19063

stdgpu: Efficient STL-like Data Structures on the GPU

Patrick Stotko
University of Bonn
arXiv:1908.05936 [cs.DC], (16 Aug 2019)

@misc{stotko2019stdgpu,

   title={stdgpu: Efficient STL-like Data Structures on the GPU},

   author={Patrick Stotko},

   year={2019},

   eprint={1908.05936},

   archivePrefix={arXiv},

   primaryClass={cs.DC}

}

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 opensource 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.
Rating: 2.0/5. From 1 vote.
Please wait...

* * *

* * *

HGPU group © 2010-2019 hgpu.org

All rights belong to the respective authors

Contact us: