A General Lower Bound on the I/O-Complexity of Comparison-based Algorithms

Abstract

We show a relationship between the number of comparisons and the number of I/O operations needed to solve a given problem. We work in a model, where the permitted operations are l/O-operations and comparisons of two records in internal memory. An I/O- operation swaps B records between external memory and the internal memory (capable of holding M records). An algorithm for this model is called an I/O-algorithm. The main result of this paper is the following: Given an I/O-algorithm that solves an n-record problem P_n using I/O(bar{x}) I/O's on the input bar{x}, there exists an ordinary comparison algorithm that uses no more than n logB + I/O(bar{x}) € T_{merge}(M-B, B) comparisons on input bar{x}. T_{merge}(n, m) denotes the number of comparisons needed to merge two sorted lists of size n and m, respectively. We use the result to show lower bounds on the number of I/O-operations needed to solve the problems of sorting, removing duplicates from a multiset and determining the mode (the most frequently occurring element in a multiset). Aggarwal and Vitter have shown that the sorting bound is tight. We show the same result for the two other problems, by providing optimal algorithms.