{"title":"使用无锁数据结构的数值模拟中的并发框架:图并行体系结构图","authors":"P. Klein, Dimo Maleshkov, D. Asenov","doi":"10.1109/PDCAT.2008.32","DOIUrl":null,"url":null,"abstract":"The development of numerical simulation software tools for the solution of real-world problems usually calls for domain experts in modeling. The GraPA framework, as an abstraction layer on top of hardware characteristics, supports modelers in two respects: one is the built-in support for co-processing of multiple models and the other is the generically delivered high performance achieved by implementing concurrency features of multicore and distributed memory architectures. Technically, GraPA is designed as a C++ template framework, where the modeler`s data structures and algorithms instantiate the framework. Using this approach, we handle parallel processing of lock-free data structures and message passing transparently to the modelers. In this paper, we report on the status of the implementation of GraPA and on its performance characteristics.","PeriodicalId":282779,"journal":{"name":"2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Framework for Concurrency in Numerical Simulations Using Lock Free Data Structures: The Graph Parallel Architecture GraPA\",\"authors\":\"P. Klein, Dimo Maleshkov, D. Asenov\",\"doi\":\"10.1109/PDCAT.2008.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of numerical simulation software tools for the solution of real-world problems usually calls for domain experts in modeling. The GraPA framework, as an abstraction layer on top of hardware characteristics, supports modelers in two respects: one is the built-in support for co-processing of multiple models and the other is the generically delivered high performance achieved by implementing concurrency features of multicore and distributed memory architectures. Technically, GraPA is designed as a C++ template framework, where the modeler`s data structures and algorithms instantiate the framework. Using this approach, we handle parallel processing of lock-free data structures and message passing transparently to the modelers. In this paper, we report on the status of the implementation of GraPA and on its performance characteristics.\",\"PeriodicalId\":282779,\"journal\":{\"name\":\"2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDCAT.2008.32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDCAT.2008.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Framework for Concurrency in Numerical Simulations Using Lock Free Data Structures: The Graph Parallel Architecture GraPA
The development of numerical simulation software tools for the solution of real-world problems usually calls for domain experts in modeling. The GraPA framework, as an abstraction layer on top of hardware characteristics, supports modelers in two respects: one is the built-in support for co-processing of multiple models and the other is the generically delivered high performance achieved by implementing concurrency features of multicore and distributed memory architectures. Technically, GraPA is designed as a C++ template framework, where the modeler`s data structures and algorithms instantiate the framework. Using this approach, we handle parallel processing of lock-free data structures and message passing transparently to the modelers. In this paper, we report on the status of the implementation of GraPA and on its performance characteristics.