# ArborX: A Performance Portable Geometric Search Library

arXiv: https://arxiv.org/abs/1908.11807 · HTML: https://mlsanity.com/paper/1908.11807/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Aug 2019.

## Built on by (most cited first, 1 of 1)

- [PANDORA: A Parallel Dendrogram Construction Algorithm for Single Linkage Clustering on GPU](https://mlsanity.com/paper/2401.06089/) (2024)

## Abstract (arXiv)

Searching for geometric objects that are close in space is a fundamental component of many applications. The performance of search algorithms comes to the forefront as the size of a problem increases both in terms of total object count as well as in the total number of search queries performed. Scientific applications requiring modern leadership-class supercomputers also pose an additional requirement of performance portability, i.e. being able to efficiently utilize a variety of hardware architectures. In this paper, we introduce a new open-source C++ search library, ArborX, which we have designed for modern supercomputing architectures. We examine scalable search algorithms with a focus on performance, including a highly efficient parallel bounding volume hierarchy implementation, and propose a flexible interface making it easy to integrate with existing applications. We demonstrate the performance portability of ArborX on multi-core CPUs and GPUs, and compare it to the state-of-the-art libraries such as Boost.Geometry.Index and nanoflann.