An analytical model for software-only main memory compression

Abstract

Many applications with large data spaces that cannot run on a typical workstation (due to page faults) call for techniques to expand the effective memory size. One such technique is memory compression.Understanding what applications under what conditions can benefit from main memory compression is complicated due to various tradeoffs and the dynamic characteristics of applications. For instance, a large area to store compressed data increases the effective memory size considerably but also decreases the amount of memory that can hold uncompressed data.This paper presents an analytical model that states the conditions for a compressed-memory system to yield performance improvements. Parameters of the model are the compression algorithm efficiency, the amount of data being compressed, and the application memory access pattern. Such a model can be used by an operating system to compute the size of the compressed-memory level that can improve an application's performance.