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A Fast Architecture-Level Thermal Analysis Method for Runtime Thermal Regulation

机译:用于运行时热调节的快速体系结构级热分析方法

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摘要

As power consumption and the corresponding heat dissipated on a die grow rapidly, efficient on-chip temperature regulation becomes imperative for today's high performance microprocessors. Temperature tracking based on the on-chip thermal sensors is not sufficient as the temperature hot spots keep changing with the load. One way to mitigate this problem is by means of software sensors, where temperature of any location is computed based on realtime power information and calibrated with the physical sensors. In this paper, we present a very efficient numerical thermal analysis method, which is suitable for fast temperature tracking and runtime thermal regulation. The proposed method, called FEKIS, combines two existing numerical techniques: extended Krylov subspace reduction technique to reduce the thermal circuit complexity and large-step integration method to exploit the sampled-based power input traces, which is typical in the power traces at the architectural and operation system levels. Experimental results show that FEKIS archives 10× speedup over recently proposed state-of-the art thermal moment matching technique and the precise time-step integration method only, and three orders of magnitude faster than the traditional numerical integration method with high accuracy.
机译:随着功耗和管芯上相应的散热迅速增长,有效的片上温度调节对于当今的高性能微处理器至关重要。由于温度热点会随着负载不断变化,因此基于片上热传感器的温度跟踪还不够。解决此问题的一种方法是借助软件传感器,其中任何位置的温度都是根据实时功率信息计算的,并使用物理传感器进行校准。在本文中,我们提出了一种非常有效的数值热分析方法,适用于快速温度跟踪和运行时热调节。所提出的方法称为FEKIS,它结合了两种现有的数值技术:扩展的Krylov子空间缩减技术以降低热电路的复杂性,以及大步积分方法来利用基于采样的电源输入迹线,这在建筑的电源迹线中很常见。和操作系统级别。实验结果表明,FEKIS的存档速度是最新提出的最先进的热矩匹配技术和精确的时间步长积分方法的10倍,并且比传统的数值积分方法快3个数量级,且具有较高的精度。

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