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Fast OBJ file importing and parsing in CUDA

机译:在CUDA中快速导入和解析OBJ文件

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摘要

Alias-Wavefront OBJ meshes are a common text file type for transferring 3D mesh data between applications made by different vendors. However, as the mesh complexity gets higher and denser, the files become larger and slower to import. This paper explores the use of GPUs to accelerate the importing and parsing of OBJ files by studying file read-time, runtime, and load resistance. We propose a new method of reading and parsing that circumvents GPU architecture limitations and improves performance, seeing the new GPU method outperforms CPU methods with a 6× - 8× speedup. When running on a heavily loaded system, the new method only received an 80% performance hit, compared to the 160% that the CPU methods received. The loaded GPU speedup compared to unloaded CPU methods was 3.5×, and, when compared to loaded CPU methods, 8×. These results demonstrate that the time is right for further research into the use of data-parallel GPU acceleration beyond that of computer graphics and high performance computing.
机译:Alias-Wavefront OBJ网格是一种常见的文本文件类型,用于在不同供应商生产的应用程序之间传输3D网格数据。但是,随着网格复杂度变得越来越高和越来越密集,文件变得越来越大,导入的速度也越来越慢。本文通过研究文件读取时间,运行时和负载阻力,探索了GPU的使用来加速OBJ文件的导入和解析。我们提出了一种新的读取和解析方法,该方法可以克服GPU架构的局限性并提高性能,因为新的GPU方法以6倍-8倍的加速性能胜过CPU方法。当在高负载的系统上运行时,新方法仅获得80%的性能下降,而CPU方法仅获得160%的性能下降。与未加载的CPU方法相比,已加载的GPU速度为3.5倍,与已加载的CPU方法相比,为8倍。这些结果表明,现在是进一步研究使用并行数据GPU加速的时机,而不仅仅是计算机图形学和高性能计算。

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