循环链表自动和自我刷新架构

Aditya Agrawal, Mike O'Connor, Evgeny Bolotin, Niladrish Chatterjee, J. Emer, S. Keckler
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引用次数: 8

摘要

随着DRAM密度的增加,刷新操作的性能和能量开销也越来越大。当系统处于活动状态时,刷新命令使DRAM组不可用的时间越来越长。这些刷新操作可能会干扰常规的内存操作并影响性能。此外,当系统处于空闲状态时,DRAM的自我刷新是能耗的主要来源,它直接影响电池寿命和待机时间。先前的刷新减少技术寻求减少主动模式自动刷新能量、减少自刷新能量、提高性能或其某种组合。在本文中,我们提出了CLARA,一种基于循环链表的刷新架构,它以非常低的开销满足所有三个目标,并且不会牺牲DRAM容量。这种方法利用了芯片粒度上的保留时间变化,而不是先前工作中内存范围内的等级粒度。CLARA将自动刷新和自刷新降低了86.2%,与工作负载无关。在正常和扩展温度范围内,自动刷新减少使平均CPU性能分别提高3.1%和6.5%。在扩展的温度范围内,GPU性能平均提高2.1%。自刷新期间的DRAM空闲功率降低了44%。CLARA在DRAM中的面积开销约为0.085%,在内存控制器中可以忽略不计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CLARA: Circular Linked-List Auto and Self Refresh Architecture
With increasing DRAM densities, the performance and energy overheads of refresh operations are increasingly significant. When the system is active, refresh commands render DRAM banks unavailable for increasing periods of time. These refresh operations can interfere with regular memory operations and hurt performance. In addition, when the system is idle, DRAM self-refresh is the dominant source of energy consumption, and it directly impacts battery life and standby time. Prior refresh reduction techniques seek to reduce active-mode auto-refresh energy, reduce self-refresh energy, improve performance, or some combination thereof. In this paper, we present CLARA, a circular linked-list based refresh architecture which meets all three goals with very low overheads and without sacrificing DRAM capacity. This approach exploits the variation in retention time at a chip granularity as opposed to a DIMM-wide, rank granularity in prior work. CLARA reduces auto- and self-refresh by 86.2%, independent of workload. Auto refresh reduction improves average CPU performance by 3.1% and 6.5% in the normal and extended temperature range, respectively. GPU performance improves by 2.1% on average in the extended temperature range. DRAM idle power during self-refresh is reduced by 44%. The area overhead of CLARA in the DRAM is about 0.085% and negligible in the memory controller.
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