Affiliation:
1. University of Victoria, Victoria, Canada
Abstract
We present a method for compilation of multi-dimensional stream processing programs from affine recurrence equations with unbounded domains into imperative code with statically allocated memory. The method involves a novel polyhedral schedule transformation called periodic tiling. It accommodates existing polyhedral optimizations to improve memory access patterns and expose parallelism. This enables efficient execution of programming languages with unbounded recurrence equations, as well as optimization of existing languages from which this form can be derived. The method is experimentally evaluated on 5 DSP algorithms with large problem sizes. Results show potential for improved throughput compared to hand-optimized C++ (speedups on a 6-core Intel Xeon CPU up to 10× with a geometric mean 3.3×).
1
Funder
Natural Sciences and Engineering Research Council of Canada
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Information Systems,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. Towards intelligent compiler optimization;2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO);2022-05-23
2. The w-calculus: a synchronous framework for the verified modelling of digital signal processing algorithms;Proceedings of the 9th ACM SIGPLAN International Workshop on Functional Art, Music, Modelling, and Design;2021-08-22
3. Polyhedral Compilation for Multi-dimensional Stream Processing;ACM Transactions on Architecture and Code Optimization;2019-09-30