{"title":"动态的，面向对象的并行处理","authors":"A. Grimshaw, W. Strayer, P. Narayan","doi":"10.1109/88.218174","DOIUrl":null,"url":null,"abstract":"Mentat, a dynamic, object-oriented parallel-processing system that provides tools for constructing portable, medium-grain parallel software by combining an object-oriented approach with an underlying layered virtual-machine model is described. Mentat's three primary design objectives-high performance through parallel execution, easy parallelism, and software portability across a wide range of platforms-are reviewed. The performance of four applications of Mentat on two platforms-a 32-node Intel iPSC/2 hypercube and a network of 16 Sun IPC Sparcstations-are examined. The applications are DNA and protein sequence comparison, image convolution, Gaussian elimination and partial pivoting, and sparse matrix-vector multiplication. The performance of Mentat in these applications is compared to that of object-oriented parallel-processing systems, compiler-based distributed-memory systems, portable parallel-processing systems, and hand-coded implementations of the same applications.<<ETX>>","PeriodicalId":325213,"journal":{"name":"IEEE Parallel & Distributed Technology: Systems & Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"60","resultStr":"{\"title\":\"Dynamic, object-oriented parallel processing\",\"authors\":\"A. Grimshaw, W. Strayer, P. Narayan\",\"doi\":\"10.1109/88.218174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mentat, a dynamic, object-oriented parallel-processing system that provides tools for constructing portable, medium-grain parallel software by combining an object-oriented approach with an underlying layered virtual-machine model is described. Mentat's three primary design objectives-high performance through parallel execution, easy parallelism, and software portability across a wide range of platforms-are reviewed. The performance of four applications of Mentat on two platforms-a 32-node Intel iPSC/2 hypercube and a network of 16 Sun IPC Sparcstations-are examined. The applications are DNA and protein sequence comparison, image convolution, Gaussian elimination and partial pivoting, and sparse matrix-vector multiplication. The performance of Mentat in these applications is compared to that of object-oriented parallel-processing systems, compiler-based distributed-memory systems, portable parallel-processing systems, and hand-coded implementations of the same applications.<<ETX>>\",\"PeriodicalId\":325213,\"journal\":{\"name\":\"IEEE Parallel & Distributed Technology: Systems & Applications\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"60\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Parallel & Distributed Technology: Systems & Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/88.218174\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Parallel & Distributed Technology: Systems & Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/88.218174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mentat, a dynamic, object-oriented parallel-processing system that provides tools for constructing portable, medium-grain parallel software by combining an object-oriented approach with an underlying layered virtual-machine model is described. Mentat's three primary design objectives-high performance through parallel execution, easy parallelism, and software portability across a wide range of platforms-are reviewed. The performance of four applications of Mentat on two platforms-a 32-node Intel iPSC/2 hypercube and a network of 16 Sun IPC Sparcstations-are examined. The applications are DNA and protein sequence comparison, image convolution, Gaussian elimination and partial pivoting, and sparse matrix-vector multiplication. The performance of Mentat in these applications is compared to that of object-oriented parallel-processing systems, compiler-based distributed-memory systems, portable parallel-processing systems, and hand-coded implementations of the same applications.<>
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