An Associativity Threshold Phenomenon in Set-Associative Caches
Michael A. Bender, Rathish Das, Mart\'in Farach-Colton, Guido, Tagliavini

TL;DR
This paper analyzes how the size of sets in set-associative caches affects performance, revealing a threshold around a logarithmic function of total cache size where behavior shifts from similar to fully associative caches to worse performance.
Contribution
It characterizes the performance threshold of set-associative caches based on set size, providing probabilistic bounds and conditions for near-optimal caching behavior.
Findings
For large set sizes, cache performance is close to fully associative caches.
Small set sizes lead to significantly worse cache performance.
Changing hash functions can improve cache performance for large set sizes.
Abstract
In an -way set-associative cache, the cache is partitioned into disjoint sets of size , and each item can only be cached in one set, typically selected via a hash function. Set-associative caches are widely used and have many benefits, e.g., in terms of latency or concurrency, over fully associative caches, but they often incur more cache misses. As the set size decreases, the benefits increase, but the paging costs worsen. In this paper we characterize the performance of an -way set-associative LRU cache of total size , as a function of . We prove the following, assuming that sets are selected using a fully random hash function: - For , the paging cost of an -way set-associative LRU cache is within additive of that a fully-associative LRU cache of size , with probability $1 -…
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Taxonomy
TopicsCaching and Content Delivery · Graph Labeling and Dimension Problems · Optimization and Search Problems
