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Curbing energy cravings in networks: A cross-sectional view across the micro-macro boundary

机译:遏制网络中的能源渴望:跨越微宏边界的横截面图

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The soaring power dissipation of computing infrastructures has effectively become a key performance bottleneck. At the same time, thermal issues arising from power hungry devices result in compromising reliability of such systems. At present, the processor cores within a chip multiprocessor (CMP) are interconnected using on-chip networks. At the same time, the emerging era of cloud computing and the associated large-scale distributed computing model are stretching the limits of computer networking. Hence, as an essential and pervasive fabric that binds all computing machinery, there is an underlying network that appears with varying scale and characteristics. In this paper, we take a look at methodologies for better management of the power budget across the cross-section of computing systems traversing the boundary between micro-level on-chip networks to macro-level cloud computing. We discuss methodologies for power and thermal management both at micro and macro scales and explore the role of one in reducing the power budget of the other.
机译:计算基础架构不断飙升的功耗实际上已成为关键的性能瓶颈。同时,由耗电设备引起的散热问题会损害此类系统的可靠性。目前,芯片多处理器(CMP)内的处理器内核是使用片上网络互连的。同时,新兴的云计算时代和相关的大规模分布式计算模型正在扩展计算机网络的局限性。因此,作为绑定所有计算机器的基本且普遍的结构,存在一个具有不同规模和特征的底层网络。在本文中,我们着眼于跨微系统级网络与宏级云计算之间的边界,更好地管理整个计算系统横截面的功率预算的方法。我们讨论了微观和宏观尺度上的电源和热管理方法,并探讨了一种方法在减少另一种方法的功率预算中的作用。

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