Deciphering Predictive Schedulers for Heterogeneous-ISA Multicore Architectures

Deciphering Predictive Schedulers for Heterogeneous-ISA Multicore Architectures
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解读异构 ISA 多核架构的预测调度程序

DOI:
10.1145/3303084.3309492
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发表时间:
2019
期刊:
Proceedings of the 10th International Workshop on Programming Models and Applications for Multicores and Manycores
影响因子:
--
通讯作者:
Tullsen, Dean M.
Tullsen, Dean M.
中科院分区:
--
文献类型:
--
作者:
Prodromou, Andreas;Venkat, Ashish;Tullsen, Dean M.

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异构架构变得越来越普遍。从共同封装小型和大型内核,到 GPU 与 CPU 并存,再到内核实现不同 ISA 的通用异构 ISA 架构。随着执行核心多样性的增长,预测模型对于调度和资源分配变得至关重要。在本文中,我们研究了异构 ISA 设置中性能预测器的功能,以及预测器对调度程序质量的影响。我们遵循无偏见的特征选择方法来确定此任务的最佳特征集,而不是在训练之前预先选择特征。我们提出了弥合传统预测准确性指标和调度程序性能之间差距的指标。我们进一步介绍了我们的评估方法,该方法是根据本研究精心设计的,最后,我们将我们的发现纳入基于机器学习的调度程序中,并评估它们对底层系统异质性水平的敏感性。
Heterogeneous architectures have become increasingly common. From co-packaging small and large cores, to GPUs alongside CPUs, to general-purpose heterogeneous-ISA architectures with cores implementing different ISAs. As diversity of execution cores grows, predictive models become of paramount importance for scheduling and resource allocation. In this paper, we investigate the capabilities of performance predictors in a heterogeneous-ISA setting, as well as the predictors' effects on scheduler quality. We follow an unbiased feature selection methodology to identify the optimal set of features for this task, instead of pre-selecting features before training. We propose metrics that bridge the gap between traditional prediction accuracy metrics and a scheduler's performance. We further present our evaluation methodology, which was meticulously designed with this study in mind, and finally, we incorporate our findings in ML-based schedulers and evaluate their sensitivity to the underlying system's level of heterogeneity.
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