Efficient GPU Implementation of Affine Index Permutations on Arrays

Mathis Bouverot-Dupuis, M. Sheeran
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Abstract

Optimal usage of the memory system is a key element of fast GPU algorithms. Unfortunately many common algorithms fail in this regard despite exhibiting great regularity in memory access patterns. In this paper we propose efficient kernels to permute the elements of an array. We handle a class of permutations known as Bit Matrix Multiply Complement (BMMC) permutations, for which we design kernels of speed comparable to that of a simple array copy. This is a first step towards implementing a set of array combinators based on these permutations.
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阵列上仿射索引排列的高效GPU实现
内存系统的最佳使用是快速GPU算法的关键因素。不幸的是,许多常见的算法在这方面失败了,尽管在内存访问模式中表现出很大的规律性。在本文中,我们提出了一个有效的核来排列数组的元素。我们处理一类称为位矩阵乘补排列(BMMC)的排列,为此我们设计了速度与简单数组复制相当的内核。这是实现一组基于这些排列的数组组合子的第一步。
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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Rank-Polymorphism for Shape-Guided Blocking Shape-Constrained Array Programming with Size-Dependent Types Efficient GPU Implementation of Affine Index Permutations on Arrays Proceedings of the 11th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing
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