Help the Middle Class Citizens in the Cache

Juncheng Yang

Feb 2018

Researches have always treated cache requests equal, however, this is NOT true. Items in the cache also have classes, some have longer lifetime than others, while some are prone to be re-accesssed. Different classes have different characteristics, it is important that we distinguish the requests and treat them differently.


In this project, we aim to discover the mid-class citizens in the cache, aka items with mid-frequency. This class of items do not have a very high-frequency to guarantee them “pinned” in the cache. While they still relatively high frequency so that being able to capture them is useful. Consider the frequent items, they are so often accessed that most cache replacement algorithm will be able to cache them; while the rare items, they appear once every few years, keep them in the cache is not a waste of precious cache space.


We borrow ideas from data mining and machine learning, we further develop them into approximate online algorithms to give intelligence to existing cache replacement algorithms.

Selected Work

Mithril is a history based prefetching algorithm that was inspired by sporadic association rule mining. The main idea behind Mithril is simple, if two non-frequent items are always accessed closely, then they are associated and we can prefetch the other if we see one of them. Based on this idea, Mithril uses a fast timestamp-based-comparison to discover associations in an approximately way online.


Juncheng Yang, Reza Karimi, Trausti Saemundsson, Avani Wildani, Ymir Vigfusson. “MITHRIL Mining Sporadic Associations for Cache Prefetching.” ACM Symposium on Cloud Computing (SoCC), 2017.