Skiplist-based concurrent priority queues

Abstract

This paper addresses the problem of designing scalable concurrent priority queues for large scale multiprocessors machines with up to several hundred processors. Priority queues are fundamental in the design of modern multiprocessor algorithms, with many classical applications ranging from numerical algorithms through discrete event simulation and expert systems. While highly scalable approaches have been introduced for the special case of queues with a fixed set of priorities, the most efficient designs for the general case are based on the parallelization of the heap data structure. Though numerous intricate heap-based schemes have been suggested in the literature, their scalability seems to be limited to small machines in the range of ten to twenty processors. This paper proposes an alternative approach: to base the design of concurrent priority queues on the probabilistic skiplist data structure, rather than on a heap. To this end, we show that a concurrent skiplist structure, following a simple set of modifications, provides a concurrent priority queue with a higher level of parallelism and significantly less contention than the fastest known heap-based algorithms. Our initial empirical evidence, collected on a simulated 256 node shared memory multiprocessor architecture similar to the MIT Alewife, suggests that the new skiplist based priority queue algorithm scales significantly better than heap based schemes throughout most of the concurrency range. With 256 processors, they are about twice as fast in performing deletions and up to 8 times faster in performing insertions.