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  • 标题:Task Scheduling Frameworks for Heterogeneous Computing Toward Exascale
  • 本地全文:下载
  • 作者:Suhelah Sandokji ; Fathy Eassa
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2018
  • 卷号:9
  • 期号:10
  • DOI:10.14569/IJACSA.2018.091029
  • 出版社:Science and Information Society (SAI)
  • 摘要:The race for Exascale Computing has naturally led computer architecture to transit from the multicore era and into the heterogeneous era. Many systems are shipped with integrated CPUs and graphics processing units (GPUs). Moreover, various applications need to utilize both CPUs and GPUs executive resources, as many of their unique features prove the significant importance and strengths of using each one of the process units PUs. Several research studies consider partitioning the applications, scheduling their execution and allocating them onto the PUs resources. They investigate the important role of optimization and tackle intelligently scheduled tasks on the combination of CPU/GPU architecture CPUs and GPUs cores in achieving the peace of performance and power consumption of Exascale Computing. In this paper, the evolution of heterogeneous computing architectures, the approaches, and challenges toward achieving Exascale Computing, and the various algorithms and techniques used to partition and scheduling tasks are all reviewed. The existing frameworks and runtime systems utilized to optimize performance and improve energy efficiency in desecrates and fused chips in order to attain the objectives of Exascale Computing will also be reviewed.
  • 关键词:Exascale computing; heterogenous computing; task scheduler framework
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