Causal commutative arrows revisited

J. Yallop, Hai Liu
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引用次数: 5

Abstract

Causal commutative arrows (CCA) extend arrows with additional constructs and laws that make them suitable for modelling domains such as functional reactive programming, differential equations and synchronous dataflow. Earlier work has revealed that a syntactic transformation of CCA computations into normal form can result in significant performance improvements, sometimes increasing the speed of programs by orders of magnitude. In this work we reformulate the normalization as a type class instance and derive optimized observation functions via a specialization to stream transformers to demonstrate that the same dramatic improvements can be achieved without leaving the language.
重新审视因果交换箭头
因果交换箭头(CCA)用额外的构造和定律扩展了箭头,使它们适合于建模领域,如函数式响应式编程、微分方程和同步数据流。早期的研究表明,将CCA计算的语法转换为标准形式可以显著提高性能,有时可以将程序的速度提高几个数量级。在这项工作中,我们将规范化重新表述为类型类实例,并通过对流转换器的专门化获得优化的观察函数,以证明无需离开语言即可实现相同的显着改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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