Kinetic Modeling of Data Eviction in Cache

The reuse distance (LRU stack distance) is an essential metric for performance prediction and optimization of storage and CPU cache. Over the last 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 paper, 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 low-cost sampling. It can produce the miss ratio curve (MRC) in linear time with extremely low space costs. On both CPU and storage benchmarks, AET reduces the time and space costs compare to former techniques. Furthermore, AET is a composable model that can characterize shared cache behavior through modeling individual programs.