随机异构多核处理器中的调度算法

Yan Liu, Yongwei Li, Yihong Zhao, Xiao-Mou. Chen
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引用次数: 2

摘要

随着多核处理器规模的不断扩大,多核处理器可能会由于设计或多样性和缺陷而出现随机异构。后一种类型的异质性由一些不可预见的可变因素(如制造过程的变化)引入,由于其不可预测性而特别具有挑战性。在这种环境下,线程调度器和全局电源管理器必须处理这种随机异构。此外,这些算法必须提供高效率、可扩展性和低开销,因为未来的多核处理器可能在单个芯片上有多个核。本文提出了一种用于应用程序调度和电源管理的变化感知调度算法。在多核处理器中,不同核之间的线程切换和采样比以往的多核调度算法带来了明显的开销。该方案记录优先核心交换线程的信息,并采用基于禁忌搜索的随机异构调度算法(TSR)避免重复采样的发生,降低线程的迁移频率和采样频率。实验结果表明,与局部搜索算法相比,TSR算法可减少45.7%的线程迁移和42.2%的采样时间。本文以超越匈牙利离线调度算法为基准。与匈牙利离线调度算法相比,TSR算法的ED2仅下降了8.58%,但与随机搜索调度算法相比,TSR算法的ED2下降了39.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A scheduling algorithm in the randomly heterogeneous multi-core processor
The increasing scale of multi-core processors are likely to be randomly heterogeneous by design or because of diversity and flaws. The latter type of heterogeneity introduced by some unforeseen variable factors such as the manufacturing process variation is especially challenging because of its unpredictability. In this environment, thread scheduler and global power manager must handle such randomly heterogeneous. Furthermore, these algorithms must supply high efficiency, scalability and low overhead because future multi-core processors may have a number of cores on a single die. This paper presents a variation-aware scheduling algorithm for application scheduling and power management. Thread switching and sampling among different cores in the multi-core processor introduce obvious overhead than previous many-core scheduling algorithms. Proposed scheme records the information of swapped thread of preferential core and uses tabu search-based randomly heterogeneous scheduling algorithm(TSR) to avoid the occurrence of repeated sampling and reduce the migration frequency and sampling frequency of a thread. The experimental results show that TSR algorithm has decreased 45.7% of thread migration and 42.2% of the sampling time as compared with local search algorithm. This paper regards the transcendental Hungarian offline scheduling algorithm as the baseline. ED2 of TSR only decrease by 8.58% as compared with that of Hungarian offline scheduling algorithm, but compared with the random search scheduling algorithm, ED2 of TSR decreased by 39.4%.
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