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Analysis of symmetry groups of box-splines for evaluation on GPUs

机译:箱形样条的对称组分析以在GPU上评估

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In this paper we analyze the symmetry groups of box-splines for efficient analytic evaluation of splines and their derivatives on GPUs (Graphics Processing Units). Given a box-spline, we first analyze its polynomial structure and find its space group which is composed of a point group and a translational group on the domain lattice. To evaluate a spline generated by the box-spline (or its derivative) function, the point group is decomposed into right cosets such that all the polytopes in the same coset share the same analytic polynomial formula. Moreover, by leveraging their symmetries, sufficient number of linearly independent derivative functions of the same order are chosen such that they have a change-of-variables relation with each other. Our OpenCL implementations show that our method is at least approximate to 30% faster but the kernel is at least approximate to 30% smaller compared with the other techniques. (C) 2017 Elsevier Inc. All rights reserved.
机译:在本文中,我们分析了箱形样条的对称组,以便在GPU(图形处理单元)上对样条及其衍生物进行有效的分析评估。给定一个箱形样条,我们首先分析其多项式结构并找到其空间组,该空间组由域格上的一个点组和一个平移组组成。为了评估由盒样条曲线(或其导数)函数生成的样条曲线,将点组分解为正确的陪集,以使同一陪集中的所有多面体共享相同的解析多项式。此外,通过利用它们的对称性,选择足够数量的相同阶数的线性独立的导数函数,使得它们彼此具有变量变化关系。我们的OpenCL实现显示,与其他技术相比,我们的方法至少快30%,但内核至少小30%。 (C)2017 Elsevier Inc.保留所有权利。

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