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.
翻译:尽管范围查询在分析和可视化高频PC应用方面发挥着关键作用,但没有对旨在加速范围查询的指数及其在高频PC环境中的可行程度进行全面分析。在实践文件的这一阶段,我们提出第一次这种评价,审查了20个支持范围查询的开放源C和C+++图书馆。本文的贡献包括回答下列问题:在高频PC环境中,哪些实施是可行的,这些图书馆如何在时间、查询时间、记忆使用和可扩展性方面进行比较,这些实施之间有哪些其他的权衡,是否有单一的总体最佳解决办法,以及何时布鲁特力解决办法能提供最佳的绩效?我们还分享在这一过程中获得的重要见解,它能够帮助高频PC应用科学家和空间指数开发者。