{"title":"流处理功能程序的自动映射","authors":"J. Dennis","doi":"10.1109/PMMPC.1995.504340","DOIUrl":null,"url":null,"abstract":"Functional programming languages are well suited to the expression and automatic mapping of parallel computations. The Paradigm compiler is being developed to automatically analyze and snap a class of Sisal programs amenable to static analysis for execution by distributed computer systems. A program description tree is constructed to represent the source program. In this form, the program is transformed into a hierarchy of acyclic interconnections of program modules (code blocks) of two basic types: array generators and stream producers. The program description tree is then used to guide decisions about allocation of processing elements to code blocks, and to construct of code for a target multiprocessor. We discuss the problem of finding an optimal allocation (mapping), and illustrate the methodology using a practical signal processing example.","PeriodicalId":344246,"journal":{"name":"Programming Models for Massively Parallel Computers","volume":"30 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Automatic mapping of stream-processing functional programs\",\"authors\":\"J. Dennis\",\"doi\":\"10.1109/PMMPC.1995.504340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Functional programming languages are well suited to the expression and automatic mapping of parallel computations. The Paradigm compiler is being developed to automatically analyze and snap a class of Sisal programs amenable to static analysis for execution by distributed computer systems. A program description tree is constructed to represent the source program. In this form, the program is transformed into a hierarchy of acyclic interconnections of program modules (code blocks) of two basic types: array generators and stream producers. The program description tree is then used to guide decisions about allocation of processing elements to code blocks, and to construct of code for a target multiprocessor. We discuss the problem of finding an optimal allocation (mapping), and illustrate the methodology using a practical signal processing example.\",\"PeriodicalId\":344246,\"journal\":{\"name\":\"Programming Models for Massively Parallel Computers\",\"volume\":\"30 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Programming Models for Massively Parallel Computers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PMMPC.1995.504340\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Programming Models for Massively Parallel Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PMMPC.1995.504340","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic mapping of stream-processing functional programs
Functional programming languages are well suited to the expression and automatic mapping of parallel computations. The Paradigm compiler is being developed to automatically analyze and snap a class of Sisal programs amenable to static analysis for execution by distributed computer systems. A program description tree is constructed to represent the source program. In this form, the program is transformed into a hierarchy of acyclic interconnections of program modules (code blocks) of two basic types: array generators and stream producers. The program description tree is then used to guide decisions about allocation of processing elements to code blocks, and to construct of code for a target multiprocessor. We discuss the problem of finding an optimal allocation (mapping), and illustrate the methodology using a practical signal processing example.