirements, many-core processors have attracted attention. Compared with single-core processors, many-core processors can execute multiple processes in parallel, allowing for improved power consumption and performance. Due to their performance, many-core processors can be used in automotive systems which have strict real-time requirements. Therefore, it is important to obtain accurate hardware and software information. In this paper, we propose a method for estimating the execution time of an application supported by MATLAB/Simulink on a many-core platform. The proposed method considers operating system (OS) overheads with a real-time OS and Kalray MPPA-256 cluster structure which contains many-core processors. The effectiveness, and the experimental results demonstrate that the proposed method is more accurate than existing methods.
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