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Faster geometric algorithms via dynamic determinant computation. (English) Zbl 1338.65118
Summary: The computation of determinants or their signs is the core procedure in many important geometric algorithms, such as convex hull, volume and point location. As the dimension of the computation space grows, a higher percentage of the total computation time is consumed by these computations. In this paper we study the sequences of determinants that appear in geometric algorithms. The computation of a single determinant is accelerated by using the information from the previous computations in that sequence. We propose two dynamic determinant algorithms with quadratic arithmetic complexity when employed in convex hull and volume computations, and with linear arithmetic complexity when used in point location problems. We implement the proposed algorithms and perform an extensive experimental analysis. On one hand, our analysis serves as a performance study of state-of-the-art determinant algorithms and implementations. On the other hand, we demonstrate the supremacy of our methods over state-of-the- art implementations of determinant and geometric algorithms. Our experimental results include a $$20$$ and $$78$$ times speed-up in volume and point location computations in dimension $$6$$ and $$11$$, respectively.

MSC:
 65F40 Numerical computation of determinants 65D18 Numerical aspects of computer graphics, image analysis, and computational geometry
Software:
CGAL; Eigen; Hull; LinBox; polymake; TOPCOM; triangulation
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