{"title":"可扩展共享内存并行编程:一个大小适合所有吗?","authors":"B. Chapman","doi":"10.1109/PDP.2006.64","DOIUrl":null,"url":null,"abstract":"In recent years, there has been much emphasis on improving the productivity of high-end parallel programmers. Efforts to design very large-scale platforms have focused on global address space machines that are capable of concurrently executing many thousands of threads. As a result, new higher level shared memory programming models have been proposed that are intended to reduce the programming effort and directly exploit the capabilities of such systems.","PeriodicalId":92432,"journal":{"name":"Proceedings. Euromicro International Conference on Parallel, Distributed, and Network-based Processing","volume":"25 1","pages":"3"},"PeriodicalIF":0.0000,"publicationDate":"2006-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Scalable Shared Memory Parallel Programming: Will One Size Fit All?\",\"authors\":\"B. Chapman\",\"doi\":\"10.1109/PDP.2006.64\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, there has been much emphasis on improving the productivity of high-end parallel programmers. Efforts to design very large-scale platforms have focused on global address space machines that are capable of concurrently executing many thousands of threads. As a result, new higher level shared memory programming models have been proposed that are intended to reduce the programming effort and directly exploit the capabilities of such systems.\",\"PeriodicalId\":92432,\"journal\":{\"name\":\"Proceedings. Euromicro International Conference on Parallel, Distributed, and Network-based Processing\",\"volume\":\"25 1\",\"pages\":\"3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Euromicro International Conference on Parallel, Distributed, and Network-based Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDP.2006.64\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Euromicro International Conference on Parallel, Distributed, and Network-based Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDP.2006.64","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scalable Shared Memory Parallel Programming: Will One Size Fit All?
In recent years, there has been much emphasis on improving the productivity of high-end parallel programmers. Efforts to design very large-scale platforms have focused on global address space machines that are capable of concurrently executing many thousands of threads. As a result, new higher level shared memory programming models have been proposed that are intended to reduce the programming effort and directly exploit the capabilities of such systems.