存储缓存快速缺失率曲线建模

Xiameng Hu, Xiaolin Wang, Lan Zhou, Yingwei Luo, Zhenlin Wang, C. Ding, Chencheng Ye
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引用次数: 29

摘要

重用距离(LRU堆栈距离)是存储缓存性能预测和优化的重要指标。在过去的四十年中,重用距离测量的算法效率稳步提高。近年来,这一进展在理论和实际实施方面都在加速。在本文中,我们提出了一个基于缓存数据的平均清除时间(AET)的LRU缓存的动力学模型。AET模型可实现快速测量和使用低成本采样。它能以极低的空间成本在线性时间内生成脱靶率曲线。在存储跟踪基准测试中,与以前的技术相比,AET减少了时间和空间成本。此外,AET是一个可组合的模型,可以通过采样和建模单个程序或跟踪来表征共享缓存行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Miss Ratio Curve Modeling for Storage Cache
The reuse distance (least recently used (LRU) stack distance) is an essential metric for performance prediction and optimization of storage cache. Over the past four decades, there have been steady improvements in the algorithmic efficiency of reuse distance measurement. This progress is accelerating in recent years, both in theory and practical implementation. In this article, we present a kinetic model of LRU cache memory, based on the average eviction time (AET) of the cached data. The AET model enables fast measurement and use of low-cost sampling. It can produce the miss ratio curve in linear time with extremely low space costs. On storage trace benchmarks, AET reduces the time and space costs compared to former techniques. Furthermore, AET is a composable model that can characterize shared cache behavior through sampling and modeling individual programs or traces.
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