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PARS: A scheduling of periodically active rank to optimize power efficiency for main memory

机译:PARS:定期活动等级的调度,以优化主存储器的电源效率

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The growing gap between microprocessor speed and DRAM speed is a major problem that computer designers are facing. In order to narrow the gap, main memory is expected to grow significantly in both speed and capacity for it is a major shared resource among cores in a multi-core system, which will lead to increasing power consumption, perhaps replacing the dominant consuming fraction of processor. Therefore, it is critical to address the power issue without seriously decreasing performance in the main memory subsystem. In this paper, we propose a periodically active rank scheduling (PARS) to optimize power efficiency for DRAM in smart phones. Our scheduling features a three-step design. First, we partition all threads in the system into groups. Second, we modify page allocation policy to achieve threads in the same group which occupies the same rank but different banks of DRAM. Finally, we sequentially schedule threads in one group after another while only active running group's ranks to retain other ranks low power status. As a result, our scheduling periodically activates one rank after another to optimize memory power efficiency. We implement PARS in Linux 2.6.39 kernel running randomly generated workloads containing single-threaded and multi-threaded benchmark. Experimental results show that PARS can improve both the memory power efficiency by 26.8% and performance by 4.2% average relative to default system while reducing negligible fairness. (C) 2015 Elsevier Ltd. All rights reserved.
机译:微处理器速度和DRAM速度之间日益扩大的差距是计算机设计人员面临的主要问题。为了缩小差距,主内存预计将在速度和容量上显着增长,因为它是多核系统中内核之间的主要共享资源,这将导致功耗增加,也许可以替代主要的消耗部分。处理器。因此,在不严重降低主内存子系统性能的情况下解决电源问题至关重要。在本文中,我们提出了一种周期性活动等级调度(PARS),以优化智能手机中DRAM的电源效率。我们的日程安排采用三步设计。首先,我们将系统中的所有线程划分为多个组。其次,我们修改页面分配策略,以在同一组中使用线程,这些线程占用相同的等级,但存储体不同。最后,我们依次在一个组中依次调度线程,而只有活动的运行组的级别保留其他级别的低功耗状态。结果,我们的调度会定期激活一个级别,以优化内存的能效。我们在Linux 2.6.39内核中实现PARS,该内核运行随机生成的包含单线程和多线程基准的工作负载。实验结果表明,相对于默认系统,PARS可以将内存电源效率平均提高26.8%,性能平均提高4.2%,同时降低可忽略的公平性。 (C)2015 Elsevier Ltd.保留所有权利。

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