{"title":"PySke: Python的算法骨架","authors":"Jolan Philippe, F. Loulergue","doi":"10.1109/HPCS48598.2019.9188151","DOIUrl":null,"url":null,"abstract":"PySke is a library of parallel algorithmic skeletons in Python designed for list and tree data structures. Such algorithmic skeletons are high-order functions implemented in parallel. An application developed with PySke is a composition of skeletons. To ease the write of parallel programs, PySke does not follow the Single Program Multiple Data (SPMD) paradigm but offers a global view of parallel programs to users. This approach aims at writing scalable programs easily. In addition to the library, we present experiments performed on a highperformance computing cluster (distributed memory) on a set of example applications developed with PySke.","PeriodicalId":371856,"journal":{"name":"2019 International Conference on High Performance Computing & Simulation (HPCS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"PySke: Algorithmic Skeletons for Python\",\"authors\":\"Jolan Philippe, F. Loulergue\",\"doi\":\"10.1109/HPCS48598.2019.9188151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PySke is a library of parallel algorithmic skeletons in Python designed for list and tree data structures. Such algorithmic skeletons are high-order functions implemented in parallel. An application developed with PySke is a composition of skeletons. To ease the write of parallel programs, PySke does not follow the Single Program Multiple Data (SPMD) paradigm but offers a global view of parallel programs to users. This approach aims at writing scalable programs easily. In addition to the library, we present experiments performed on a highperformance computing cluster (distributed memory) on a set of example applications developed with PySke.\",\"PeriodicalId\":371856,\"journal\":{\"name\":\"2019 International Conference on High Performance Computing & Simulation (HPCS)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on High Performance Computing & Simulation (HPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCS48598.2019.9188151\",\"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 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCS48598.2019.9188151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PySke is a library of parallel algorithmic skeletons in Python designed for list and tree data structures. Such algorithmic skeletons are high-order functions implemented in parallel. An application developed with PySke is a composition of skeletons. To ease the write of parallel programs, PySke does not follow the Single Program Multiple Data (SPMD) paradigm but offers a global view of parallel programs to users. This approach aims at writing scalable programs easily. In addition to the library, we present experiments performed on a highperformance computing cluster (distributed memory) on a set of example applications developed with PySke.