Results 1  10
of
12
Parallel Construction of Quadtrees and Quality Triangulations
, 1999
"... We describe e#cient PRAM algorithms for constructing unbalanced quadtrees, balanced quadtrees, and quadtreebased finite element meshes. Our algorithms take time O(log n) for point set input and O(log n log k) time for planar straightline graphs, using O(n + k/ log n) processors, where n measure ..."
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Cited by 71 (8 self)
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We describe e#cient PRAM algorithms for constructing unbalanced quadtrees, balanced quadtrees, and quadtreebased finite element meshes. Our algorithms take time O(log n) for point set input and O(log n log k) time for planar straightline graphs, using O(n + k/ log n) processors, where n measures input size and k output size. 1. Introduction A crucial preprocessing step for the finite element method is mesh generation, and the most general and versatile type of twodimensional mesh is an unstructured triangular mesh. Such a mesh is simply a triangulation of the input domain (e.g., a polygon), along with some extra vertices, called Steiner points. Not all triangulations, however, serve equally well; numerical and discretization error depend on the quality of the triangulation, meaning the shapes and sizes of triangles. A typical quality guarantee gives a lower bound on the minimum angle in the triangulation. Baker et al. 1 first proved the existence of quality triangulations fo...
Parallel Algorithmic Techniques for Combinatorial Computation
 Ann. Rev. Comput. Sci
, 1988
"... this paper and supplied many helpful comments. This research was supported in part by NSF grants DCR8511713, CCR8605353, and CCR8814977, and by DARPA contract N0003984C0165. ..."
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Cited by 35 (3 self)
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this paper and supplied many helpful comments. This research was supported in part by NSF grants DCR8511713, CCR8605353, and CCR8814977, and by DARPA contract N0003984C0165.
Towards overcoming the transitiveclosure bottleneck: efficient parallel algorithms for planar digraphs
 J. Comput. System Sci
, 1993
"... Abstract. Currently, there is a significant gap between the best sequential and parallel complexities of many fundamental problems related to digraph reachability. This complexity bottleneck essentially reflects a seemingly unavoidable reliance on transitive closure techniques in parallel algorithms ..."
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Cited by 11 (1 self)
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Abstract. Currently, there is a significant gap between the best sequential and parallel complexities of many fundamental problems related to digraph reachability. This complexity bottleneck essentially reflects a seemingly unavoidable reliance on transitive closure techniques in parallel algorithms for digraph reachability. To pinpoint the nature of the bottleneck, we de* velop a collection of polylogtime reductions among reachability problems. These reductions use only linear processors and work for general graphs. Furthermore, for planar digraphs, we give polylogtime algorithms for the following problems: (1) directed ear decomposition, (2) topological ordering, (3) digraph reachability, (4) descendent counting, and (5) depthfirst search. These algorithms use only linear processors and therefore reduce the complexity to within a polylog factor of optimal.
An Optimal Parallel Algorithm for Computing a NearOptimal Order of Matrix Multiplications
 LNCS # 621
, 1992
"... This paper considers the computation of matrix chain products of the form M1 \Theta M2 \Theta \Delta \Delta \Delta \Theta Mn\Gamma1 . The order in which the matrices are multiplied affects the number of operations. The best sequential algorithm for computing an optimal order of matrix multiplicatio ..."
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Cited by 6 (2 self)
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This paper considers the computation of matrix chain products of the form M1 \Theta M2 \Theta \Delta \Delta \Delta \Theta Mn\Gamma1 . The order in which the matrices are multiplied affects the number of operations. The best sequential algorithm for computing an optimal order of matrix multiplication runs in O(n log n) time while the best known parallel NC algorithm runs in O(log 2 n) time using n 6 = log 6 n processors. This paper presents the first approximating optimal parallel algorithm for this problem and for the problem of finding a nearoptimal triangulation of a convex polygon. The algorithm runs in O(log n) time using n= log n processors on a CREW PRAM, and in O(log log n) time using n= log log n processors on a weak CRCW PRAM. It produces an order of matrix multiplications and a partition of polygon which differ from the optimal ones at most 0.1547 times. 1 Introduction The problem of computing an optimal order of matrix multiplication (the matrix chain product proble...
A.Lingas. On the maximum qdependent set problem
 In International Conference for Young Computer Scientists, ICYCS’91
, 1991
"... ..."
An Efficient Parallel Algorithm for Shortest Paths in Planar Layered Digraphs
, 1993
"... Computing shortest paths in a directed graph has received considerable attention in the sequential RAM model of computation. However, developing a polylogtime parallel algorithm that is close to the sequential optimal in terms of the total work done remains an elusive goal. We present a first step ..."
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Cited by 2 (0 self)
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Computing shortest paths in a directed graph has received considerable attention in the sequential RAM model of computation. However, developing a polylogtime parallel algorithm that is close to the sequential optimal in terms of the total work done remains an elusive goal. We present a first step in this direction by giving efficient parallel algorithms for shortest paths in planar layered digraphs. We show that these graphs admit special kinds of separators called oneway separators which allow the paths in the graph to cross it only once. We use these separators to give divide and conquer solutions to the problem of finding the shortest paths between any two vertices. We first give a simple algorithm that works in the CREW model and computes the shortest path between any two vertices in an nnode planar layered digraph in time O(log³ n) using n/log n processors. A CRCW version of this algorithm runs in time O(log² n log log n) and uses n/log log n processors. We then use re...
On Parallel Algorithms for Combinatorial Problems
, 1993
"... Graphs are the most widely used of all mathematical structures. There is uncountable number of interesting computational problems defined in terms of graphs. A graph can be seen as a collection of vertices (V ), and a collection of edges (E) joining all or some of the vertices. One is very often int ..."
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Cited by 1 (0 self)
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Graphs are the most widely used of all mathematical structures. There is uncountable number of interesting computational problems defined in terms of graphs. A graph can be seen as a collection of vertices (V ), and a collection of edges (E) joining all or some of the vertices. One is very often interested in finding subsets, either from the set V of vertices or from the set E of edges, which possess some predefined property. A subset S of vertices or edges in a graph G is said to be maximum with respect to a property if, among all the subsets of G having this property, S is one having the largest cardinality. Set S is said to be maximal with respect to a property, if the set has the property, and it is not a proper subset of another set having the property. A subset of vertices in a graph, is said to be independent if no two of them are adjacent. The problems of finding maximum and maximal independent sets in a graph are well known problems. One of the more natural generalizations of...
A DivideandConquer Approach to Shortest Paths in Planar Layered Digraphs
, 1992
"... Computing shortest paths in a directed graph has received considerable attention in the sequential RAM model of computation. However, developing a polylogtime parallel algorithm that is close to the sequential optimal in terms of the total work done remains an elusive goal. We present a first step ..."
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Computing shortest paths in a directed graph has received considerable attention in the sequential RAM model of computation. However, developing a polylogtime parallel algorithm that is close to the sequential optimal in terms of the total work done remains an elusive goal. We present a first step in this direction by showing that for an nnode planar layered digraph with nonnegative edgeweights the shortest path between any two vertices can be computed in O(log³ n) time with n processors in a CREW PRAM. A CRCW version of our algorithm runs in time O(log² n log log n) and uses n log n/log log n processors. Our results make use of the existence of special kinds of separators in planar layered digraphs, called oneway separators, to implement a divide and conquer solution.