多通道存储系统的能量感知动态数据分配机制

Masayuki Sato, Takuya Toyoshima, Hikaru Takayashiki, Ryusuke Egawa, Hiroaki Kobayashi
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引用次数: 0

摘要

现代的存储系统配备了许多存储通道,以获得较高的存储带宽。为了利用这种组织,应用程序的数据分布在通道之间,并以交错的方式传输。尽管内存密集型应用程序可以从许多内存通道的高带宽中受益,但诸如计算密集型应用程序之类的应用程序并不需要高带宽。为了降低此类应用的能耗,存储器系统具有低功耗模式。在无内存请求时,主存可以进入这些模式,降低能耗。然而,这些应用程序通常会对处理其数据的通道发出间歇性的内存请求,从而导致无法进入低功耗模式。因此,即使应用程序不需要高带宽,存储系统也无法进入低功耗模式。为了解决这一问题,本文提出了一种多通道存储系统的动态数据分配机制。该机制通过动态更改地址映射方案和迁移数据,强制此类应用程序的数据使用指定的通道。这样,没有分配数据的其他信道就有机会长时间进入低功耗模式。因此,所提出的机制有可能降低多通道存储系统的能量消耗。评价结果表明,该机制可使能耗平均降低11.8%和1.7%。
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An Energy-aware Dynamic Data Allocation Mechanism for Many-channel Memory Systems
A modern memory system is equipped with many memory channels to obtain a high memory bandwidth. To take the advantage of this organization, applications’ data are distributed among the channels and transferred in an interleaved fashion. Although memory-intensive applications benefit from a high bandwidth by many memory channels, applications such as compute-intensive ones do not need the high bandwidth. To reduce the energy consumption for such applications, the memory system has low-power modes. During no memory request, the main memory can enter these modes and reduce energy consumption. However, these applications often cause intermittent memory requests to the channels that handle their data, resulting in not entering the low-power modes. Hence, the memory system cannot enter the low-power modes even though the applications do not need the high bandwidth. To solve this problem, this paper proposes a dynamic data allocation mechanism for many-channel memory systems. This mechanism forces data of such applications to use the specified channels by dynamically changing the address-mapping schemes and migrating the data. As a result, the other channels to which the data are not allocated can have a chance to enter the low-power modes for a long time. Therefore, the proposed mechanism has the potential to reduce the energy consumption of many-channel memory systems. The evaluation results show that this mechanism can reduce the energy consumption by up to 11.8% and 1.7% on average.
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