{"title":"Arrp: a functional language with multi-dimensional signals and recurrence equations","authors":"Jakob Leben","doi":"10.1145/2975980.2975983","DOIUrl":null,"url":null,"abstract":"We present a new functional programming language for digital signal processing (DSP) named Arrp, in which signals are regarded as multi-dimensional arrays with an infinite dimension representing time, and defined using quasi-affine recurrence equations. An immediate benefit is an intuitive syntax that is very close to common mathematical notation used in DSP. Code reuse, especially in multi-dimensional and multi-rate signal processing, is supported through polymorphic and higher-order functions. We describe the differences between our approach and other paradigms in the domain, demonstrate the benefits of the language, and outline a method for compilation of the language into efficient C++ code using the polyhedral model. Preliminary experimental evaluation of our compiler shows that Arrp executes as fast or faster than hand-written C++ code, without explicit parallelization.","PeriodicalId":416294,"journal":{"name":"Proceedings of the 4th International Workshop on Functional Art, Music, Modelling, and Design","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Workshop on Functional Art, Music, Modelling, and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2975980.2975983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
We present a new functional programming language for digital signal processing (DSP) named Arrp, in which signals are regarded as multi-dimensional arrays with an infinite dimension representing time, and defined using quasi-affine recurrence equations. An immediate benefit is an intuitive syntax that is very close to common mathematical notation used in DSP. Code reuse, especially in multi-dimensional and multi-rate signal processing, is supported through polymorphic and higher-order functions. We describe the differences between our approach and other paradigms in the domain, demonstrate the benefits of the language, and outline a method for compilation of the language into efficient C++ code using the polyhedral model. Preliminary experimental evaluation of our compiler shows that Arrp executes as fast or faster than hand-written C++ code, without explicit parallelization.