Memory-aware energy-optimal frequency assignment for dynamic supply voltage scaling

Youngjin Cho, N. Chang
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引用次数: 27

Abstract

Dynamic supply voltage scaling (DVS) is one of the best ways to reduce the energy consumption of a device when there is a super-linear relationship between energy and supply voltage, and a pseudo-linear relationship between delay and supply voltage. However, most DVS schemes scale the clock frequency of the supply-voltage-clock-scalable (SVCS) CPU only and do not address the energy consumption of the memory. The memory is generally non-supply-voltage-scalable (NSVS), but its energy consumption is variable to its clock frequency and the total execution time. Thus, DVS for an SVCS CPU cannot achieve an optimal system-wide energy saving without consideration of the memory, as far as it is controlled by an SVCS CPU. We introduce an energy-optimal frequency assignment, for both an SVCS CPU and a synchronous NSVS memory, which optimizes the system-wide energy consumption. We derive the energy-optimal clock frequencies for an SVCS CPU and a synchronous NSVS memory, as a function of the number of processor clock cycles, the number of memory accesses and the hardware energy model. Our technique modifies the frequency assignment of the CPU and the memory used in previous DVS schemes, which ignore the memory energy. It enables the system-wide energy-optimal settings and achieves additional 50% energy reduction over previous DVS schemes. This technique can also be applicable to synchronous NSVS peripheral devices.
动态电源电压标度的记忆感知能量最优频率分配
当能量与电源电压呈超线性关系,延迟与电源电压呈伪线性关系时,动态电源电压缩放(DVS)是降低器件能耗的最佳途径之一。然而,大多数分布式交换机方案只缩放SVCS (supply-voltage-clock-scalable) CPU的时钟频率,而不解决内存的能耗问题。内存通常是非供电电压可伸缩的(nsv),但其能耗随其时钟频率和总执行时间而变化。因此,SVCS CPU的分布式交换机在受SVCS CPU控制的情况下,如果不考虑内存,就无法实现最优的全系统节能。我们为SVCS CPU和同步nscs存储器引入了能量最优频率分配,从而优化了系统范围的能量消耗。我们导出了SVCS CPU和同步NSVS存储器的能量最优时钟频率,作为处理器时钟周期数、存储器访问数和硬件能量模型的函数。我们的技术修改了在以前的分布式交换机方案中使用的CPU和内存的频率分配,这些方案忽略了内存能量。它可以实现全系统的能量优化设置,并实现比以前的分布式交换机方案额外减少50%的能量。该技术也适用于同步nsv外围设备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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