{"title":"基于衍射树的可扩展并发池","authors":"A. D. Anenkov, A. Paznikov, M. Kupriyanov","doi":"10.1109/SCM50615.2020.9198793","DOIUrl":null,"url":null,"abstract":"Multithreading synchronization is one of the most essential problems parallel programming. Concurrent pool is one of the most common and demanded data structures in scalable applications. The promising way to implement concurrent pool is using diffracting (diffraction) tree as an auxiliary data structure to increase the scalability. In this work, we try to optimize diffracting-tree based pool and propose our implementations which outperforms the existing ones. We designed concurrent based on diffracting trees which optimize access of threads to global variables for maximization of the efficiency (throughput) of data structure. We performed experimental modeling to evaluate the efficiency of concurrent pools. We give the evidence that our pools have higher scalability compared with the existing pool’s implementations based on diffracting trees. We discuss the experimental results and provide the guidance for using them.","PeriodicalId":169458,"journal":{"name":"2020 XXIII International Conference on Soft Computing and Measurements (SCM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scalable Concurrent Pools Based on Diffracting Trees\",\"authors\":\"A. D. Anenkov, A. Paznikov, M. Kupriyanov\",\"doi\":\"10.1109/SCM50615.2020.9198793\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multithreading synchronization is one of the most essential problems parallel programming. Concurrent pool is one of the most common and demanded data structures in scalable applications. The promising way to implement concurrent pool is using diffracting (diffraction) tree as an auxiliary data structure to increase the scalability. In this work, we try to optimize diffracting-tree based pool and propose our implementations which outperforms the existing ones. We designed concurrent based on diffracting trees which optimize access of threads to global variables for maximization of the efficiency (throughput) of data structure. We performed experimental modeling to evaluate the efficiency of concurrent pools. We give the evidence that our pools have higher scalability compared with the existing pool’s implementations based on diffracting trees. We discuss the experimental results and provide the guidance for using them.\",\"PeriodicalId\":169458,\"journal\":{\"name\":\"2020 XXIII International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 XXIII International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCM50615.2020.9198793\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 XXIII International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCM50615.2020.9198793","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scalable Concurrent Pools Based on Diffracting Trees
Multithreading synchronization is one of the most essential problems parallel programming. Concurrent pool is one of the most common and demanded data structures in scalable applications. The promising way to implement concurrent pool is using diffracting (diffraction) tree as an auxiliary data structure to increase the scalability. In this work, we try to optimize diffracting-tree based pool and propose our implementations which outperforms the existing ones. We designed concurrent based on diffracting trees which optimize access of threads to global variables for maximization of the efficiency (throughput) of data structure. We performed experimental modeling to evaluate the efficiency of concurrent pools. We give the evidence that our pools have higher scalability compared with the existing pool’s implementations based on diffracting trees. We discuss the experimental results and provide the guidance for using them.