Fast Miss Ratio Curve Modeling for Storage Cache
Fast Miss Ratio Curve Modeling for Storage Cache
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DOI：
10.1145/3185751
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发表时间：
2018-04
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影响因子：
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通讯作者：
Xiameng Hu;Xiaolin Wang;Lan Zhou;Yingwei Luo;Zhenlin Wang;C. Ding;Chencheng Ye
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文献类型：
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作者：
Xiameng Hu;Xiaolin Wang;Lan Zhou;Yingwei Luo;Zhenlin Wang;C. Ding;Chencheng Ye
重复使用距离（最近使用的（LRU）堆栈距离）是用于性能预测和优化存储缓存的必不可少的度量。在过去的四十年中，重复使用距离测量的算法效率一直有所提高。在理论和实际实施方面，近年来，这一进展正在加速。在本文中，我们根据缓存数据的平均驱逐时间（AET）提出了LRU缓存存储器的动力学模型。 AET模型可以快速测量和使用低成本采样。它可以以极低的空间成本在线性时间内产生遗漏比率曲线。在存储跟踪基准测试中，与以前的技术相比，AET降低了时间和空间成本。此外，AET是一个可组合模型，可以通过采样和建模单个程序或跟踪来表征共享的缓存行为。
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.