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Contention-aware prediction for performance impact of task co-running in multicore computers
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Ren, Shenyuan, He, Ligang, Li, Junyu, Chen, Zhiyan, Jiang, Peng and Li, Chang-Tsun (2019) Contention-aware prediction for performance impact of task co-running in multicore computers. Wireless Networks . pp. 1-8. doi:10.1007/s11276-018-01902-7 ISSN 1022-0038.
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Official URL: http://dx.doi.org/10.1007/s11276-018-01902-7
Abstract
In this paper, we investigate the influential factors that impact on the performance when the tasks are co-running on a multicore computers. Further, we propose the machine learning-based prediction framework to predict the performance of the co-running tasks. In particular, two prediction frameworks are developed for two types of task in our model: repetitive tasks (i.e., the tasks that arrive at the system repetitively) and new tasks (i.e., the task that are submitted to the system the first time). The difference between which is that we have the historical running information of the repetitive tasks while we do not have the prior knowledge about new tasks. Given the limited information of the new tasks, an online prediction framework is developed to predict the performance of co-running new tasks by sampling the performance events on the fly for a short period and then feeding the sampled results to the prediction framework. We conducted extensive experiments with the SPEC2006 benchmark suite to compare the effectiveness of different machine learning methods considered in this paper. The results show that our prediction model can achieve the accuracy of 99.38% and 87.18% for repetitive tasks and new tasks, respectively.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Journal or Publication Title: | Wireless Networks | ||||
Publisher: | Springer | ||||
ISSN: | 1022-0038 | ||||
Official Date: | 13 February 2019 | ||||
Dates: |
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Page Range: | pp. 1-8 | ||||
DOI: | 10.1007/s11276-018-01902-7 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Open Access (Creative Commons) |
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