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Modular Resultant Algorithm for Graphics Processors

机译:图形处理器的模块化结果算法

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In this paper we report on the recent progress in computing bivariate polynomial resultants on Graphics Processing Units (GPU). Given two polynomials in Z[x, y], our algorithm first maps the polynomials to a prime field. Then, each modular image is processed individually. The GPU evaluates the polynomials at a number of points and computes univariate modular resultants in parallel. The remaining "combine" stage of the algorithm is executed sequentially on the host machine. Porting this stage to the graphics hardware is an object of ongoing research. Our algorithm is based on an efficient modular arithmetic from [1]. With the theory of displacement structure we have been able to parallelize the resultant algorithm up to a very fine scale suitable for realization on the GPU. Our benchmarks show a substantial speed-up over a host-based resultant algorithm [2] from CGAL (www.cgal.org).
机译:在本文中,我们报告了在图形处理单元(GPU)上计算二元多项式结果的最新进展。给定Z [x,y]中的两个多项式,我们的算法首先将多项式映射到素数域。然后,分别处理每个模块化图像。 GPU在多个点评估多项式,并并行计算单变量模块化结果。该算法的其余“组合”阶段在主机上顺序执行。将此阶段移植到图形硬件是正在进行的研究的目标。我们的算法基于[1]中的高效模块化算法。借助位移结构理论,我们已经能够将所得算法并行化至非常适合在GPU上实现的非常精细的比例。我们的基准测试显示,与CGAL(www.cgal.org)的基于主机的结果算法相比,速度有了显着提高[2]。

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