...
首页> 外文期刊>IEEE transactions on visualization and computer graphics >Flip to Regular Triangulation and Convex Hull
【24h】

Flip to Regular Triangulation and Convex Hull

机译:翻转规则三角剖分和凸包

获取原文
获取原文并翻译 | 示例
           

摘要

Flip is a simple and local operation to transform one triangulation to another. It makes changes only to some neighboring simplices, without considering any attribute or configuration global in nature to the triangulation. Thanks to this characteristic, several flips can be independently applied to different small, non-overlapping regions of one triangulation. Such operation is favored when designing algorithms for data-parallel, massively multithreaded hardware, such as the GPU. However, most existing flip algorithms are designed to be executed sequentially, and usually need some restrictions on the execution order of flips, making them hard to be adapted to parallel computation. In this paper, we present an in depth study of flip algorithms in low dimensions, with the emphasis on the flexibility of their execution order. In particular, we propose a series of provably correct flip algorithms for regular triangulation and convex hull in 2D and 3D, with implementations for both CPUs and GPUs. Our experiment shows that our GPU implementation for constructing these structures from a given point set achieves up to two orders of magnitude of speedup over other popular single-threaded CPU implementation of existing algorithms.
机译:翻转是一种简单的本地操作,可以将一个三角剖分转换为另一个三角剖分。它仅对某些相邻的单形进行更改,而没有考虑对三角剖分本质上全局的任何属性或配置。由于这一特性,可以将多个翻转分别应用于一个三角测量的不同小,非重叠区域。在设计用于数据并行,大规模多线程硬件(例如GPU)的算法时,此类操作非常有用。然而,大多数现有的翻转算法被设计为顺序执行,并且通常需要对翻转的执行顺序进行一些限制,从而使其难以适应并行计算。在本文中,我们将对低维翻转算法进行深入研究,重点是执行顺序的灵活性。特别是,我们针对2D和3D中的常规三角剖分和凸包提出了一系列可证明正确的翻转算法,并针对CPU和GPU进行了实现。我们的实验表明,与现有算法的其他流行单线程CPU实现相比,用于从给定点集构造这些结构的GPU实现实现高达两个数量级的加速。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号