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Proactive thermal management using memory based computing

机译:使用基于内存的计算进行主动热管理

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Nanoscale devices provide the capability of gigascale integration in modern electronic systems. However, such systems suffer from high defect rates and large parametric variations. The surge of transistor count with the increased clock rate elevates the processor temperature which makes these systems even more unreliable and unstable. Dynamic Thermal Management (DTM) approaches considerably increase application's run-time in order to lower the peak temperature. Memory-based computing (MBC) is a promising approach to improve overall system reliability when few functional units are defective or unreliable under process-induced or thermal variations. In this paper, we present a novel DTM technique using proactive MBC to reduce the peak temperature of applications. We propose an efficient technique to proactively transfer the instructions with frequent operand pairs to memory. Experimental results demonstrate that the proposed proactive thermal management can significantly decrease the peak temperature to improve the system reliability with minor impact on performance.
机译:纳米级设备提供了在现代电子系统中进行千兆级集成的能力。但是,这样的系统遭受高缺陷率和大参数变化的困扰。随着时钟速率的增加,晶体管数量的激增会升高处理器温度,这会使这些系统更加不可靠和不稳定。动态热管理(DTM)方法可显着增加应用程序的运行时间,以降低峰值温度。当很少的功能单元在过程引起的或热的变化下有缺陷或不可靠时,基于内存的计算(MBC)是提高整体系统可靠性的一种有前途的方法。在本文中,我们提出了一种使用主动式MBC降低应用峰值温度的新颖DTM技术。我们提出了一种有效的技术,将具有频繁操作数对的指令主动转移到内存中。实验结果表明,所提出的主动热管理可以显着降低峰值温度,从而改善系统可靠性,而对性能的影响较小。

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