Energy-efficient task allocation techniques for asymmetric multiprocessor embedded systems
Energy-efficient task allocation techniques for asymmetric multiprocessor embedded systems
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DOI：
10.1145/2544375.2544391
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发表时间：
2014-01
期刊：
影响因子：
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通讯作者：
A. Elewi;M. Shalan;M. Awadalla;E. Saad
中科院分区：
文献类型：
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作者：
A. Elewi;M. Shalan;M. Awadalla;E. Saad
非对称多处理器系统被认为是功率高效的多处理器架构。此外，有效的任务分配（分区）可以在这些非对称多处理器平台上实现更高的能源效率。本文讨论了非对称多处理器（多核）嵌入式系统上周期性实时任务的能量感知静态划分问题。本文根据该平台支持的动态电压频率调整模型对该问题进行了形式化描述，证明了该问题是一个NP难问题。然后，文章概述了最佳参考分区技术的DVFS模型的每一种情况下，适当的假设。最后，文章提出了对传统装箱技术的修改，并结合平台支持的DVFS模型设计了新的装箱技术。对各种算法和技术进行了仿真和比较。模拟显示了有希望的结果，与传统方法相比，当不支持DVFS时，所提出的技术将能耗降低了75%，当平台支持每核DVFS时，将能耗降低了50%。
Asymmetric multiprocessor systems are considered power-efficient multiprocessor architectures. Furthermore, efficient task allocation (partitioning) can achieve more energy efficiency at these asymmetric multiprocessor platforms. This article addresses the problem of energy-aware static partitioning of periodic real-time tasks on asymmetric multiprocessor (multicore) embedded systems. The article formulates the problem according to the Dynamic Voltage and Frequency Scaling (DVFS) model supported by the platform and shows that it is an NP-hard problem. Then, the article outlines optimal reference partitioning techniques for each case of DVFS model with suitable assumptions. Finally, the article proposes modifications to the traditional bin-packing techniques and designs novel techniques taking into account the DVFS model supported by the platform. All algorithms and techniques are simulated and compared. The simulation shows promising results, where the proposed techniques reduced the energy consumption by 75% compared to traditional methods when DVFS is not supported and by 50% when per-core DVFS is supported by the platform.