## Abstract

This paper surveys randomized parallel algorithms found in the literature for various problems in computer science. In particular we will demonstrate the power of randomization as a tool for parallelizing sequential algorithms and introduce the reader so some of the techniques employed in designing randomized parallel algorithms. We consider representative problems from the following areas of computer science and describe how randomized parallel algorithms for these problems have been obtained: 1) routing and sorting, 2) processor load balancing, 3) algebra, and 4) graph theory. Finally we discuss methods of derandomizing randomized parallel algorithms.

## Keywords

Parallel Algorithm Depth First Search Boolean Circuit Shared Memory Model Pram Model
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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## Copyright information

© Plenum Press, New York 1988