A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In 23rd Symp. on Mathematical Foundations of Computer Science, volume 1450 of LNCS, pages 722--731. Springer, 1998.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....(for excellent survey see [CG99] which are based on relaxation of graph s edges, are inherently sequential and their parallel versions are known only for special settings of the problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [MS00, RV92, CMMS98] together with studies concerning good decompositions [HTB97] For special cases of graphs, like planar digraphs [TZ96, DKZ94] graphs with separator decomposition [Coh96] or graphs with small treewidth [CZ95] more efficient algorithms are known. Yet none of these algorithms are applicable on ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, Lecture Notes in Computer Science, volume 1450, pages 722--731. Springer-Verlag, 1998.

....(for excellent survey see [CG99] which are based on relaxation of graph s edges, are inherently sequential and their parallel versions are known only for special settings of the problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [MS00, RV92, CMMS98] together with studies concerning good decompositions [HTB97] For special cases of graphs, like planar digraphs [TZ96, DKZ94] graphs with separator decomposition [Coh96] or graphs with small treewidth [CZ95] more ef Thetacient algorithms are known. Yet none of these algorithms are applicable on ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, Lecture Notes in Computer Science, volume 1450, pages 722#731. Springer-Verlag, 1998.

....technique) Our distributed algorithm is based on the relaxation of graph s edges [CLR90] Distributed relaxation based algorithms are known only for special settings of single source shortest paths problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [CMMS98,MS00,RV92]. For special cases of graphs, like planar digraphs [TZ96,KPSZ94] graphs with separator decomposition [Coh96] or graphs with small tree width [CZ95] more efficient algorithms are known. Yet none of these algorithms is applicable to general digraphs with negative length cycles. The most notable ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, Lecture Notes in Computer Science, volume 1450, pages 722--731. Springer-Verlag, 1998.

....technique) Our distributed algorithm is based on the relaxation of graph s edges [CLR90] Distributed relaxation based algorithms are known only for special settings of single source shortest paths problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [CMMS98,MS00,RV92]. For special cases of graphs, like planar digraphs [TZ96,KPSZ94] graphs with separator decomposition [Coh96] or graphs with small tree width [CZ95] more ef Thetacient algorithms are known. Yet none of these algorithms is applicable to general digraphs with negative length cycles. The most ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, Lecture Notes in Computer Science, volume 1450, pages 722#731. Springer-Verlag, 1998.

....Other algorithms (for excellent survey see [8] which are based on relaxation of graph s edges, are inherently sequential and their parallel versions are known only for special settings of the problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [19, 20, 12]. For special cases of graphs, like planar digraphs [25, 13] graphs with separator decomposition [10] or graphs with small tree width [7] more ecient algorithms are known. Yet none of these algorithms is applicable on directed graphs with potential negative cycles. We present a scalable ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. MFCS 1998, volume 1450 of LNCS, pages 722{

....Our distributed algorithm is therefore based on the relaxation of graph s edges [CLR90] Distributed relaxation based algorithms are known only for special settings of single source shortest paths problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [CMMS98,MS00,RV92]. For special cases of graphs, like planar digraphs [TZ96,KPSZ94] graphs with separator decomposition [Coh96] or graphs with small tree width [CZ95] more ecient algorithms are known. Yet none of these algorithms is applicable to general digraphs with potential negative length cycle. The most ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, Lecture Notes in Computer Science, volume 1450, pages 722-731. Springer-Verlag, 1998.

....Other algorithms (for excellent survey see [8] which are based on relaxation of graph s edges, are inherently sequential and their parallel versions are known only for special settings of the problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [19, 20, 12]. For special cases of graphs, like planar digraphs [25, 13] graphs with separator decomposition [10] or graphs with small tree width [7] more ecient algorithms are known. Yet none of these algorithms is applicable on directed graphs with potential negative cycles. We present a scalable ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. MFCS 1998, volume 1450 of LNCS, pages 722{

....algorithms (for excellent survey see [CG99] which are based on relaxation of graph s edges, are inherently sequential and their parallel version is known only for special settings of problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [MS00, RV92, CMMS98] together with studies concerning good decomposition [HTB97] For special cases of graphs, like planar digraphs [TZ96, DKZ94] graphs with separator decomposition [Coh96] or graphs with small tree width [CZ95] more efficient algorithms are known. Yet none of these algorithms are applicable on ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, Lecture Notes in Computer Science, volume 1450, pages 722--731. Springer-Verlag, 1998.

....algorithms (for excellent survey see [CG99] which are based on relaxation of graph s edges, are inherently sequential and their parallel version is known only for special settings of problem. For general digraphs with non negative edge lengths parallel algorithms are presented in [MS00, RV92, CMMS98] together with studies concerning good decomposition [HTB97] For special cases of graphs, like planar digraphs [TZ96, DKZ94] graphs with separator decomposition [Coh96] or graphs with small tree width [CZ95] more ef Thetacient algorithms are known. Yet none of these algorithms are applicable ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, Lecture Notes in Computer Science, volume 1450, pages 722#731. Springer-Verlag, 1998.

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A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In 23rd Symp. on Mathematical Foundations of Computer Science, volume 1450 of LNCS, pages 722--731. Springer, 1998.

....Shi and Spencer [28] Most of these algorithms can be modified to run on the weakest PRAM model without concurrent read write capability. Parallel shortest path problems on random graphs [6] where each of the n 2 possible edges is present with a certain probability have been studied intensively [8, 10, 15, 17, 25, 26, 27]. Under the assumption of independent random edge weights uniformly distributed in the interval [0; 1] the fastest work efficient parallel SSSP algorithm for random graphs [25, 26] requires O(log 2 n) time and linear work on average; additionally, O(d (L 1) log n log 2 n) time and O(n ....

.... obtain fast SSSP algorithms with linear average case work, one might also try to parallelize Goldberg s new sequential label setting algorithm [16] However, in its current form, the criterion used to detect nodes that can be scanned in arbitrary order is at most as efficient as the INapproach in [10]. It can be shown that there are graph classes with random edge weights, maximum constant node degree and maximum shortest path weight L = O(log n) where this criterion requires p n= log n) phases. In contrast, our new approach runs in O(log 3 n) time and linear work for these graphs. Still, ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In 23rd Symp. on Mathematical Foundations of Computer Science, volume 1450 of LNCS, pages 722--731. Springer, 1998.

....was found for jRj = Theta(jQj 3=4 ) While repeatedly doubling the number of nodes, the average number of phases (for different starting points) only increased by a factor of about 1:5; for n = 157; 457 the simulation needed 1; 178 phases, the number of reinserts was bounded by 0:2n. In [10, 9] we develop an algorithm which needs no reexpansions for arbitrary edge weights. However, even for random edge weights it needs Theta Gamma n 1=3 Delta phases even for random edge weights. Acknowledgements We would like to thank in particular Kurt Mehlhorn and Volker Priebe for many ....

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In 23rd Symposium on Mathematical Foundations of Computer Science, LNCS, Brno, Czech Republic, 1998. Springer.

No context found.

A. Crauser, K. Mehlhorn, U. Meyer, and P. Sanders. A parallelization of Dijkstra's shortest path algorithm. In Proc. 23rd MFCS'98, volume 1450 of Lecture Notes in Computer Science, pages 722--731. SpringerVerlag, 1998.

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A. Crauser, K. Mehlhorn, U. Meyer, P. Sanders. A parallelization of Dijkstra's shortest path algorithm. Proc. 23rd Intl. Symp. Math. Found. of Comp. Sci. (MFCS 1998), LNCS 1450, pp. 722-731.

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