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Spaceefficient planar convex hull algorithms
 Proc. Latin American Theoretical Informatics
, 2002
"... A spaceefficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. We describe four spaceefficient algorithms for computing the convex hull of a planar point set. ..."
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Cited by 20 (1 self)
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A spaceefficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. We describe four spaceefficient algorithms for computing the convex hull of a planar point set.
Optimal inplace planar convex hull algorithms
 Proceedings of Latin American Theoretical Informatics (LATIN 2002), volume 2286 of Lecture Notes in Computer Science
, 2002
"... An inplace algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. In this paper we describe three inplace algorithms for computing the convex hull of a planar point set. All three algorithms are optima ..."
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Cited by 4 (2 self)
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An inplace algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. In this paper we describe three inplace algorithms for computing the convex hull of a planar point set. All three algorithms are optimal, some more so than others...
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"... Abstract. An inplace algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. In this paper we describe three inplace algorithms for computing the convex hull of a planar point set. All three algorithms a ..."
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Abstract. An inplace algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. In this paper we describe three inplace algorithms for computing the convex hull of a planar point set. All three algorithms are optimal, some more so than others... 1 Introduction Let S = fS[0]; : : : ; S[n \Gamma 1]g be a set of n distinct points in the Euclidean plane. The convex hull of S is the minimal convex region that contains every point of S. From this definition, it follows that the convex hull of S is a convex polygon whose vertices are points of S. For convenience, we say that a point p is &quot;on the convex hull of S &quot; if p is a vertex of the convex hull of S.
SpaceEfficient Planar Convex Hull Algorithms
"... A spaceefficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. We describe four spaceefficient algorithms for computing the convex hull of a planar point set. ..."
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A spaceefficient algorithm is one in which the output is given in the same location as the input and only a small amount of additional memory is used by the algorithm. We describe four spaceefficient algorithms for computing the convex hull of a planar point set.
Generic Algorithm for 0/1Sorting
"... Abstract. In the 0/1sorting problem, given a sequence S of elements drawn from a universe E and a characteristic function f: E → {0, 1}, the task is to rearrange the elements in S so that every element x, for which f(x) = 0, is placed before any element y, for which f(y) = 1. Moreover, this reord ..."
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Abstract. In the 0/1sorting problem, given a sequence S of elements drawn from a universe E and a characteristic function f: E → {0, 1}, the task is to rearrange the elements in S so that every element x, for which f(x) = 0, is placed before any element y, for which f(y) = 1. Moreover, this reordering should be done stably without altering the relative order of elements having the same fvalue, and space efficiently using only O(1) words of extra space. In this paper we present a generic algorithm for solving the 0/1sorting problem which works optimally for many different kinds of sequences and characteristic functions. The model of computation used is a word RAM with a twolevel memory hierarchy consisting of an ideal cache and an arbitrarily large main memory. The performance of our algorithm can be summarized as follows: 1. Let n denote the length of S. The algorithm performs at most O(n) element exchanges, invocations of f, and word operations. 2. Let wf (u) denote the amount of work done when applying f to element u. When the cost of the evaluation of the characteristic function is not uniform, but depends on the element f is applied to, the algorithm uses O �� u∈S wf (u) � work under the assumption that element exchanges involve O(1) work. 3. Let B denote the size of cache blocks measured in elements. The algorithm incurs O (n/B) cache misses in the idealcache model under the tallcache assumption (excluding the cache misses possibly generated by the invocations of f). Interestingly, our algorithm is neither aware of the characteristics of the cache (hardware obliviousness) nor the implementation of f (software obliviousness). 1.
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"... Spaceefficient algorithms for computing the convex hull of a simple polygonal line in linear time 1,2,3 ..."
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Spaceefficient algorithms for computing the convex hull of a simple polygonal line in linear time 1,2,3