{"title":"Python骨架库的新列表骨架","authors":"F. Loulergue, Jolan Philippe","doi":"10.1109/PDCAT46702.2019.00077","DOIUrl":null,"url":null,"abstract":"Algorithmic skeletons are patterns of parallel computations. Skeletal parallel programming eases parallel programming: a program is merely a composition of such patterns. Data-parallel skeletons operate on parallel data-structures that have often sequential counterparts. In algorithmic skeleton approaches that offer a global view of programs, a parallel program has therefore a structure similar to a sequential program but operates on parallel data-structures. PySke is such an algorithmic skeleton library for Python to program shared or distributed memory parallel architectures in a simple way. This paper presents an extension to PySke: new algorithmic skeletons on parallel lists. This extension is evaluated on an application.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New List Skeletons for the Python Skeleton Library\",\"authors\":\"F. Loulergue, Jolan Philippe\",\"doi\":\"10.1109/PDCAT46702.2019.00077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Algorithmic skeletons are patterns of parallel computations. Skeletal parallel programming eases parallel programming: a program is merely a composition of such patterns. Data-parallel skeletons operate on parallel data-structures that have often sequential counterparts. In algorithmic skeleton approaches that offer a global view of programs, a parallel program has therefore a structure similar to a sequential program but operates on parallel data-structures. PySke is such an algorithmic skeleton library for Python to program shared or distributed memory parallel architectures in a simple way. This paper presents an extension to PySke: new algorithmic skeletons on parallel lists. This extension is evaluated on an application.\",\"PeriodicalId\":166126,\"journal\":{\"name\":\"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDCAT46702.2019.00077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDCAT46702.2019.00077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New List Skeletons for the Python Skeleton Library
Algorithmic skeletons are patterns of parallel computations. Skeletal parallel programming eases parallel programming: a program is merely a composition of such patterns. Data-parallel skeletons operate on parallel data-structures that have often sequential counterparts. In algorithmic skeleton approaches that offer a global view of programs, a parallel program has therefore a structure similar to a sequential program but operates on parallel data-structures. PySke is such an algorithmic skeleton library for Python to program shared or distributed memory parallel architectures in a simple way. This paper presents an extension to PySke: new algorithmic skeletons on parallel lists. This extension is evaluated on an application.