Mapping Method Usable with Clustered Many-core Platforms for Simulink Model

• Item type: Journal(1)
• 公開日: 2022-02-15
• タイトル: Mapping Method Usable with Clustered Many-core Platforms for Simulink Model
• タイトル / 言語: en
• タイトル: Mapping Method Usable with Clustered Many-core Platforms for Simulink Model
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集:組込みシステム工学] embedded systems, model-based development, multi/many-core
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Graduate School of Science and Engineering, Saitama University
• 著者所属: Graduate School of Science and Engineering, Saitama University
• 著者所属: Graduate School of Engineering Science, Osaka University
• 著者所属: Technology Headquarters, eSOL Co., Ltd.
• 著者所属: Graduate School of Informatics, Nagoya University
• 著者所属: Graduate School of Science and Engineering, Saitama University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Engineering, Saitama University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Engineering, Saitama University
• 著者所属(英): en
• 著者所属(英): Graduate School of Engineering Science, Osaka University
• 著者所属(英): en
• 著者所属(英): Technology Headquarters, eSOL Co., Ltd.
• 著者所属(英): en
• 著者所属(英): Graduate School of Informatics, Nagoya University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Engineering, Saitama University
• 著者名: Yutaro, Kobayashi; Kentaro, Honda; Sasuga, Kojima; Hiroshi, Fujimoto; Masato, Edahiro; Takuya, Azumi
• 著者名(英): Yutaro, Kobayashi; Kentaro, Honda; Sasuga, Kojima; Hiroshi, Fujimoto; Masato, Edahiro; Takuya, Azumi
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Multi/many-core processors are being increasingly used to reduce power consumption and improve performance. The use of model-based development for embedded systems has also been increasing. Relative to these trends, the model-based parallelizer or MBP has an essential role in parallelizing applications at the model level. MBP maps Simulink blocks to cores using various types of information such as block characteristics, C code, and multi/many-core hardware implementation. However, MBP does not consider many-core hardware with cluster structures such as Kalray MPPA2-256 processor which contains 16 clusters of 16 cores for 256 general-purpose cores in total. This paper proposes an algorithm that determines core allocations by considering cluster structures. The proposed algorithm combines two other algorithms: one algorithm uses the core allocation of MBP and path analysis at the cluster-level and considers effects from communication contention when determining cluster allocations, and the other algorithm uses the results from MBP and remaps cluster allocations. The proposed algorithm produces better results than its component algorithms could produce separately. Evaluations demonstrate that the proposed algorithm obtained the best results among four methods in terms of execution time on Simulink models.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.30(2022) (online); DOI http://dx.doi.org/10.2197/ipsjjip.30.141; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Multi/many-core processors are being increasingly used to reduce power consumption and improve performance. The use of model-based development for embedded systems has also been increasing. Relative to these trends, the model-based parallelizer or MBP has an essential role in parallelizing applications at the model level. MBP maps Simulink blocks to cores using various types of information such as block characteristics, C code, and multi/many-core hardware implementation. However, MBP does not consider many-core hardware with cluster structures such as Kalray MPPA2-256 processor which contains 16 clusters of 16 cores for 256 general-purpose cores in total. This paper proposes an algorithm that determines core allocations by considering cluster structures. The proposed algorithm combines two other algorithms: one algorithm uses the core allocation of MBP and path analysis at the cluster-level and considers effects from communication contention when determining cluster allocations, and the other algorithm uses the results from MBP and remaps cluster allocations. The proposed algorithm produces better results than its component algorithms could produce separately. Evaluations demonstrate that the proposed algorithm obtained the best results among four methods in terms of execution time on Simulink models.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.30(2022) (online); DOI http://dx.doi.org/10.2197/ipsjjip.30.141; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 63, 号 2, 発行日 2022-02-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764