{"title":"JAC3D在NCUBE/ 10上的实现","authors":"C. Vaughan","doi":"10.1109/DMCC.1990.555431","DOIUrl":null,"url":null,"abstract":"An implementation is presented for JAC3D on a massively parallel hypercube computer. JACSD, a three dimensional finite element code developed at Sandia, uses several hundred hours of Cray time each year in solving structural analysis problems. Two major areas of investigation are discussed: (1) the development of general methods, data structures, and routines to communicate information between processors, and (2) the implementation and evaluation of four algorithms to map problems onto the node processors of the hypercube in a loadbalanced fashion. The performance of JACJD on the NCUBE/ten is compared with that on a Cray X-MP: the NCUBE/ten version presently takes 20% more compute time than the Cray. On a larger simulation which used more of the NCUBE's memory, the NCUBE/ten would take less compute time than the Cray. Current activity on the newer NCUBE 2 hypercube is summarized which should lead to an order of magnitude improvement in run-time performance for the massively parallel solution of structural analysis problems.","PeriodicalId":204431,"journal":{"name":"Proceedings of the Fifth Distributed Memory Computing Conference, 1990.","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Implementation of JAC3D on The NCUBE/ten\",\"authors\":\"C. Vaughan\",\"doi\":\"10.1109/DMCC.1990.555431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An implementation is presented for JAC3D on a massively parallel hypercube computer. JACSD, a three dimensional finite element code developed at Sandia, uses several hundred hours of Cray time each year in solving structural analysis problems. Two major areas of investigation are discussed: (1) the development of general methods, data structures, and routines to communicate information between processors, and (2) the implementation and evaluation of four algorithms to map problems onto the node processors of the hypercube in a loadbalanced fashion. The performance of JACJD on the NCUBE/ten is compared with that on a Cray X-MP: the NCUBE/ten version presently takes 20% more compute time than the Cray. On a larger simulation which used more of the NCUBE's memory, the NCUBE/ten would take less compute time than the Cray. Current activity on the newer NCUBE 2 hypercube is summarized which should lead to an order of magnitude improvement in run-time performance for the massively parallel solution of structural analysis problems.\",\"PeriodicalId\":204431,\"journal\":{\"name\":\"Proceedings of the Fifth Distributed Memory Computing Conference, 1990.\",\"volume\":\"88 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifth Distributed Memory Computing Conference, 1990.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DMCC.1990.555431\",\"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 of the Fifth Distributed Memory Computing Conference, 1990.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DMCC.1990.555431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An implementation is presented for JAC3D on a massively parallel hypercube computer. JACSD, a three dimensional finite element code developed at Sandia, uses several hundred hours of Cray time each year in solving structural analysis problems. Two major areas of investigation are discussed: (1) the development of general methods, data structures, and routines to communicate information between processors, and (2) the implementation and evaluation of four algorithms to map problems onto the node processors of the hypercube in a loadbalanced fashion. The performance of JACJD on the NCUBE/ten is compared with that on a Cray X-MP: the NCUBE/ten version presently takes 20% more compute time than the Cray. On a larger simulation which used more of the NCUBE's memory, the NCUBE/ten would take less compute time than the Cray. Current activity on the newer NCUBE 2 hypercube is summarized which should lead to an order of magnitude improvement in run-time performance for the massively parallel solution of structural analysis problems.