? 针对OBJ模型的GPU驱动可扩展解析器
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Journal of Computer Science and Technology 2018, Vol. 33 Issue (2) :417-428    DOI: 10.1007/s11390-018-1827-2
Computer Graphics and Multimedia << Previous Articles | >>
针对OBJ模型的GPU驱动可扩展解析器
Sunghun Jo, Yuna Jeong, Sungkil Lee*, Member, ACM
Department of Software, Sungkyunkwan University, Suwon 16419, Korea
GPU-Driven Scalable Parser for OBJ Models
Sunghun Jo, Yuna Jeong, Sungkil Lee*, Member, ACM
Department of Software, Sungkyunkwan University, Suwon 16419, Korea

摘要
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摘要 本文使用图形处理单元(GPUs),为大规模文本文件的处理提出了一个可扩展解析器框架。具体来说,我们解决方案的目的是为了有效解析Wavefront OBJ模型,其文本详细说明了它的3D几何图形及其拓扑。我们的工作基于它在语块加工方面的可扩展性和有效性。整个解析问题可以分为可多个子问题,这些子问题中的语块可以独立处理并无缝融合。内语块处理过程高度平行,由GPUs平衡。由此,本文提出的方法突破了现有的OBJ解析器的瓶颈。系统性能评估实验的结果显示我们的解决方案不仅显著地超越了现存的基于CPU的解决方案同时也超越了基于GPU的解决方案。
关键词3D模型   Wavefront OBJ   解析器   GPU     
Abstract: This paper presents a scalable parser framework using graphics processing units (GPUs) for massive text-based files. Specifically, our solution is designed to efficiently parse Wavefront OBJ models texts of which specify 3D geometries and their topology. Our work bases its scalability and efficiency on chunk-based processing. The entire parsing problem is subdivided into subproblems the chunk of which can be processed independently and merged seamlessly. The within-chunk processing is made highly parallel, leveraged by GPUs. Our approach thereby overcomes the bottlenecks of the existing OBJ parsers. Experiments performed to assess the performance of our system showed that our solutions significantly outperform the existing CPU-based solutions and GPU-based solutions as well.
Keywords3D model   Wavefront OBJ   parser   GPU     
Received 2017-01-02;
本文基金:

This work was supported in part by the Mid-career and Global Frontier (on Human-centered Interaction for Coexistence) Research and Development Programs through the National Research Foundation (NRF) under Grant Nos. 2015R1A2A2A01003783 and 2012M3A6A3055695, the Information Technology Research Center (ITRC) Program under Grant No. ⅡTP-2017-2016-0-00312 supervised by the Institute for Information and Communications Technology Promotion (ⅡTP), funded by the Korea Government (Ministry of Science, ICT (Information and Communications Technologies) and Future Planning), and Faculty Research Fund, Sungkyunkwan University, 2011.

通讯作者: Sungkil Lee     Email: sungkil@skku.edu
About author: Sunghun Jo received his B.S. degree in computer engineering at Hansei University, Gunpo City, in 2016. He is a M.S. student in computer engineering at Sungkyunkwan University, Suwon. His main research interest is real-time rendering
引用本文:   
Sunghun Jo, Yuna Jeong, Sungkil Lee.针对OBJ模型的GPU驱动可扩展解析器[J]  Journal of Computer Science and Technology , 2018,V33(2): 417-428
Sunghun Jo, Yuna Jeong, Sungkil Lee.GPU-Driven Scalable Parser for OBJ Models[J]  Journal of Computer Science and Technology, 2018,V33(2): 417-428
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