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- W3202353500 abstract "Recently, the use of interactive jobs in addition to traditional batch jobs is attracting attention in supercomputer systems. We expect overcommitting scheduling, in which multiple HPC jobs share computational resources, to accept them while keeping resource utilization higher and response time lower. In order to realize overcommitting scheduling, the following approaches are necessary: 1) to understand the impact on performance when various applications share resources, and 2) to predict the performance before overcommitting. With this knowledge, we will be able to optimize overcommitting scheduling that avoids performance degradation of jobs. In this paper, we describe the overall picture of overcommitting scheduling and took the two approaches shown above. We confirmed that overcommitting shows performance improvement of the overall system and also built a performance model that can be applied to job scheduling." @default.
- W3202353500 created "2021-10-11" @default.
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- W3202353500 date "2021-01-01" @default.
- W3202353500 modified "2023-09-25" @default.
- W3202353500 title "Measurement and Modeling of Performance of HPC Applications Towards Overcommitting Scheduling Systems" @default.
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- W3202353500 doi "https://doi.org/10.1007/978-3-030-88224-2_4" @default.
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