{"title":"PFSI。基于神威多核处理器的海冰模型算法编程框架","authors":"Binyang Li, Bo Li, D. Qian","doi":"10.1109/ASAP.2017.7995268","DOIUrl":null,"url":null,"abstract":"Sea ice model is a typical high performance computing problem. CPU and GPU based parallel method has been proposed to accelerate the simulation process, but it is still hard to meet the large-scale calculation demand due to the compute-intensive nature of the model. Sunway TaihuLight supercomputer use the SW26010 processor as its computing unit and achieves high performance for large-scale scientific computing. In this paper we present a programming framework (PFSI.sw) for sea ice model algorithms based on Sunway many-core processor. Based on this framework, programmer can exploit the parallelism of existing sea ice model algorithms and achieve good performance. Several strategies are introduced to this framework, data dividing, data transfer as well as the load balance are the main aspects we currently concerned. This framework has been implemented and tested with two sea ice model algorithms by using real world dataset on Sunway many-core processors. The experiment demonstrates comparable performance to the traditional parallel implementation on Sunway many-core processor and our framework improves the performance up to 40%.","PeriodicalId":405953,"journal":{"name":"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"PFSI.sw: A programming framework for sea ice model algorithms based on Sunway many-core processor\",\"authors\":\"Binyang Li, Bo Li, D. Qian\",\"doi\":\"10.1109/ASAP.2017.7995268\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sea ice model is a typical high performance computing problem. CPU and GPU based parallel method has been proposed to accelerate the simulation process, but it is still hard to meet the large-scale calculation demand due to the compute-intensive nature of the model. Sunway TaihuLight supercomputer use the SW26010 processor as its computing unit and achieves high performance for large-scale scientific computing. In this paper we present a programming framework (PFSI.sw) for sea ice model algorithms based on Sunway many-core processor. Based on this framework, programmer can exploit the parallelism of existing sea ice model algorithms and achieve good performance. Several strategies are introduced to this framework, data dividing, data transfer as well as the load balance are the main aspects we currently concerned. This framework has been implemented and tested with two sea ice model algorithms by using real world dataset on Sunway many-core processors. The experiment demonstrates comparable performance to the traditional parallel implementation on Sunway many-core processor and our framework improves the performance up to 40%.\",\"PeriodicalId\":405953,\"journal\":{\"name\":\"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASAP.2017.7995268\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASAP.2017.7995268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PFSI.sw: A programming framework for sea ice model algorithms based on Sunway many-core processor
Sea ice model is a typical high performance computing problem. CPU and GPU based parallel method has been proposed to accelerate the simulation process, but it is still hard to meet the large-scale calculation demand due to the compute-intensive nature of the model. Sunway TaihuLight supercomputer use the SW26010 processor as its computing unit and achieves high performance for large-scale scientific computing. In this paper we present a programming framework (PFSI.sw) for sea ice model algorithms based on Sunway many-core processor. Based on this framework, programmer can exploit the parallelism of existing sea ice model algorithms and achieve good performance. Several strategies are introduced to this framework, data dividing, data transfer as well as the load balance are the main aspects we currently concerned. This framework has been implemented and tested with two sea ice model algorithms by using real world dataset on Sunway many-core processors. The experiment demonstrates comparable performance to the traditional parallel implementation on Sunway many-core processor and our framework improves the performance up to 40%.