Item type |
Symposium(1) |
公開日 |
2021-03-15 |
タイトル |
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タイトル |
Predictive Many-core Allocation Method for Edge Off-Road Services |
タイトル |
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言語 |
en |
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タイトル |
Predictive Many-core Allocation Method for Edge Off-Road Services |
言語 |
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言語 |
eng |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
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資源タイプ |
conference paper |
著者所属 |
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Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology |
著者所属 |
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VA Linux Systems Japan K K |
著者所属 |
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Tokai University |
著者所属 |
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Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology |
著者所属(英) |
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en |
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Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology |
著者所属(英) |
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en |
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VA Linux Systems Japan K K |
著者所属(英) |
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en |
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Tokai University |
著者所属(英) |
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en |
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Department of Information Science and Engineering, College of Engineering, Shibaura Institute of Technology |
著者名 |
Masato, Fukui
Yoichi, Ishiwata
Takeshi, Ohkawa
Midori, Sugaya
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著者名(英) |
Masato, Fukui
Yoichi, Ishiwata
Takeshi, Ohkawa
Midori, Sugaya
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論文抄録 |
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内容記述タイプ |
Other |
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内容記述 |
In recent years, edge computing has been attracting attention for the purpose of offloading advanced processing by IoT and robot services. It needs to efficiently provide services to multiple robotics services while dynamically switching abundant computational resources such as many-core resources. In Many-core research, many studies have been conducted to increase the degree of parallelism of tasks to improve responsiveness and computational efficiency. However, there is still not enough discussion on how to effectively allocate resources in a way that is suitable for integrated services and to achieve both efficiency and responsiveness. In this study, we construct an efficient resource allocation prediction formula as a study of an efficient Many-core allocation method for edge offload. In addition, as a specific service, we decided to evaluate the offload of AI processing of communication robots. In the construction of the prediction formula, it was confirmed that sufficient processing performance and responsiveness can be obtained with the minimum core by automatically calculating the optimum number of cores from the actual application operation. |
論文抄録(英) |
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内容記述タイプ |
Other |
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内容記述 |
In recent years, edge computing has been attracting attention for the purpose of offloading advanced processing by IoT and robot services. It needs to efficiently provide services to multiple robotics services while dynamically switching abundant computational resources such as many-core resources. In Many-core research, many studies have been conducted to increase the degree of parallelism of tasks to improve responsiveness and computational efficiency. However, there is still not enough discussion on how to effectively allocate resources in a way that is suitable for integrated services and to achieve both efficiency and responsiveness. In this study, we construct an efficient resource allocation prediction formula as a study of an efficient Many-core allocation method for edge offload. In addition, as a specific service, we decided to evaluate the offload of AI processing of communication robots. In the construction of the prediction formula, it was confirmed that sufficient processing performance and responsiveness can be obtained with the minimum core by automatically calculating the optimum number of cores from the actual application operation. |
書誌情報 |
Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform
巻 2020,
p. 46-50,
発行日 2021-03-15
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出版者 |
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言語 |
ja |
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出版者 |
情報処理学会 |