Open AccessA General Lower Bound on the I/O-Complexity of Comparison-based Algorithms
Author(s) -
Lars Arge,
Mikael B. Knudsen,
Kirsten Larsen
Publication year - 1992
Publication title -
daimi pb
Language(s) - English
Resource type - Journals
eISSN - 2245-9316
pISSN - 0105-8517
DOI - 10.7146/dpb.v21i407.6641
Subject(s) - multiset , merge (version control) , algorithm , merge algorithm , upper and lower bounds , combinatorics , computer science , binary logarithm , heuristics , mathematics , sorting , discrete mathematics , sorting algorithm , parallel computing , mathematical optimization , mathematical analysis
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.