On the Complexity of Cache Analysis for Different Replacement Policies

D. Monniaux, Valentin Touzeau
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引用次数: 3

Abstract

Modern processors use cache memory, a memory access that “hits” the cache returns early, while a “miss” takes more time. Given a memory access in a program, cache analysis consists in deciding whether this access is always a hit, always a miss, or is a hit or a miss depending on execution. Such an analysis is of high importance for bounding the worst-case execution time of safety-critical real-time programs. There exist multiple possible policies for evicting old data from the cache when new data are brought in, and different policies, though apparently similar in goals and performance, may be very different from the analysis point of view. In this article, we explore these differences from a complexity-theoretical point of view. Specifically, we show that, among the common replacement policies, Least Recently Used is the only one whose analysis is NP-complete, whereas the analysis problems for the other policies are PSPACE-complete.
不同替换策略下缓存分析的复杂性
现代处理器使用缓存存储器,这种存储器访问“命中”缓存会提前返回,而“未命中”则需要更长的时间。给定一个程序中的内存访问,缓存分析包括判断这个访问是总是命中还是总是未命中,或者是命中还是未命中取决于执行。这种分析对于限定安全关键型实时程序的最坏情况执行时间具有重要意义。当引入新数据时,有多种可能的策略用于从缓存中清除旧数据,不同的策略虽然在目标和性能上明显相似,但从分析的角度来看可能差别很大。在本文中,我们从复杂性理论的角度探讨这些差异。具体来说,我们证明了在常见的替换策略中,最近最少使用是唯一一个分析问题是np完全的策略,而其他策略的分析问题是pspace完全的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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