D. S. Hirschberg – Communications of the ACM

Research and Advances Aug 1 1985

Diehr and Faaland developed an algorithm that finds the minimum sum of key length pagination of a scroll of n items, and which uses O(n log n) time, solving a problem posed by McCreight. An improved algorithm is given which uses O(n) time.

Computing Applications

Author Archives

Research and Advances Nov 1 1980

Decentralized extrema-finding in circular configurations of processors

This note presents an efficient algorithm, requiring O(n log n) message passes, for finding the largest (or smallest) of a set of n uniquely numbered processors arranged in a circle, in which no central controller exists and the number of processors is not known a priori.

Research and Advances Aug 1 1979

Computing connected components on parallel computers

We present a parallel algorithm which uses n2 processors to find the connected components of an undirected graph with n vertices in time O(log2n). An O(log2n) time bound also can be achieved using only n⌈n/⌈log2n⌉⌉ processors. The algorithm can be used to find the transitive closure of a symmetric Boolean matrix. We assume that the processors have access to a common memory. Simultaneous access to the same location is permitted for fetch instructions but not for store instructions.

Research and Advances Aug 1 1978

Fast parallel sorting algorithms

A parallel bucket-sort algorithm is presented that requires time O(log n) and the use of n processors. The algorithm makes use of a technique that requires more space than the product of processors and time. A realistic model is used in which no memory contention is permitted. A procedure is also presented to sort n numbers in time O(k log n) using n1+1/k processors, for k an arbitrary integer. The model of computation for this procedure permits simultaneous fetches from the same memory location.

Artificial Intelligence and Machine Learning

Research and Advances Aug 1 1976

An insertion technique for one-sided height-balanced trees

A restriction on height-balanced binary trees is presented. It is seen that this restriction reduces the extra memory requirements by half (from two extra bits per node to one) and maintains fast search capabilities at a cost of increased time requirements for inserting new nodes.

Research and Advances Jun 1 1975

A linear space algorithm for computing maximal common subsequences

The problem of finding a longest common subsequence of two strings has been solved in quadratic time and space. An algorithm is presented which will solve this problem in quadratic time and in linear space.

Artificial Intelligence and Machine Learning

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