A Survey of Miss-Ratio Curve Construction Techniques

TL;DR

This survey reviews various techniques for constructing miss-ratio curves, highlighting recent advancements that enable real-time approximation and discussing their applications in cache management and operating systems.

Contribution

It provides a comprehensive classification of existing methods based on locality metrics and storage techniques, and compares historical and modern approaches.

Findings

Recent methods enable constant-time approximation of MRCs

Techniques vary from dynamic programming to AI-inspired algorithms

Open research areas include theoretical foundations and practical applications

Abstract

Miss-ratio curve (MRC), or equivalently hit-ratio curve (HRC), construction techniques have recently gathered the attention of many researchers. Recent advancements have allowed for approximating these curves in constant time, allowing for online working-set-size (WSS) measurement. Techniques span the algorithmic design paradigm from classic dynamic programming to artificial intelligence inspired techniques. Our survey produces broad classification of the current techniques primarily based on \emph{what} locality metric is being recorded and \emph{how} that metric is stored for processing. Applications of theses curves span from dynamic cache partitioning in the processor, to improving block allocation at the operating system level. Our survey will give an overview of the historical, exact MRC construction methods, and compare them with the state-of-the-art methods present in today's literature. In addition, we will show where there are still open areas of research and remain excited to see what this domain can produce with a strong theoretical background.