Affiliation
Department of Electrical & Computer Engineering, University of ArizonaIssue Date
2023-11-12
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Association for Computing MachineryCitation
Gener, S., Hassan, S., & Akoglu, A. (2023, November). Value-Based Resource Management at SoC Scale. In Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (pp. 1642-1650).Rights
© 2023 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Value-based resource management heuristics, which are traditionally deployed in heterogeneous HPC systems, maximize system productivity by assigning resources to each job based on its priority and estimated value gain relative to each job's completion time. We investigate the utility of value-based resource management at heterogeneous SoC scale and demonstrate its ability to make effective scheduling decisions for time-constrained jobs in oversubscribed systems where system resources are shared by multiple users and applications arrive dynamically. The proposed value-based resource management approach drops tasks that are estimated to result with lower-value gain dynamically with the aim of completing more number of high-value jobs with a scheduling decision time at 120µ s scale. The value-based resource management treats scheduling as a global optimization problem, therefore this study sets a path forward for deploying a unified value-based resource management on a system composed of front-end SoC-based edge devices and a back-end HPC system. © 2023 Owner/Author.Note
Open access articleISBN
979-840070785-8Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1145/3624062.3624243
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Except where otherwise noted, this item's license is described as © 2023 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.