On the Effects of Data-Aware Allocation on Fully Distributed Storage Systems for Exascale

被引：0

作者：

Pascual, Jose A. ^{[1
]}

Concatto, Caroline ^{[1
]}

Lant, Joshua ^{[1
]}

Navaridas, Javier ^{[1
]}

机构：

[1] Univ Manchester, Comp Sci Sch, Manchester, Lancs, England

来源：

EURO-PAR 2017: PARALLEL PROCESSING WORKSHOPS | 2018年 / 10659卷

关键词：

Near-data computing; Scheduling; Resource allocation;

D O I：

10.1007/978-3-319-75178-8_58

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The convergence between computing- and data-centric workloads and platforms is imposing new challenges on how to best use the resources of modern computing systems. In this paper we show the need of enhancing system schedulers to differentiate between compute- and data-oriented applications to minimise interferences between storage and application traffic. These interferences can be especially harmful in systems featuring fully distributed storage systems together with unified interconnects, such as our custom-made architecture ExaNeSt. We analyse several data-aware allocation strategies, and found that such strategies are essential to maintain performance in distributed storage systems.

引用

页码：725 / 736

页数：12

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