Efficient GPU Implementation of Affine Index Permutations on Arrays
Paper i proceeding, 2023

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.

functional languages

GPU

data-parallelism

Författare

Mathis Bouverot-Dupuis

Ecole Normale Superieure (ENS)

Mary Sheeran

Chalmers, Data- och informationsteknik, Funktionell programmering

FHPNC 2023 - Proceedings of the 11th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing, Co-located with ICFP 2023

15-28
9798400702969 (ISBN)

11th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing, FHPNC 2023, co-located with ICFP
Seattle, USA,

En algebra av tensorkombinerare och dess tillämpningar

Vetenskapsrådet (VR) (2021-05491), 2021-12-01 -- 2025-12-31.

Ämneskategorier

Datavetenskap (datalogi)

DOI

10.1145/3609024.3609411

Mer information

Senast uppdaterat

2023-10-27