Automatic SIMD vectorization for Haskell

Author:

Petersen Leaf1,Orchard Dominic2,Glew Neal1

Affiliation:

1. Intel Corporation, Santa Clara, CA, USA

2. University of Cambridge, Cambridge, United Kingdom

Abstract

Expressing algorithms using immutable arrays greatly simplifies the challenges of automatic SIMD vectorization, since several important classes of dependency violations cannot occur. The Haskell programming language provides libraries for programming with immutable arrays, and compiler support for optimizing them to eliminate the overhead of intermediate temporary arrays. We describe an implementation of automatic SIMD vectorization in a Haskell compiler which gives substantial vector speedups for a range of programs written in a natural programming style. We compare performance with that of programs compiled by the Glasgow Haskell Compiler.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Modern Look at GRIN, an Optimizing Functional Language Back End;Acta Cybernetica;2021-02-03

2. Pure Functions in C: A Small Keyword for Automatic Parallelization;International Journal of Parallel Programming;2020-05-30

3. Measuring the Haskell Gap;Proceedings of the 25th symposium on Implementation and Application of Functional Languages - IFL '13;2014

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