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Dynamic energy management for chip multi-processors under performance constraints

机译:性能约束下的芯片多处理器动态能源管理

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摘要

We introduce a novel algorithm for dynamic energy management (DEM) under performance constraints in chip multi-processors (CMPs). Using the novel concept of delayed instructions count, performance loss estimations are calculated at the end of each control period for each core. In addition, a Kalman filtering based approach is employed to predict workload in the next control period for which voltage-frequency pairs must be selected. This selection is done with a novel dynamic voltage and frequency scaling (DVFS) algorithm whose objective is to reduce energy consumption but without degrading performance beyond the user set threshold. Using our customized Sniper based CMP system simulation framework, we demonstrate the effectiveness of the proposed algorithm for a variety of benchmarks for 16 core and 64 core network-on-chip based CMP architectures. Simulation results show consistent energy savings across the board. We present our work as an investigation of the tradeoff between the achievable energy reduction via DVFS when predictions are done using the effective Kalman filter for different performance penalty thresholds. (C) 2017 Elsevier B.V. All rights reserved.
机译:我们介绍了一种在芯片多处理器(CMP)的性能约束下动态能量管理(DEM)的新颖算法。使用延迟指令计数的新颖概念,在每个内核的每个控制周期结束时计算性能损失估计。另外,采用基于卡尔曼滤波的方法来预测必须选择电压-频率对的下一控制周期中的工作量。这种选择是通过一种新颖的动态电压和频率缩放(DVFS)算法完成的,其目的是减少能耗,但又不会降低性能,而不会超出用户设置的阈值。使用我们定制的基于Sniper的CMP系统仿真框架,我们证明了该算法对于基于16核和64核基于芯片的CMP架构的各种基准的有效性。仿真结果显示了全面的节能效果。当使用针对不同性能损失阈值的有效卡尔曼滤波器进行预测时,我们通过DVFS可实现的能量减少之间的权衡取舍进行了研究。 (C)2017 Elsevier B.V.保留所有权利。

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