Characterization, modeling and scheduling of power consumption of scientific computing applications in multicores
Cluster Computing, ISSN: 1573-7543, Vol: 22, Issue: 3, Page: 839-859
2019
- 16Citations
- 14Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
This article presents an empirical evaluation of power consumption for scientific computing applications in multicore systems. Three types of applications are studied, in single and combined executions on Intel and AMD servers, for evaluating the overall power consumption of each application. The main results indicate that power consumption behavior has a strong dependency with the type of application. Additional performance analysis shows that the best load of the server regarding energy efficiency depends on the type of the applications, with efficiency decreasing in heavily loaded situations. These results allow formulating a model to characterize applications according to power consumption, efficiency, and resource sharing, which provide useful information for resource management and scheduling policies. Several scheduling strategies are evaluated using the proposed energy model over realistic scientific computing workloads. Results confirm that strategies that maximize host utilization provide the best energy efficiency and performance results.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85059580776&origin=inward; http://dx.doi.org/10.1007/s10586-018-2882-8; http://link.springer.com/10.1007/s10586-018-2882-8; http://link.springer.com/content/pdf/10.1007/s10586-018-2882-8.pdf; http://link.springer.com/article/10.1007/s10586-018-2882-8/fulltext.html; https://dx.doi.org/10.1007/s10586-018-2882-8; https://link.springer.com/article/10.1007/s10586-018-2882-8
Springer Science and Business Media LLC
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