Paper Info
Title
The SprayList: a scalable relaxed priority queue
Abstract
High-performance concurrent priority queues are essential for applications such as task scheduling and discrete event simulation. Unfortunately, even the best performing implementations do not scale past a number of threads in the single digits. This is because of the sequential bottleneck in accessing the elements at the head of the queue in order to perform a DeleteMin operation. In this paper, we present the SprayList, a scalable priority queue with relaxed ordering semantics. Starting from a non-blocking SkipList, the main innovation behind our design is that the DeleteMin operations avoid a sequential bottleneck by ``spraying'' themselves onto the head of the SkipList list in a coordinated fashion. The spraying is implemented using a carefully designed random walk, so that DeleteMin returns an element among the first O(p log^3 p) in the list, with high probability, where p is the number of threads. We prove that the running time of a DeleteMin operation is O(log^3 p), with high probability, independent of the size of the list. Our experiments show that the relaxed semantics allow the data structure to scale for high thread counts, comparable to a classic unordered SkipList. Furthermore, we observe that, for reasonably parallel workloads, the scalability benefits of relaxation considerably outweigh the additional work due to out-of-order execution.
Year
DOI
Venue
2015
10.1145/2688500.2688523
PPOPP
Keywords
Field
DocType
concurrent data structures,data structures,parallel algorithms
Bottleneck,Programming language,Computer science,Scheduling (computing),Theoretical computer science,Priority queue,Concurrent data structure,Distributed computing,Queue,Skip list,Parallel computing,Thread (computing),Discrete event simulation
Conference
Volume
Issue
ISSN
50
8
0362-1340
Citations 
PageRank 
References 
33
1.10
23
Authors
4
Name
Order
Citations
PageRank
Dan Alistarh134142.64
Justin Kopinsky2395.23
Jerry Li322922.67
Nir Shavit43780244.84