Abstract
The goal of this paper is to point out that analyses of parallelism in computational problems have practical implications even when multi-processor machines are not available. This is true because, in many cases, a good parallel algorithm for one problem may turn out to be useful for designing an efficient serial algorithm for another problem. A unified framework for cases like this is presented. Particular cases, which are discussed in this paper, provide motivation for examining parallelism in problems like sorting, selection, minimum-spanning-tree, shortest route, maxflow, matrix multiplication, as well as scheduling and locational problems.

This publication has 12 references indexed in Scilit: