Matching run-length coded strings (RLCSs) is very important in the field of pattern recognition. This paper considers the design of vectorized matching algorithms that operate directly on RLCSs. We first modify the al...
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Matching run-length coded strings (RLCSs) is very important in the field of pattern recognition. This paper considers the design of vectorized matching algorithms that operate directly on RLCSs. We first modify the algorithm of Karp and Rabin (1987) to design a linear-time randomized matching algorithm for RLCSs. Following this algorithm, two new and fast vectorized algorithms are presented. The first one is off-line and the second one is on-line. Some experiments are carried out on a GRAY X-MP EA/116se vector supercomputer to demonstrate the good performance of our vectorized algorithms. (C) 1997 Elsevier Science B.V.
Recently Karger proposed a new randomized algorithm for finding a minimum cut of an n-vertex graph (weighted or unweighted) with probability Omega(n(-2)). In this paper we present a new probabilistic analysis of Karge...
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Recently Karger proposed a new randomized algorithm for finding a minimum cut of an n-vertex graph (weighted or unweighted) with probability Omega(n(-2)). In this paper we present a new probabilistic analysis of Karger's randomized algorithm for a few classes of unweighted graphs. For random graphs whose edges are selected with a given probability p, (log n)/n less than or equal to p less than or equal to 1, we show that the expectation of success probability of the algorithm is Omega(p/n). We also investigate a class of graphs with special structure that consists of two n-cliques and gamma(n - 1) edges between the two cliques, Here gamma is a parameter satisfying 0 < gamma < 1 that makes these gamma(n - 1) edges a unique minimum cut. We show that the algorithm finds the unique minimum cut with probability n(gamma/n(gamma)). (C) 1997 Elsevier Science B.V.
Recent developments in database technology, such as deductive database systems, have given rise to the demand for new, cost-effective optimization techniques for join expressions. In this paper many different algorith...
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Recent developments in database technology, such as deductive database systems, have given rise to the demand for new, cost-effective optimization techniques for join expressions. In this paper many different algorithms that compute approximate solutions for optimizing join orders are studied since traditional dynamic programming techniques are not appropriate for complex problems. Two possible solution spaces, the space of left-deep and bushy processing trees, are evaluated from a statistical point of view. The result is that the common limitation to left-deep processing trees is only advisable for certain join graph types. Basically, optimizers from three classes are analysed: heuristic, randomized and genetic algorithms. Each one is extensively scrutinized with respect to its working principle and its fitness for the desired application. It turns out that randomized and genetic algorithms are well suited for optimizing join expressions. They generate solutions of high quality within a reasonable running time. The benefits of heuristic optimizers, namely the short running time, are often outweighed by merely moderate optimization performance.
In this paper, we consider the problem of interprocessor communication on parallel computers that have optical communication networks. We consider the completely connected optical-communication parallel computer (OCPC...
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In this paper, we consider the problem of interprocessor communication on parallel computers that have optical communication networks. We consider the completely connected optical-communication parallel computer (OCPC), which has a completely connected optical network, and also the mesh-of-optical-buses parallel computer (MOB-PC), which has a mesh of optical buses as its communication network. The particular communication problem that we study is that of realizing an h-relation. In this problem, each processor has at most h messages to send and at most h messages to receive. It is clear that any 1-relation can be realized in one communication step on an OCPC. However, the best previously known p-processor OCPC algorithm for realizing an arbitrary h-relation for h > 1 requires -(h + log p) expected communication steps. (This algorithm is due to Valiant and is based on earlier work of Anderson and Miller.) Valiant's algorithm is optimal only for h = Omega(log p), and it is an open question of Gereb-Graus and Tsantilas whether there is a faster algorithm for h = Omega(log p). In this paper, we answer this question in the affirmative and we extend the range of optimality by considering the case in which h less than or equal to log p. In particular, we present a -(h + log log p)-communication-step randomized algorithm that realizes an arbitrary h-relation on a p-processor OCPC. We show that if h less than or equal to log p, then the failure probability can be made as small as p(-alpha) for any positive constant alpha. We use the OCPC algorithm as a subroutine in a -(h + log log p)communication-step randomized algorithm that realizes an arbitrary h-relation on a p x p-processor MOB-PC. Once again, we show that if h less than or equal to log p, then the failure probability can be made as small as p(-alpha) for any positive constant alpha.
We give an O (log(4) n)-time O(n(2))-processor CRCW PRAM algorithm to find a hamiltonian cycle in a strong semicomplete bipartite digraph, B, provided that a factor of B (i.e., a collection of vertex disjoint cycles c...
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We give an O (log(4) n)-time O(n(2))-processor CRCW PRAM algorithm to find a hamiltonian cycle in a strong semicomplete bipartite digraph, B, provided that a factor of B (i.e., a collection of vertex disjoint cycles covering the vertex set of B)is computed in a preprocessing step. The factor is found (if it exists) using a bipartite matching algorithm, hence placing the whole algorithm in the class Random-NC. We show that any parallel algorithm which can check the existence of a hamiltonian cycle in a strong semicomplete bipartite digraph in time O(r(n)) using p(n) processors can be used to check the existence of a perfect matching in a bipartite graph in time O(r(n) + n(2)/p(n)) using p(n) processors. Hence, our problem belongs to the class NC if and only if perfect matching in bipartite graphs belongs to NC. We also consider the problem of finding a hamiltonian path in a semicomplete bipartite digraph.
In this paper, we consider the problem of selection on coarse-grained distributed memory parallel computers. We discuss several deterministic and randomized algorithms for parallel selection. We also consider several ...
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In this paper, we consider the problem of selection on coarse-grained distributed memory parallel computers. We discuss several deterministic and randomized algorithms for parallel selection. We also consider several algorithms for load balancing needed to keep a balanced distribution of data across processors during the execution of the selection algorithms. We have carried out detailed implementations of all the algorithms discussed on the CM-5 and report on the experimental results. The results clearly demonstrate the role of randomization in reducing communication overhead.
COUNTER algorithms, a family of randomized algorithms for the list update problem, were introduced by Reingold, Westbrook, and Sleator (1994). They showed that for any epsilon > 0, there exist COUNTER algorithms th...
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COUNTER algorithms, a family of randomized algorithms for the list update problem, were introduced by Reingold, Westbrook, and Sleator (1994). They showed that for any epsilon > 0, there exist COUNTER algorithms that achieve a competitive ratio of root 3 + epsilon. In this paper we use a mixture of two COUNTER algorithms to achieve a competitiveness of 12/7, which is less than root 3. Furthermore, we demonstrate that it is impossible to prove a competitive ratio smaller than 12/7 for any mixture of COUNTER algorithms using the type of potential function argument that has been used so far. We also provide new lower bounds for the competitiveness of COUNTER algorithms in the standard cost model, including a 1.625 lower bound for the variant BIT and a matching 12/7 lower bound for our algorithm. (C) 1997 Elsevier Science B.V.
We present a family of randomized algorithms that enjoys a wide range of time-space trade-offs in deciding undirected S-T-connectivity. Our trade-offs cover the whole range between breadth first search and the random ...
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We present a family of randomized algorithms that enjoys a wide range of time-space trade-offs in deciding undirected S-T-connectivity. Our trade-offs cover the whole range between breadth first search and the random walk procedure of Aleliunas at al., and achieve a time-space product of (O) over tilde(mn) (where n is the number of vertices in the graph, m is the number of edges, and (O) over tilde notation is used in order to suppress logarithmic terms). Moreover, we obtain improved time-space trade-offs of (O) over tilde(n(2)) for regular graphs. A convenient and informative way of expressing our trade-offs, that implies the trade-offs stated above, is as (O) over tilde((Sigma(i=1)(n) d(i))(Sigma(i=1)(n) 1/d(i))), where d(i) is the degree of vertex i in the input graph. In constructing our algorithms and analysing them, we build upon earlier work of Broder et al. (who achieved a time-space trade-off of (O) over tilde(m(2))), Barnes and Feige (who achieved a time-space trade-off of (O) over tilde(m(3/2)n(1/2))), and Aldous. In passing, we also improve previous results regarding the rate at which a random walk discovers new vertices in a graph. (C) 1997 Academic Press.
This note combines the lazy randomized incremental construction scheme with the technique of ''connectivity acceleration'' to obtain an O(n(log(*) n)(2)) time randomized algorithm to compute a single f...
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This note combines the lazy randomized incremental construction scheme with the technique of ''connectivity acceleration'' to obtain an O(n(log(*) n)(2)) time randomized algorithm to compute a single face in the overlay of two simple polygons in the plane. (C) 1997 Elsevier Science B.V.
We present efficient algorithms for designing optimal collective communication primitives for cluster-based heterogeneous computing across Asynchronous Transfer Mode (ATM) networks. The virtual path (VP) concept is kn...
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We present efficient algorithms for designing optimal collective communication primitives for cluster-based heterogeneous computing across Asynchronous Transfer Mode (ATM) networks. The virtual path (VP) concept is known to be a powerful transport mechanism for ATM networks, In many parallel processing applications, the potential communication pattern is known in advance, We then seek to find an optimal set of virtual paths to realize the communication pattern, such that the communication overhead of the parallel processing application is minimized, and at the same time, the extent to which the other data traffic in the network is affected by the data traffic generated by the parallel processing application is also minimized, We consider the following four collective communication problems that occur frequently in parallel computation: one-to-all broadcast, all-to-all broadcast, one-to-all scatter, and all-to-all scatter, We formulate these problems as combinatorial optimization problems of finding a system of virtual path routes in networks, with the objectives of minimizing the path length, the link congestion, and the node copy load, We consider two cases of data sources, namely homogeneous and heterogeneous, For the case of homogeneous sources, we present polynomial-time algorithms for the problems of one-to-all broadcast, all-to-all broadcast, and one-to-all scatter, by converting these problems to the maximum-flow problems, For the case of heterogeneous sources, we show that the problems of all-to-all broadcast, one-to-all scatter, and all-to-all scatter are all NP-complete, Finally, we present novel randomized algorithms for these problems, and show that with high probability these algorithms yield good solutions in the sense that the objective functions yield values close to the optimums. The randomized algorithms can also be used to design near-optimum multicast communication primitives, These randomized algorithms make use of linear programming and are eas
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