B. Lippmeier, M. Chakravarty, G. Keller, Amos Robinson
Existing approaches to array fusion can deal with straight-line producer consumer pipelines, but cannot fuse branching data flows where a generated array is consumed by several different consumers. Branching data flows are common and natural to write, but a lack of fusion leads to the creation of an intermediate array at every branch point. We present a new array fusion system that handles branches, based on Waters's series expression framework, but extended to work in a functional setting. Our system also solves a related problem in stream fusion, namely the introduction of duplicate loop counters. We demonstrate speedup over existing fusion systems for several key examples.
{"title":"Data flow fusion with series expressions in Haskell","authors":"B. Lippmeier, M. Chakravarty, G. Keller, Amos Robinson","doi":"10.1145/2503778.2503782","DOIUrl":"https://doi.org/10.1145/2503778.2503782","url":null,"abstract":"Existing approaches to array fusion can deal with straight-line producer consumer pipelines, but cannot fuse branching data flows where a generated array is consumed by several different consumers. Branching data flows are common and natural to write, but a lack of fusion leads to the creation of an intermediate array at every branch point. We present a new array fusion system that handles branches, based on Waters's series expression framework, but extended to work in a functional setting. Our system also solves a related problem in stream fusion, namely the introduction of duplicate loop counters. We demonstrate speedup over existing fusion systems for several key examples.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134490507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Voellmy, Junchang Wang, P. Hudak, Kazuhiko Yamamoto
Haskell threads provide a key, lightweight concurrency abstraction to simplify the programming of important network applications such as web servers and software-defined network (SDN) controllers. The flagship Glasgow Haskell Compiler (GHC) introduces a run-time system (RTS) to achieve a high-performance multicore implementation of Haskell threads, by introducing effective components such as a multicore scheduler, a parallel garbage collector, an IO manager, and efficient multicore memory allocation. Evaluations of the GHC RTS, however, show that it does not scale well on multicore processors, leading to poor performance of many network applications that try to use lightweight Haskell threads. In this paper, we show that the GHC IO manager, which is a crucial component of the GHC RTS, is the scaling bottleneck. Through a series of experiments, we identify key data structure, scheduling, and dispatching bottlenecks of the GHC IO manager. We then design a new multicore IO manager named Mio that eliminates all these bottlenecks. Our evaluations show that the new Mio manager improves realistic web server throughput by 6.5x and reduces expected web server response time by 5.7x. We also show that with Mio, McNettle (an SDN controller written in Haskell) can scale effectively to 40+ cores, reach a throughput of over 20 million new requests per second on a single machine, and hence become the fastest of all existing SDN controllers.
{"title":"Mio: a high-performance multicore io manager for GHC","authors":"A. Voellmy, Junchang Wang, P. Hudak, Kazuhiko Yamamoto","doi":"10.1145/2503778.2503790","DOIUrl":"https://doi.org/10.1145/2503778.2503790","url":null,"abstract":"Haskell threads provide a key, lightweight concurrency abstraction to simplify the programming of important network applications such as web servers and software-defined network (SDN) controllers. The flagship Glasgow Haskell Compiler (GHC) introduces a run-time system (RTS) to achieve a high-performance multicore implementation of Haskell threads, by introducing effective components such as a multicore scheduler, a parallel garbage collector, an IO manager, and efficient multicore memory allocation. Evaluations of the GHC RTS, however, show that it does not scale well on multicore processors, leading to poor performance of many network applications that try to use lightweight Haskell threads. In this paper, we show that the GHC IO manager, which is a crucial component of the GHC RTS, is the scaling bottleneck. Through a series of experiments, we identify key data structure, scheduling, and dispatching bottlenecks of the GHC IO manager. We then design a new multicore IO manager named Mio that eliminates all these bottlenecks. Our evaluations show that the new Mio manager improves realistic web server throughput by 6.5x and reduces expected web server response time by 5.7x. We also show that with Mio, McNettle (an SDN controller written in Haskell) can scale effectively to 40+ cores, reach a throughput of over 20 million new requests per second on a single machine, and hence become the fastest of all existing SDN controllers.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114214814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although quantification over functions in QuickCheck properties has been supported from the beginning, displaying and shrinking them as counter examples has not. The reason is that in general, functions are infinite objects, which means that there is no sensible show function for them, and shrinking an infinite object within a finite number of steps seems impossible. This paper presents a general technique with which functions as counter examples can be shrunk to finite objects, which can then be displayed to the user. The approach turns out to be practically usable, which is shown by a number of examples. The two main limitations are that higher-order functions cannot be dealt with, and it is hard to deal with terms that contain functions as subterms.
{"title":"Shrinking and showing functions: (functional pearl)","authors":"Koen Claessen","doi":"10.1145/2364506.2364516","DOIUrl":"https://doi.org/10.1145/2364506.2364516","url":null,"abstract":"Although quantification over functions in QuickCheck properties has been supported from the beginning, displaying and shrinking them as counter examples has not. The reason is that in general, functions are infinite objects, which means that there is no sensible show function for them, and shrinking an infinite object within a finite number of steps seems impossible. This paper presents a general technique with which functions as counter examples can be shrunk to finite objects, which can then be displayed to the user. The approach turns out to be practically usable, which is shown by a number of examples. The two main limitations are that higher-order functions cannot be dealt with, and it is hard to deal with terms that contain functions as subterms.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115686094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Generic programming allows the concise expression of algorithms that would otherwise require large amounts of handwritten code. A number of such systems have been developed over the years, but a common drawback of these systems is poor runtime performance relative to handwritten, non-generic code. Generic-programming systems vary significantly in this regard, but few consistently match the performance of handwritten code. This poses a dilemma for developers. Generic-programming systems offer concision but cost performance. Handwritten code offers performance but costs concision. This paper explores the use of Template Haskell to achieve the best of both worlds. It presents a generic-programming system for Haskell that provides both the concision of other generic-programming systems and the efficiency of handwritten code. Our system gives the programmer a high-level, generic-programming interface, but uses Template Haskell to generate efficient, non-generic code that outperforms existing generic-programming systems for Haskell. This paper presents the results of benchmarking our system against both handwritten code and several other generic-programming systems. In these benchmarks, our system matches the performance of handwritten code while other systems average anywhere from two to twenty times slower.
{"title":"Template your boilerplate: using template haskell for efficient generic programming","authors":"Michael D. Adams, Thomas Dubuisson","doi":"10.1145/2364506.2364509","DOIUrl":"https://doi.org/10.1145/2364506.2364509","url":null,"abstract":"Generic programming allows the concise expression of algorithms that would otherwise require large amounts of handwritten code. A number of such systems have been developed over the years, but a common drawback of these systems is poor runtime performance relative to handwritten, non-generic code. Generic-programming systems vary significantly in this regard, but few consistently match the performance of handwritten code. This poses a dilemma for developers. Generic-programming systems offer concision but cost performance. Handwritten code offers performance but costs concision.\u0000 This paper explores the use of Template Haskell to achieve the best of both worlds. It presents a generic-programming system for Haskell that provides both the concision of other generic-programming systems and the efficiency of handwritten code. Our system gives the programmer a high-level, generic-programming interface, but uses Template Haskell to generate efficient, non-generic code that outperforms existing generic-programming systems for Haskell.\u0000 This paper presents the results of benchmarking our system against both handwritten code and several other generic-programming systems. In these benchmarks, our system matches the performance of handwritten code while other systems average anywhere from two to twenty times slower.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114676179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In mathematics, an enumeration of a set S is a bijective function from (an initial segment of) the natural numbers to S. We define "functional enumerations" as efficiently computable such bijections. This paper describes a theory of functional enumeration and provides an algebra of enumerations closed under sums, products, guarded recursion and bijections. We partition each enumerated set into numbered, finite subsets. We provide a generic enumeration such that the number of each part corresponds to the size of its values (measured in the number of constructors). We implement our ideas in a Haskell library called testing-feat, and make the source code freely available. Feat provides efficient "random access" to enumerated values. The primary application is property-based testing, where it is used to define both random sampling (for example QuickCheck generators) and exhaustive enumeration (in the style of SmallCheck). We claim that functional enumeration is the best option for automatically generating test cases from large groups of mutually recursive syntax tree types. As a case study we use Feat to test the pretty-printer of the Template Haskell library (uncovering several bugs).
{"title":"Feat: functional enumeration of algebraic types","authors":"Jonas Duregård, Patrik Jansson, Meng Wang","doi":"10.1145/2364506.2364515","DOIUrl":"https://doi.org/10.1145/2364506.2364515","url":null,"abstract":"In mathematics, an enumeration of a set S is a bijective function from (an initial segment of) the natural numbers to S. We define \"functional enumerations\" as efficiently computable such bijections. This paper describes a theory of functional enumeration and provides an algebra of enumerations closed under sums, products, guarded recursion and bijections. We partition each enumerated set into numbered, finite subsets.\u0000 We provide a generic enumeration such that the number of each part corresponds to the size of its values (measured in the number of constructors). We implement our ideas in a Haskell library called testing-feat, and make the source code freely available. Feat provides efficient \"random access\" to enumerated values. The primary application is property-based testing, where it is used to define both random sampling (for example QuickCheck generators) and exhaustive enumeration (in the style of SmallCheck). We claim that functional enumeration is the best option for automatically generating test cases from large groups of mutually recursive syntax tree types. As a case study we use Feat to test the pretty-printer of the Template Haskell library (uncovering several bugs).","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131045228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haskell programmers have been experimenting with dependent types for at least a decade, using clever encodings that push the limits of the Haskell type system. However, the cleverness of these encodings is also their main drawback. Although the ideas are inspired by dependently typed programs, the code looks significantly different. As a result, GHC implementors have responded with extensions to Haskell's type system, such as GADTs, type families, and datatype promotion. However, there remains a significant difference between programming in Haskell and in full-spectrum dependently typed languages. Haskell enforces a phase separation between runtime values and compile-time types. Therefore, singleton types are necessary to express the dependency between values and types. These singleton types introduce overhead and redundancy for the programmer. This paper presents the singletons library, which generates the boilerplate code necessary for dependently typed programming using GHC. To compare with full-spectrum languages, we present an extended example based on an Agda interface for safe database access. The paper concludes with a detailed discussion on the current capabilities of GHC for dependently typed programming and suggestions for future extensions to better support this style of programming.
{"title":"Dependently typed programming with singletons","authors":"R. Eisenberg, Stephanie Weirich","doi":"10.1145/2364506.2364522","DOIUrl":"https://doi.org/10.1145/2364506.2364522","url":null,"abstract":"Haskell programmers have been experimenting with dependent types for at least a decade, using clever encodings that push the limits of the Haskell type system. However, the cleverness of these encodings is also their main drawback. Although the ideas are inspired by dependently typed programs, the code looks significantly different. As a result, GHC implementors have responded with extensions to Haskell's type system, such as GADTs, type families, and datatype promotion. However, there remains a significant difference between programming in Haskell and in full-spectrum dependently typed languages. Haskell enforces a phase separation between runtime values and compile-time types. Therefore, singleton types are necessary to express the dependency between values and types. These singleton types introduce overhead and redundancy for the programmer.\u0000 This paper presents the singletons library, which generates the boilerplate code necessary for dependently typed programming using GHC. To compare with full-spectrum languages, we present an extended example based on an Agda interface for safe database access. The paper concludes with a detailed discussion on the current capabilities of GHC for dependently typed programming and suggestions for future extensions to better support this style of programming.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129059500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrew Farmer, Andy Gill, E. Komp, Neil Sculthorpe
The importance of reasoning about and refactoring programs is a central tenet of functional programming. Yet our compilers and development toolchains only provide rudimentary support for these tasks. This paper introduces a programmatic and compiler-centric interface that facilitates refactoring and equational reasoning. To develop our ideas, we have implemented HERMIT, a toolkit enabling informal but systematic transformation of Haskell programs from inside the Glasgow Haskell Compiler's optimization pipeline. With HERMIT, users can experiment with optimizations and equational reasoning, while the tedious heavy lifting of performing the actual transformations is done for them. HERMIT provides a transformation API that can be used to build higher-level rewrite tools. One use-case is prototyping new optimizations as clients of this API before being committed to the GHC toolchain. We describe a HERMIT application - a read-eval-print shell for performing transformations using HERMIT. We also demonstrate using this shell to prototype an optimization on a specific example, and report our initial experiences and remaining challenges.
{"title":"The HERMIT in the machine: a plugin for the interactive transformation of GHC core language programs","authors":"Andrew Farmer, Andy Gill, E. Komp, Neil Sculthorpe","doi":"10.1145/2364506.2364508","DOIUrl":"https://doi.org/10.1145/2364506.2364508","url":null,"abstract":"The importance of reasoning about and refactoring programs is a central tenet of functional programming. Yet our compilers and development toolchains only provide rudimentary support for these tasks. This paper introduces a programmatic and compiler-centric interface that facilitates refactoring and equational reasoning. To develop our ideas, we have implemented HERMIT, a toolkit enabling informal but systematic transformation of Haskell programs from inside the Glasgow Haskell Compiler's optimization pipeline. With HERMIT, users can experiment with optimizations and equational reasoning, while the tedious heavy lifting of performing the actual transformations is done for them.\u0000 HERMIT provides a transformation API that can be used to build higher-level rewrite tools. One use-case is prototyping new optimizations as clients of this API before being committed to the GHC toolchain. We describe a HERMIT application - a read-eval-print shell for performing transformations using HERMIT. We also demonstrate using this shell to prototype an optimization on a specific example, and report our initial experiences and remaining challenges.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122597012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Polls and surveys are increasingly employed to gather information about attitudes and experiences of all kinds of populations and user groups. The ultimate purpose of a survey is to identify trends and relationships that can inform decision makers. To this end, the data gathered by a survey must be appropriately analyzed. Most of the currently existing tools focus on the user interface aspect of the data collection task, but pay little attention to the structure and type of the collected data, which are usually represented as potentially tag-annotated, but otherwise unstructured, plain text. This makes the task of writing data analysis programs often difficult and error-prone, whereas a typed data representation could support the writing of type-directed data analysis tools that would enjoy the many benefits of static typing. In this paper we present Surveyor, a DSEL that allows the compositional construction of typed surveys, where the types describe the structure of the data to be collected. A survey can be run to gather typed data, which can then be subjected to analysis tools that are built using Surveyor's typed combinators. Altogether the Surveyor DSEL realizes a strongly typed and type-directed approach to data gathering and analysis. The implementation of our DSEL is based on GADTs to allow a flexible, yet strongly typed representation of surveys. Moreover, the implementation employs the Scrap-Your-Boilerplate library to facilitate the type-dependent traversal, extraction, and combination of data gathered from surveys.
越来越多地采用民意测验和调查来收集关于各种人口和用户群体的态度和经验的信息。调查的最终目的是确定趋势和关系，以便为决策者提供信息。为此，必须对调查收集的数据进行适当的分析。目前现有的大多数工具都侧重于数据收集任务的用户界面方面，但很少关注所收集数据的结构和类型，这些数据通常表示为潜在的标记注释，但在其他方面是非结构化的纯文本。这使得编写数据分析程序的任务通常很困难且容易出错，而类型化数据表示可以支持编写面向类型的数据分析工具，从而享受静态类型的许多好处。在本文中，我们介绍了Surveyor，这是一个DSEL，它允许组合构建类型调查，其中类型描述要收集的数据的结构。可以运行调查来收集类型化数据，然后将其置于使用Surveyor的类型化组合器构建的分析工具中。总之，Surveyor DSEL实现了一种强类型和类型导向的数据收集和分析方法。我们的DSEL的实现基于gadt，以允许灵活的、强类型的调查表示。此外，该实现使用了scrapi - your - boilerplate库来促进从调查中收集的数据的依赖类型的遍历、提取和组合。
{"title":"Surveyor: a DSEL for representing and analyzing strongly typed surveys","authors":"W. Allen, Martin Erwig","doi":"10.1145/2364506.2364518","DOIUrl":"https://doi.org/10.1145/2364506.2364518","url":null,"abstract":"Polls and surveys are increasingly employed to gather information about attitudes and experiences of all kinds of populations and user groups. The ultimate purpose of a survey is to identify trends and relationships that can inform decision makers. To this end, the data gathered by a survey must be appropriately analyzed.\u0000 Most of the currently existing tools focus on the user interface aspect of the data collection task, but pay little attention to the structure and type of the collected data, which are usually represented as potentially tag-annotated, but otherwise unstructured, plain text. This makes the task of writing data analysis programs often difficult and error-prone, whereas a typed data representation could support the writing of type-directed data analysis tools that would enjoy the many benefits of static typing.\u0000 In this paper we present Surveyor, a DSEL that allows the compositional construction of typed surveys, where the types describe the structure of the data to be collected. A survey can be run to gather typed data, which can then be subjected to analysis tools that are built using Surveyor's typed combinators. Altogether the Surveyor DSEL realizes a strongly typed and type-directed approach to data gathering and analysis.\u0000 The implementation of our DSEL is based on GADTs to allow a flexible, yet strongly typed representation of surveys. Moreover, the implementation employs the Scrap-Your-Boilerplate library to facilitate the type-dependent traversal, extraction, and combination of data gathered from surveys.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124220406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This report documents the insights gained from implementing the core functionality of xmonad, a popular window manager written in Haskell, in the Coq proof assistant. Rather than focus on verification, this report outlines the technical challenges involved with incorporating Coq code in a Haskell project.
{"title":"xmonad in Coq (experience report): programming a window manager in a proof assistant","authors":"Wouter Swierstra","doi":"10.1145/2364506.2364523","DOIUrl":"https://doi.org/10.1145/2364506.2364523","url":null,"abstract":"This report documents the insights gained from implementing the core functionality of xmonad, a popular window manager written in Haskell, in the Coq proof assistant. Rather than focus on verification, this report outlines the technical challenges involved with incorporating Coq code in a Haskell project.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116182855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a refined approach to parallel array fusion that uses indexed types to specify the internal representation of each array. Our approach aids the client programmer in reasoning about the performance of their program in terms of the source code. It also makes the intermediate code easier to transform at compile-time, resulting in faster compilation and more reliable runtimes. We demonstrate how our new approach improves both the clarity and performance of several end-user written programs, including a fluid flow solver and an interpolator for volumetric data.
{"title":"Guiding parallel array fusion with indexed types","authors":"B. Lippmeier, M. Chakravarty, G. Keller, S. Jones","doi":"10.1145/2364506.2364511","DOIUrl":"https://doi.org/10.1145/2364506.2364511","url":null,"abstract":"We present a refined approach to parallel array fusion that uses indexed types to specify the internal representation of each array. Our approach aids the client programmer in reasoning about the performance of their program in terms of the source code. It also makes the intermediate code easier to transform at compile-time, resulting in faster compilation and more reliable runtimes. We demonstrate how our new approach improves both the clarity and performance of several end-user written programs, including a fluid flow solver and an interpolator for volumetric data.","PeriodicalId":188691,"journal":{"name":"ACM SIGPLAN Symposium/Workshop on Haskell","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129851699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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