Affiliation:
1. National University of Defense Technology, Changsha, China
2. Beihang University, Beijing, China
3. National University of Defense Technology, Beijing, China
Abstract
Load imbalance has always been a crucial challenge in Parallel Discrete Event Simulation (PDES). In the past few years, we have witnessed an increased interest in using multithreading PDES on multi/many-core platforms. In multithreading PDES, migrating logical processes and coordinating threads are more convenient and cause lower overhead, which provides a better circumstance for load balancing. However, current algorithms, including the persistence-based scheme and work-stealing-based scheme, have their drawbacks. On one hand, persistence-based load balancers, which use the historical data to predict the future, will inevitably make some error. On the other hand, the work-stealing scheme ignores the application-related characteristic, which may limit the potential performance improvement. In this article, we propose an adaptive persistence and work-stealing combined dynamic load balancing algorithm (APWS). The algorithm detects load imbalance, adaptively rebalances the distribution of logical processes, and uses a greedy lock-free work-stealing scheme to eliminate bias at runtime. We assess the performance of the APWS algorithm by a series of experiments. Results demonstrate that our APWS algorithm achieves better performance in different scenarios.
Funder
National natural Science Foundation of China
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications,Modeling and Simulation
Cited by
1 articles.
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