A comparative study of parallel and sequential priority queue algorithms

Abstract

Priority queues are used in many applications including real-time systems, operating systems, and simulations. Their implementation may have a profound effect on the performance of such applications. In this article, we study the performance of well-known sequential priority queue implementations and the recently proposed parallel access priority queues. To accurately assess the performance of a priority queue, the performance measurement methodology must be appropriate. We use the Classic Hold, the Markov Model, and an Up/Down access pattern to measure performance and look at both the average access time and the worst-case time that are of vital interest to real-tiem applicatons. Our results suggest that the best choice for priority queue algorithms depends heavily on the application. For queue sizes smaller than 1,000 elements, the Splay Tree, the Skew Heap, and Henriksen's algorithm show good average access times. For large queue sized of 5,000 elements or more, the Calendar Queue and the Lazy Queue offer good average access times but have very long worst-case access times. The Skew Heap and the splay Tree exhibit the best worst-case access times. Among the parallel access priority queues tested, the Parallel Access Skew Heap provides the best performance on small shares memory multiprocessors.