Despite the critical role that range queries play in analysis and visualization for HPC applications, there has been no comprehensive analysis of indices that are designed to accelerate range queries and the extent to which they are viable in an HPC setting. In this state of the practice paper we present the first such evaluation, examining 20 open-source C and C++ libraries that support range queries. Contributions of this paper include answering the following questions: which of the implementations are viable in an HPC setting, how do these libraries compare in terms of build time, query time, memory usage, and scalability, what are other trade-offs between these implementations, is there a single overall best solution, and when does a brute force solution offer the best performance? We also share key insights learned during this process that can assist both HPC application scientists and spatial index developers.
@article{arxiv.2106.13972,
title = {Exploring Spatial Indexing for Accelerated Feature Retrieval in HPC},
author = {Margaret Lawson and William Gropp and Jay Lofstead},
journal= {arXiv preprint arXiv:2106.13972},
year = {2021}
}