Results 1 to 10 of about 98,530 (56)
On separating the EREW and CREW PRAM models
Theoretical Computer Science, 1989 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Eli Gafni +2 more
exaly +3 more sources
Optimal Parallel Two Dimensional Text Searching on a CREW PRAM
Information and Computation, 1998 In this paper, the efficient parallel algorithm for two dimensional pattern matching over a general alphabet is presented. The text processing phase is optimal in that its work is linear and its running time is optimal; i.e., it matches the lower bound \(O(\log m)\) for CREW PRAMs, where \(m\) is the length of the longest dimension of the pattern ...
Amihood Amir +2 more
exaly +3 more sources
Connected Components inO(log3/2n) Parallel Time for the CREW PRAM
Journal of Computer and System Sciences, 1997 Finding the connected components of an undirected graphG=(V, E) onn=|V| vertices andm=|E| edges is a fundamental computational problem. The best known parallel algorithm for the CREW PRAM model runs inO(log2n) time usingn2/log2nprocessors.
Donald B. Johnson, P. Metaxas
exaly +4 more sources
SIAM Journal on Computing, 1993 The universality of the Parallel Random-Access Machines is usually defined by simulating universal Turing machines or boolean networks. These definitions are well-suited if we are interested in evaluating the complexity of algorithms but it is not as good if we want to deal with computability.
Bruno Martin
semanticscholar +5 more sources
Time Lower Bounds For CREW-PRAM Computation Of Monotone Functions [PDF]
International Colloquium on Automata, Languages and Programming, 1989 It is shown that the time to compute a monotone boolean function depending upon n variables on a CREW-PRAM satisfies the lower bound T=Θ(logl+(log n)/l), where l is the size of the largest prime implicant. It is also shown that the bound is existentially tight by constructing a family of monotone functions that can be computed in T=O(log l+(log n)/l ...
G. Bilardi, A. Moitra
semanticscholar +2 more sources
SIAM Journal on Computing, 1989 This paper gives a full characterization of the time needed to compute a Boolean function on a CREW PRAM with an unlimited number of processors.
N. Nisan
semanticscholar +2 more sources
A cost optimal parallel algorithm for computing force field in N-body simulations on a CREW PRAM
Theoretical Computer Science, 2001 We consider the following force field computation problem: given a cluster of n particles in three-dimensional space, compute the force exerted on each particle by the other particles.
G. Xue
semanticscholar +3 more sources
Application of Fuzzy Optimization to the Orienteering Problem
Advances in Fuzzy Systems, 2015 This paper deals with the orienteering problem (OP) which is a combination of two well-known problems (i.e., travelling salesman problem and the knapsack problem).
Madhushi Verma, K. K. Shukla
doaj +1 more source
Separating the Power of EREW and CREW PRAMs with Small Communication Width
Information and Computation, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Paul Beame +2 more
openaire +2 more sources
Parallelization of Ant System for GPU under the PRAM Model
Computing and informatics, 2018 . We study the parallelized ant system algorithm solving the traveling salesman problem on n cities. First, following the series of recent results for the graphics processing unit, we show that they translate to the PRAM (parallel random access machine ...
A. Brodnik, Marko Grgurovic
semanticscholar +1 more source