最小最小和最优选择的堆栈距离在线优化计算

G. Bilardi, K. Ekanadham, P. Pattnaik
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引用次数: 2

摘要

对于两级内存层次结构,称为MIN和OPT的替换策略是最优的。这些策略的缓存内容的计算需要了解整个地址跟踪的离线知识。但是,给定访问的堆栈距离,即该访问导致命中的缓存的最小容量,与未来的访问无关,并且可以在线计算。计算每次访问时间O(V)的堆栈距离的离线和在线算法已经存在了几十年,其中V表示跟踪中不同地址的数量。最近将离线时间限制改进为O(√V log V).本文介绍了在每次访问O(log V)时间内在线计算MIN和OPT的堆栈距离的临界堆栈算法。结果利用了一种新的基于平衡二叉树的OPT和数据结构的特性分析。通过对元素区别度的约简,推导出相应的Ω(log V)下界;这个界限适用于各种计算模型,甚至适用于仅一个缓存容量的离线模拟。
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Optimal On-Line Computation of Stack Distances for MIN and OPT
The replacement policies known as MIN and OPT are optimal for a two-level memory hierarchy. The computation of the cache content for these policies requires the off-line knowledge of the entire address trace. However, the stack distance of a given access, that is, the smallest capacity of a cache for which that access results in a hit, is independent of future accesses and can be computed on-line. Off-line and on-line algorithms to compute the stack distance in time O(V) per access have been known for several decades, where V denotes the number of distinct addresses within the trace. The off-line time bound was recently improved to O(√V log V). This paper introduces the Critical Stack Algorithm for the online computation of the stack distance of MIN and OPT, in time O(log V) per access. The result exploits a novel analysis of properties of OPT and data structures based on balanced binary trees. A corresponding Ω(log V) lower bound is derived by a reduction from element distinctness; this bound holds in a variety of models of computation and applies even to the off-line simulation of just one cache capacity.
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