A hierarchical run-time adaptive resource allocation framework for large-scale MPSoC systems

被引:13
|
作者
Quan, Wei [1 ,2 ]
Pimentel, Andy D. [1 ]
机构
[1] Univ Amsterdam, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands
[2] Natl Univ Def Technol, Yanwachi Main St 47, Changsha 410073, Hunan, Peoples R China
关键词
Embedded systems; KPN; MPSoC; Task mapping; Simulation; MANAGEMENT; DESIGN;
D O I
10.1007/s10617-016-9179-z
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In the embedded computer system domain, MPSoC systems have become increasingly popular due to the ever-increasing performance demands of modern embedded applications. The number of processing elements in these MPSoCs also steadily increases. Whereas current MPSoCs still contain a limited number of processing elements, future MPSoCs will feature tens up to hundreds of (heterogeneous) processing elements that are all integrated on a single chip. On these future large-scale MPSoC systems, the mapping of applications onto the hardware resources plays an important role to fully explore the parallelism of applications. In this article, a hierarchical run-time adaptive resource allocation framework which uses an intelligent task remapping approach is proposed to improve the system performance for large-scale MPSoCs.
引用
收藏
页码:311 / 339
页数:29
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