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Abstract: We present parallel computational geometry algorithms that are scalable, architecture independent, easy to implement, and have, with high probability, an optimal time complexity for uniformly distributed random input data. Our methods apply to multicomputers with arbitrary interconnection network or bus system. (Update)
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BibTeX entry: (Update)
@misc{ probability-scalable,
author = "With High Probability",
title = "Scalable And Architecture Independent Parallel Geometric Algorithms",
url = "citeseer.ist.psu.edu/656970.html" }
Citations (may not include all citations):1749 An introduction to probability theory and its applications (context) - Feller - 1950
91 The quickhull algorithm for convex hull - Barber, Dobkin et al. - 1993
69 Optimal expected time algorithms for closest point problems (context) - Bentley, Yao - 1980
64 Scalable parallel computational geometry for coarse grained .. - Dehne, Fabri et al. - 1993
53 Parallel Computational Geometry (context) - Akl, Lyons - 1993
24 Ultra-fast expected time parallel algorithms - MacKenzie, Stout - 1991
22 the average number of maxima in a set of vectors and applica.. (context) - Bentley, Kung et al. - 1978
6 Constant-time geometry on PRAMs (context) - Stout - 1988
5 Zufllige konvexe Polygone in einem Ringgebiet (context) - Rnyi, Sulanke - 1968
5 Improved parallel bucketing algorithms for proximity problem.. (context) - Hagerup, Katajainen - 1993
5 ber die konvexe Hlle von n zufllig gerwhten Punkten (context) - Rnyi, Sulanke - 1963
5 Sur l'envelope convexe des nauges des poits alatoires dans R (context) - Raynaud - 1972
4 The complexity of an axial view of a parallelepipedic scene:.. (context) - Mathieu-Kenyon - 1990
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