E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Comp., 1993.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....assumption that the main memory is capable of holding B elements is made. memory algorithm takes 10 minutes to complete, the internal memory algorithm could use more than 150 hours, or equivalently, about 6 days I O efficient graph algorithms have been considered by a number of authors [10, 11, 17, 33, 25, 20, 31, 7, 6, 30, 22, 26]. If V is the number of vertices and E the number of edges in a graph, the best known algorithms for depth first search, depending on the exact relationship between V and E, use O( V ) 17] or O [25, 16] I Os. For breadth first search an O(V sort(E) algorithm has been developed for ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Computation, 1993.

....V M Delta sort(E) Delta [13] O (sort(E) Delta log B scan(E) Delta log V ) 23] SSSP O Gamma V E B Delta log 2 V B Delta [23] Table 1: Best known upper bounds for basic graph theoretic problems. I O efficient graph algorithms have been considered by a number of authors [5, 6, 13, 29, 23, 17, 27, 2, 1, 26, 20, 25, 11]. Table 1 reviews the best known algorithms for basic graph theoretic problems on general undirected graphs. For directed graphs the best known algorithm for breadth first search (BFS) and depth first search (DFS) use O Gamma (V E B ) Delta log V B sort(E) Delta I Os [11] Lower ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. LNCS, 762:416--425, 1993.

....external priority queue. Using the buffer tree technique on a tournament tree, Kumar and Schwabe [107] developed a priority queue supporting update operations in O( 1 B log N B ) I Os. They also showed how to use their structure in several efficient external graph algorithms (see e. g [2, 7, 18, 22, 27, 46, 59, 81, 97, 107, 110, 111, 116, 118, 122, 142, 156] for other results on external graph algorithms and data structures) Note that if the priority of an element is known, an update operation can be performed in O( 1 B log M=B N B ) I Os on a buffer tree using a delete and an insert operation. 4 3 sided planar range searching In internal ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Computation, LNCS 762, pages 416--425, 1993.

....set of vertices fits in main memory. Related work is done in [75, 76] In [97] work on graph traversal in external memory is done, which primarily addresses the problem of storing graphs and not the problem of performing computations on them. Related work on storing trees is done in [66, 71] In [58] memory management problems for maintaining connectivity information and paths on graphs are studied, and in [85] linear relaxation problems are studied. Recently, Chiang et al. 40, 42] considered graph problems in the general I O model. They developed efficient algorithms for a large number of ....

....100, 131, 133] More recently researchers have designed externalmemory algorithms for a number of problems in different areas. Most notably I O efficient algorithms have been developed for a large number of computational geometry [15, 67] and graph problems [42] Other related papers are [122] and [58] that address the problem of computing the transitive closure of a graph under some restrictions on the size of the graph, and propose a framework for studying memory management problems for maintaining connectivity information and paths on graphs, respectively. Also worth noticing in this context ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Computation, 1993.

....problem. The area was effectively started in the late eighties by Aggarwal and Vitter [6] and subsequently I O algorithms have been developed for several problem domains, including computational geometry [29, 7, 13, 14, 4, 15, 31, 38, 39, 41, 3, 44, 2, 12, 13, 16, 28, 30, 44] graph algorithms [17, 7, 33, 1, 21, 8, 27, 35, 40], and string processing [25, 26, 11, 20] Also I O performance can often be improved if many disks can efficiently be used in parallel and the use of parallel disks has received a lot of theoretical attention. Recent surveys of theoretical results in the area of I O efficient algorithms can be ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Computation, 1993. BIBLIOGRAPHY 111

....More recently, external memory research has moved towards solving graph and geometric problems. Work on graph problems includes transitive closure computations [28] some graph traversal problems [19] and memory management problems for maintaining connectivity information and paths on graphs [16]. Recently, Chiang et al. 10] present a collection of new techniques for designing and analyzing I O efficient graph algorithms, and apply these techniques to a wide variety of specific problems. For geometric problems, Goodrich et al. 20] study a number of problems in computational geometry and ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Comp., 1993.

.... Gamma sort(E) Delta log log V B E Delta [25] MST O Gamma sort(E) Delta log V M Delta [12] O (sort(E) Delta log B scan(E) Delta log V ) 22] SSSP O Gamma V E B Delta log V B Delta [22] I O efficient graph algorithms have been considered by a number of authors [1, 2, 5, 6, 10, 12, 16, 19, 22, 24 26, 29]. Table 1 reviews the best known algorithms for basic graph theoretic problems on general undirected graphs. For directed graphs the best known algorithm for breadth first search (BFS) and depth first search (DFS) use O Gamma (V scan(E) Delta log V B sort(E) Delta I Os [10] Lower ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. LNCS, 762:416--425, 1993.

....set of vertices fits in main memory. Related work is done in [75, 76] In [97] work on graph traversal in external memory is done, which primarily addresses the problem of storing graphs and not the problem of performing computations on them. Related work on storing trees is done in [66, 71] In [58] memory management problems for maintaining connectivity information and paths on graphs are studied, and in [85] linear relaxation problems are studied. Recently, Chiang et al. 40, 42] considered graph problems in the general I O model. They developed e#cient algorithms for a large number of ....

....100, 131, 133] More recently researchers have designed externalmemory algorithms for a number of problems in di#erent areas. Most notably I O e#cient algorithms have been developed for a large number of computational geometry [15, 67] and graph problems [42] Other related papers are [122] and [58] that address the problem of computing the transitive closure of a graph under some restrictions on the size of the graph, and propose a framework for studying memory management problems for maintaining connectivity information and paths on graphs, respectively. Also worth noticing in this context ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Computation, 1993.

....assumption that the main memory is capable of holding B 2 elements is made. 2 memory algorithm takes 10 minutes to complete, the internal memory algorithm could use more than 150 hours, or equivalently, about 6 days I O efficient graph algorithms have been considered by a number of authors [10, 11, 17, 33, 25, 20, 31, 7, 6, 30, 22, 26]. If V is the number of vertices and E the number of edges in a graph, the best known algorithms for depth first search, depending on the exact relationship between V and E, use O( V M E B V ) 17] or O Gamma (V E B ) log V B sort(E) Delta [25, 16] I Os. For breadth first search ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Computation, 1993.

....graph, whose complete information must be stored in secondary memory for space reasons. That subset of the information must be useful to reduce the quantity of accesses to secondary memory necessary to answer a sequence of queries about the connectivity or the existing paths between pairs of nodes [219]. 5.5.5 2 Satisfiability problem The 2 Satisfiability problem has been studied from both an on line [295] and an experimental [353] point of view. 5.6 Probabilistic analysis of algorithms In [325] a scheduling problem has been considered form a probabilistic point of view providing an accurate ....

E. Feuerstein and A. Marchetti Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Fourth Annual International Symposium on Algorithms and Computation (ISAAC '93), volume 762 of Lecture Notes in Computer Science. Springer-Verlag, December 1993.

....facilitate prefetching for various problems, but without taking blocking issues into account. Also worth noting is recent work [11] on some graph traversal problems; this work primarily addresses the problem of storing graphs, however, not in performing specific computations on them. Related work [9] proposes a framework for studying memory management problems for maintaining connectivity information and paths on graphs. Other than these papers, we do not know of any previous work on I O efficient graph algorithms. 1.3 Our Results. In this paper we give a number of general techniques for ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Comp., 1993.

....[4] More recently, external memory research has moved towards solving graph and geometric problems. Work on graph problems includes transitive closure computations [35] some graph traversal problems [23] and memory management problems for maintaining connectivity information and paths on graphs [19]. Recently, Chiang et al. 12] present a collection of new techniques for designing and analyzing I O efficient graph algorithms, and apply these techniques to a wide variety of specific problems. Concurrent to the work presented in this paper, Arge [3] considers the problem of manipulating ....

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Comp., 1993.

....facilitate prefetching for various problems, but without taking blocking issues into account. Also worth noting is recent work [58] on some graph traversal problems; this work primarily addresses the problem of storing graphs, however, not in performing specific computations on them. Related work [50] proposes a framework for studying memory management problems for maintaining connectivity information and paths on graphs. Other than these papers, we do not know of any previous work on I O efficient graph algorithms. 4.1.3 Our Results in This Chapter We give a number of techniques for solving ....

Esteban Feuerstein and Alberto Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Comp., 1993.

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E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Comp., 1993.

No context found.

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proc. Int. Symp. on Algorithms and Comp., 1993.

No context found.

E. Feuerstein and A. Marchetti-Spaccamela. Memory paging for connectivity and path problems in graphs. In Proceedings of the International Symposium on Algorithms and Computation, pages 416--425, 1993.

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