XDRA: DDR dram中降低能耗的最后一级缓存的探索与优化

S. Min, Haris Javaid, S. Parameswaran
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引用次数: 5

摘要

高能耗的嵌入式系统通常利用DDR-DRAM的空闲状态,在空闲期间将DRAM置于深度低功耗模式(自刷新掉电模式)来降低能耗。DDR-DRAM空闲时间严重依赖于最后一级缓存。使用处理器-内存模拟器进行穷举搜索可能需要几个月的时间。本文首次提出了一种名为XDRA的快速框架,该框架允许探索最后一级缓存配置以提高DDR-DRAM的能量效率。XDRA结合了处理器-内存模拟器、缓存模拟器和新颖的分析技术,产生了一个基于Kriging的估计器,该估计器可以预测给定主内存大小和应用程序的不同缓存配置所节省的能源。对于来自mediabbench和SPEC2000套件的11个应用程序以及两种DRAM大小(Micron DDR3-DRAM 256MB和4GB),估计器的误差平均小于4.4%。XDRA选择的缓存配置的能源效率(缓存和DRAM能源)平均比普通缓存配置高3.6倍和4倍。在22次测试中,XDRA选出了20次最优缓存配置。这两个次优配置最多比最优配置低3.9%。与数百天的周期精确模拟相比,XDRA只花了几天时间就勘探了330种缓存配置,节省了至少85%的勘探时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
XDRA: Exploration and optimization of last-level cache for energy reduction in DDR DRAMs
Embedded systems with high energy consumption often exploit the idleness of DDR-DRAM to reduce their energy consumption by putting the DRAM into deepest low-power mode (self-refresh power down mode) during idle periods. DDR-DRAM idle periods heavily depend on the last-level cache. Exhaustive search using processor-memory simulators can take several months. This paper for first time proposes a fast framework called XDRA, which allows the exploration of last-level cache configurations to improve DDR-DRAM energy efficiency. XDRA combines a processor-memory simulator, a cache simulator and novel analysis techniques to produce a Kriging based estimator which predicts the energy savings for differing cache configurations for a given main memory size and application. Errors for the estimator were less than 4.4% on average for 11 applications from mediabench and SPEC2000 suite and two DRAM sizes (Micron DDR3-DRAM 256MB and 4GB). Cache configurations selected by XDRA were on average 3.6× and 4× more energy efficient (cache and DRAM energy) than a common cache configuration. Optimal cache configurations were selected by XDRA 20 times out of 22. The two suboptimal configurations were at most 3.9% from their optimal counterparts. XDRA took a few days for the exploration of 330 cache configurations compared to several hundred days of cycle-accurate simulations, saving at least 85% of exploration time.
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