{"title":"批处理点对点通信中网络争用的动态时间步进分组级仿真快速建模","authors":"Zhang Yang, Jintao Peng, Qingkai Liu","doi":"10.1145/3409390.3409398","DOIUrl":null,"url":null,"abstract":"Network contention has long been one of the root causes of performance loss in large-scale parallel applications. With the increasing importance of performance modeling to both large-scale application optimization and application-system co-design, the conflict of speed and accuracy in contention modeling is becoming prominent. Cycle-accurate network simulators are often too slow for large scale applications, while point-to-point analytical models are not accurate enough to capture the contention effects. To model the network contention in batch point-to-point communications, we propose a unified contention model after the flow-fair end-to-end congestion control mechanism. The model uses packet-level simulations to be accurate, but can be approximated by a flow-level semi-analytical model when messages are large enough, thus is fast. Furthermore, we propose a dynamic time-stepping technique which significantly speeds up the packet-level simulation with only minor accuracy loss. Experiments with typical communication patterns and application traces show that our model accurately predicates the communication time with an average error of 9%(fixed time step) and the dynamic time-stepping technique improve the simulation performance by up to 131 folds with an average accuracy loss of 10.5% for real application traces.","PeriodicalId":350506,"journal":{"name":"Workshop Proceedings of the 49th International Conference on Parallel Processing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast Modeling of Network Contention in Batch Point-to-point Communications by Packet-level Simulation with Dynamic Time-stepping\",\"authors\":\"Zhang Yang, Jintao Peng, Qingkai Liu\",\"doi\":\"10.1145/3409390.3409398\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network contention has long been one of the root causes of performance loss in large-scale parallel applications. With the increasing importance of performance modeling to both large-scale application optimization and application-system co-design, the conflict of speed and accuracy in contention modeling is becoming prominent. Cycle-accurate network simulators are often too slow for large scale applications, while point-to-point analytical models are not accurate enough to capture the contention effects. To model the network contention in batch point-to-point communications, we propose a unified contention model after the flow-fair end-to-end congestion control mechanism. The model uses packet-level simulations to be accurate, but can be approximated by a flow-level semi-analytical model when messages are large enough, thus is fast. Furthermore, we propose a dynamic time-stepping technique which significantly speeds up the packet-level simulation with only minor accuracy loss. Experiments with typical communication patterns and application traces show that our model accurately predicates the communication time with an average error of 9%(fixed time step) and the dynamic time-stepping technique improve the simulation performance by up to 131 folds with an average accuracy loss of 10.5% for real application traces.\",\"PeriodicalId\":350506,\"journal\":{\"name\":\"Workshop Proceedings of the 49th International Conference on Parallel Processing\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop Proceedings of the 49th International Conference on Parallel Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3409390.3409398\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop Proceedings of the 49th International Conference on Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3409390.3409398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast Modeling of Network Contention in Batch Point-to-point Communications by Packet-level Simulation with Dynamic Time-stepping
Network contention has long been one of the root causes of performance loss in large-scale parallel applications. With the increasing importance of performance modeling to both large-scale application optimization and application-system co-design, the conflict of speed and accuracy in contention modeling is becoming prominent. Cycle-accurate network simulators are often too slow for large scale applications, while point-to-point analytical models are not accurate enough to capture the contention effects. To model the network contention in batch point-to-point communications, we propose a unified contention model after the flow-fair end-to-end congestion control mechanism. The model uses packet-level simulations to be accurate, but can be approximated by a flow-level semi-analytical model when messages are large enough, thus is fast. Furthermore, we propose a dynamic time-stepping technique which significantly speeds up the packet-level simulation with only minor accuracy loss. Experiments with typical communication patterns and application traces show that our model accurately predicates the communication time with an average error of 9%(fixed time step) and the dynamic time-stepping technique improve the simulation performance by up to 131 folds with an average accuracy loss of 10.5% for real application traces.