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https://doi.org/10.3390/jlpea10040031
Title: | Pkmin: Peak power minimization for multi-threaded many-core applications | Authors: | Maity, A. Pathania, A. Mitra, T. |
Keywords: | Directed acyclic task graphs Many-core Peak-power management |
Issue Date: | 2020 | Publisher: | MDPI AG | Citation: | Maity, A., Pathania, A., Mitra, T. (2020). Pkmin: Peak power minimization for multi-threaded many-core applications. Journal of Low Power Electronics and Applications 10 (4) : 1-15. ScholarBank@NUS Repository. https://doi.org/10.3390/jlpea10040031 | Rights: | Attribution 4.0 International | Abstract: | Multiple multi-threaded tasks constitute a modern many-core application. An accompanying generic Directed Acyclic Graph (DAG) represents the execution precedence relationship between the tasks. The application comes with a hard deadline and high peak power consumption. Parallel execution of multiple tasks on multiple cores results in a quicker execution, but higher peak power. Peak power single-handedly determines the involved cooling costs in many-cores, while its violations could induce performance-crippling execution uncertainties. Less task parallelization, on the other hand, results in lower peak power, but a more prolonged deadline violating execution. The problem of peak power minimization in many-cores is to determine task-to-core mapping configuration in the spatio-temporal domain that minimizes the peak power consumption of an application, but ensures application still meets the deadline. All previous works on peak power minimization for many-core applications (with or without DAG) assume only single-threaded tasks. We are the first to propose a framework, called PkMin, which minimizes the peak power of many-core applications with DAG that have multi-threaded tasks. PkMin leverages the inherent convexity in the execution characteristics of multi-threaded tasks to find a configuration that satisfies the deadline, as well as minimizes peak power. Evaluation on hundreds of applications shows PkMin on average results in 49.2% lower peak power than a similar state-of-the-art framework. © 2020 by the authors. | Source Title: | Journal of Low Power Electronics and Applications | URI: | https://scholarbank.nus.edu.sg/handle/10635/199305 | ISSN: | 20799268 | DOI: | 10.3390/jlpea10040031 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
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