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孙奥林, 徐奇, 陈松. 暗硅多核系统芯片资源调度算法[J]. 计算机辅助设计与图形学学报, 2017, 29(6): 1145-1154.
引用本文: 孙奥林, 徐奇, 陈松. 暗硅多核系统芯片资源调度算法[J]. 计算机辅助设计与图形学学报, 2017, 29(6): 1145-1154.
Sun Aolin, Xu Qi, Chen Song. Resource Scheduling Algorithm for Multi-core System Chip with Dark Silicon[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(6): 1145-1154.
Citation: Sun Aolin, Xu Qi, Chen Song. Resource Scheduling Algorithm for Multi-core System Chip with Dark Silicon[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(6): 1145-1154.

暗硅多核系统芯片资源调度算法

Resource Scheduling Algorithm for Multi-core System Chip with Dark Silicon

  • 摘要: 芯片集成度的提升芯片带来功耗密度的增加,引起芯片的过热问题.近年来,人们提出暗硅设计的概念,有选择地关闭部分工作模块,避免芯片上所有模块同时处于开启状态,以解决过热问题.为此,提出一种基于模拟退火的多核系统资源调度算法.针对具体的应用采用迭代方法调整热设计功耗约束、分配处理器资源,并确定芯片模块的开启和关闭,在保证系统吞吐的同时,有效地解决芯片的过热问题.首先,针对已知应用集,在热设计功耗和系统约束下通过动态规划为每个应用配置处理器数目和频率等级.其次,基于模拟退火算法以散热效果和通信延迟为目标完成应用映射,确定开启和关闭的处理器.最后,根据有无过热点的反馈,迭代地调整热设计功耗大小,获得系统最大热设计功耗,并据此获得应用的最终资源配置和映射结果.所提调度方法能够有效地避免过热点,在资源约束下最优化系统性能.实验结果表明,相比于棋盘式布局,系统最高温度能够降低3%,相比开关调整过热点的方法,系统吞吐量能够最大增加约12%.

     

    Abstract: With the increasing chip integration, the power density has been rising and results in on-chip thermal emergency. Recently, the dark silicon designs are proposed to avoid the hotspot, where all the fractions of chip resources cannot be simultaneously powered on. Consequently, we need reasonably determine which fraction should be powered on to ensure the throughput requirements. In this paper, we proposed a resource scheduling method for the multi-core system with dark silicon design. First of all, given a set of applications, we extracted the throughput and power consumption of each application under all the possible processor number and frequency configuration, which are constrained by the system resources and power budget, The resource configuration problem was solved by a dynamic programming-based method. Secondly, with the configuration, a simulated annealing based method is used to map the application and determine the distribution of dark cores and active cores on the system with minimization of the thermal costs and communication costs. Finally, according to the feedback of whether there exist hotspots in the system, a loop based thermal design power adaption method was used to obtain maximum power budget and avoid temperature violation. Experimental results show that, in comparison with chess mapping approach, the maximum temperature can be decreased about 3% at best. Additionally, we obtain 12% gain in performance when compared with power down hotspot adaption.

     

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