{"title":"数据优化:最小化SIMD机器上残留的处理器间数据移动","authors":"K. Knobe, V. Natarajan","doi":"10.1109/FMPC.1990.89492","DOIUrl":null,"url":null,"abstract":"Basic concepts in array layout are summarized, and unhonored preferences and residual data motion are discussed. A technique for minimizing such motion is presented. For each array the source program is divided into regions, each associated with a single home. This enables efficient handling of residual data motion. The partitioning into regions is based on control flow and data dependence. Preliminary results obtained with this technique show an order-of-magnitude improvement for certain classes of programs.<<ETX>>","PeriodicalId":193332,"journal":{"name":"[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":"{\"title\":\"Data optimization: minimizing residual interprocessor data motion on SIMD machines\",\"authors\":\"K. Knobe, V. Natarajan\",\"doi\":\"10.1109/FMPC.1990.89492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Basic concepts in array layout are summarized, and unhonored preferences and residual data motion are discussed. A technique for minimizing such motion is presented. For each array the source program is divided into regions, each associated with a single home. This enables efficient handling of residual data motion. The partitioning into regions is based on control flow and data dependence. Preliminary results obtained with this technique show an order-of-magnitude improvement for certain classes of programs.<<ETX>>\",\"PeriodicalId\":193332,\"journal\":{\"name\":\"[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"37\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FMPC.1990.89492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FMPC.1990.89492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data optimization: minimizing residual interprocessor data motion on SIMD machines
Basic concepts in array layout are summarized, and unhonored preferences and residual data motion are discussed. A technique for minimizing such motion is presented. For each array the source program is divided into regions, each associated with a single home. This enables efficient handling of residual data motion. The partitioning into regions is based on control flow and data dependence. Preliminary results obtained with this technique show an order-of-magnitude improvement for certain classes of programs.<>