stdgpu：基于GPU的高效STL类数据结构
stdgpu: Efficient STL-like Data Structures on the GPU
摘要：
并行计算和图形硬件的巨大进步在计算机视觉、计算机图形以及增强现实（AR）和虚拟现实（VR）领域开辟了若干新颖的实时GPU应用。尽管这些应用程序构建在提供高度优化算法的已建立的开源框架上，但它们通常带有自定义的自编写数据结构来管理底层数据。在这项工作中，我们提出了stdgpu，一个开源库，它定义了几个通用的GPU数据结构的快速和可靠的数据管理。我们的库并没有放弃以前建立的框架，而是旨在扩展它们，从而弥合CPU和GPU计算之间的差距。通过这种方式，它提供了干净和熟悉的界面，并无缝集成到新的和现有的项目中。我们希望促进统一CPU和GPU计算的进一步发展，并欢迎社区的贡献。
英文摘要：
Tremendous advances in parallel computing and graphics hardware opened up several novel real-time GPU applications in the fields of computer vision, computer graphics as well as augmented reality (AR) and virtual reality (VR). Although these applications built upon established open-source frameworks that provide highly optimized algorithms, they often come with custom self-written data structures to manage the underlying data. In this work, we present stdgpu, an open-source library which defines several generic GPU data structures for fast and reliable data management. Rather than abandoning previous established frameworks, our library aims to extend them, therefore bridging the gap between CPU and GPU computing. This way, it provides clean and familiar interfaces and integrates seamlessly into new as well as existing projects. We hope to foster further developments towards unified CPU and GPU computing and welcome contributions from the community.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
