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Coordinated Optimization of the Performance of Processors and Memory in a Heterogeneous System under Energy Constraints

机译:能量约束下异构系统中处理器和内存性能的协同优化

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摘要

As the power consumed by systems continues to increase, reducing their power consumption is one of the goals of system optimization. However, power consumption is also gradually becoming one of the important constraints that affects the design and implementation of the system. At present, research on optimization with energy constraints is mainly focused on optimizing the energy of the processors, but the energy consumed by off-chip memory accounts for a large proportion of the total consumed by the whole system. In this research, we investigate the coordinated optimization of the performance of the processors and memory for a heterogeneous system subject to energy constraints. A communication-computation pipeline for parallel programs is constructed to optimize program performance by simultaneously scaling the voltage and frequency of the processors and memory using a task partition strategy. Our experimental results indicate that our method of optimizing system performance by coordinating task partition and frequency scaling under energy constraints can result in a satisfying execution time and processor profit and meet the given energy constraints.
机译:随着系统所消耗的功率不断增加,减少其功耗是系统优化的目标之一。但是,功耗也逐渐成为影响系统设计和实现的重要约束之一。当前,对具有能量约束的优化的研究主要集中在优化处理器的能量上,但是片外存储器消耗的能量在整个系统消耗的总能量中占很大比例。在这项研究中,我们研究受能量约束的异构系统的处理器和内存性能的协同优化。通过使用任务分配策略同时缩放处理器和内存的电压和频率,构建了用于并行程序的通信计算管道,以优化程序性能。我们的实验结果表明,通过在能量约束下协调任务分配和频率缩放来优化系统性能的方法可以产生令人满意的执行时间和处理器利润,并满足给定的能量约束。

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