{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T06:21:48Z","timestamp":1761718908856,"version":"3.41.0"},"reference-count":26,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T00:00:00Z","timestamp":1584662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National natural Science Foundation of China","doi-asserted-by":"crossref","award":["61702527 and 61903368"],"award-info":[{"award-number":["61702527 and 61903368"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Model. Comput. Simul."],"published-print":{"date-parts":[[2020,4,30]]},"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.1145\/3364218","type":"journal-article","created":{"date-parts":[[2020,3,21]],"date-time":"2020-03-21T04:18:28Z","timestamp":1584764308000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["An Adaptive Persistence and Work-stealing Combined Algorithm for Load Balancing on Parallel Discrete Event Simulation"],"prefix":"10.1145","volume":"30","author":[{"given":"Tang","family":"Wenjie","sequence":"first","affiliation":[{"name":"National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Yiping","sequence":"additional","affiliation":[{"name":"National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Tianlin","sequence":"additional","affiliation":[{"name":"National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Song","family":"Xiao","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhu","family":"Feng","sequence":"additional","affiliation":[{"name":"National University of Defense Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,3,20]]},"reference":[{"edition":"1","volume-title":"Foundations of Parallel and Distributed Programming","author":"Andrews Greg R.","key":"e_1_2_1_1_1"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.1994.365680"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/268823.268897"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/510378.510591"},{"volume-title":"Proceedings of the 11th Workshop on Parallel and Distributed Simulation. 178--181","year":"1997","author":"Cai Wentong","key":"e_1_2_1_5_1"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/71.841745"},{"volume-title":"Proceedings of the 2011 IEEE Workshop on Principles of Advanced and Distributed Simulation (PADS\u201911)","year":"2011","key":"e_1_2_1_7_1"},{"volume-title":"Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. 189--200","year":"2009","author":"Eric Mikida","key":"e_1_2_1_8_1"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/71.210814"},{"volume-title":"Proceedings of the Los Alamos Computer Science Institute. 1--17","year":"2002","author":"Kal\u00e9 Laxmikant V.","key":"e_1_2_1_10_1"},{"volume-title":"Proceedings of the Workshop on Parallel and Distributed Simulation. 189--194","year":"2004","author":"Lemeire Jan","key":"e_1_2_1_11_1"},{"volume-title":"Proceedings of the 21st International Symposium on High-Performance Parallel Distributed Computing (HPDC\u201912)","author":"Lifflander Jonathan","key":"e_1_2_1_12_1"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1057\/s41273-016-0033-x"},{"key":"e_1_2_1_14_1","article-title":"Multithreaded stochastic PDES for reactions and diffusions in neurons","volume":"27","author":"Zhongwei Lin","year":"2016","journal-title":"ACM Trans. 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