Skip to main content

A single-tree algorithm to compute the Euclidean minimum spanning tree on GPUs...

by Andrey V Prokopenko, Piyush K Sao, Damien T Lebrun-grandie
Publication Type
Conference Paper
Book Title
Proceedings of the 51st International Conference on Parallel Processing
Publication Date
Page Numbers
1 to 10
Publisher Location
New York, NY, USA, United States of America
Conference Name
International Conference on Parallel Processing (ICPP)
Conference Location
Bordeaux, France
Conference Sponsor
Inria, Universite de Bordeaux, Intel
Conference Date

Computing the Euclidean minimum spanning tree (Emst) is a computationally demanding step of many algorithms. While work-efficient serial and multithreaded algorithms for computing Emst are known, designing an efficient GPU algorithm is challenging due to a complex branching structure, data dependencies, and load imbalances. In this paper, we propose a single-tree Borůvka-based algorithm for computing Emst on GPUs. We use an efficient nearest neighbor algorithm and reduce the number of the required distance calculations by avoiding traversing subtrees with leaf nodes in the same component. The developed algorithms are implemented in a performance portable way using ArborX, an open-source geometric search library based on the Kokkos framework. We evaluate the proposed algorithm on various 2D and 3D datasets, show and compare it with the current state-of-the-art open-source CPU implementations. We demonstrate 4-24 × speedup over the fastest multi-threaded implementation. We prove the portability of our implementation by providing results on a variety of hardware: AMD EPYC 7763, Nvidia A100 and AMD MI250X. We show scalability of the implementation, computing Emst for 37 million 3D cosmological dataset in under a 0.5 second on a single A100 Nvidia GPU.