Task scheduling on a many-core processor for high-volume throughput applications

doi:10.16511/j.cnki.qhdxxb.2017.26.004

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Abstract Big data applications with high-volume throughputs have become the most common applications in datacenters. The efficiencies of these applications running on traditional processors are very low for various reasons, one of which is the low-efficiency task scheduling. This paper presents a task scheduling framework that identifies program behavior and the running environment and then partitions the cores with hierarchical task scheduling though hardware and software co-design to reduce the negative effect of shared resource contention and improving the instruction cache hit rate using thread similarity. Tests show this algorithm improves performance by 20% on average over the legacy work-stealing scheduling algorithm.

Keywords many-core processor big data applications high-volume throughput task scheduling

ZTFLH:

TP316

Issue Date: 15 March 2017

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	XU Yuanchao
	YANG Lu

Cite this article:

XU Yuanchao,YANG Lu. Task scheduling on a many-core processor for high-volume throughput applications[J]. Journal of Tsinghua University(Science and Technology), 2017, 57(3): 244-249.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2017.26.004 OR http://jst.tsinghuajournals.com/EN/Y2017/V57/I3/244

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