Abstract

Abstract — Hashing algorithms and their efficiency is modeled with their expected probe lengths. This value measures the number of algorithmic steps required to find the position of an item inside the table. This metric, however, has an implicit assumption that all of these steps have a uniform cost. In this paper we show that this is not true on modern computers, and that caches and especially cache lines have a great impact on the performance and effectiveness of hashing algorithms that use array-based structures. Spatial locality of memory accesses plays a major role in the effectiveness of an algorithm. We show a novel model of evaluating hashing schemes; this model is based on the number of cache misses the algorithms suffer. This new approach is shown to model the real performance of hash tables more precisely than previous methods. For developing this model the sketch of proof of the expected probe length of linear probing is included.

Citations