Results 81 to 90 of about 98,329 (103)
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On Separating the EREW and CREW PRAM Models,
1988Prabhakar Ragde, Joseph Naor, Eli Gafni
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Retrieval of scattered information by EREW, CREW, and CRCW PRAMs
Computational Complexity, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Faith E. Fich +4 more
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SIAM Journal on Computing, 1989
Summary: 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. The characterization is given in terms of a new complexity measure of boolean functions: the ``block sensitivity'', a generalization of the well-known ``critical sensitivity'' measure.
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Summary: 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. The characterization is given in terms of a new complexity measure of boolean functions: the ``block sensitivity'', a generalization of the well-known ``critical sensitivity'' measure.
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Optimal CREW-PRAM algorithms for direct dominance problems
1993We present optimal parallel solutions to direct dominance problems for planar point sets. Our algorithms are deterministic and designed to run on the concurrent read exclusive write parallel random-access machine (CREW PRAM). In particular, we provide algorithms for counting the number of points that are directly dominated by each point of a planar ...
Amitava Datta +2 more
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A High Performance Parallel IP Lookup Technique Based on Multiprocessor Organization and CREW PRAM
2008 Second Asia International Conference on Modelling & Simulation (AMS), 2008The IP Lookup Process is a key bottleneck in routing due to the increase in routing table size, increasing traffic and migration to IPv6 addresses. The IP routing lookup involves computation of the Longest Prefix Matching for which existing solutions, such as BSD Radix Tries, scale poorly when traffic in the router increases or when employed for IPv6 ...
Mahmoud Hasanloo +2 more
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Journal of Heuristics, 2019
Non-dominated sorting is a crucial component of Pareto-based multi- and many-objective evolutionary algorithms. As the number of objectives increases, the execution time of a multi-objective evolutionary algorithm increases, too. Since multi-objective evolutionary algorithms normally have a low data dependency, research-ers have increasingly adopted ...
Sumit Mishra, Carlos A. Coello Coello
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Non-dominated sorting is a crucial component of Pareto-based multi- and many-objective evolutionary algorithms. As the number of objectives increases, the execution time of a multi-objective evolutionary algorithm increases, too. Since multi-objective evolutionary algorithms normally have a low data dependency, research-ers have increasingly adopted ...
Sumit Mishra, Carlos A. Coello Coello
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Parallel algorithms for some dominance problems based on a CREW PRAM
1991Two parallel geometric algorithms based on the idea of point domination are presented. The first algorithm solves the d-dimensional isothetic rectangles intersection counting problem of input size N/2d, where d > 1 and N is a multiple of 2d, in O(logd−1N) time and O(N) space.
Ip-Wang Chan, Donald K. Friesen
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2019 IEEE Congress on Evolutionary Computation (CEC), 2019
In the current paper we focus on parallelization of non-dominated sorting which is an essential step in Pareto-based multi-objective evolutionary algorithms. The parallel approaches can help to reduce the overall execution time of multi-objective evolutionary algorithms.
Sumit Mishra, Carlos A. Coello Coello
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In the current paper we focus on parallelization of non-dominated sorting which is an essential step in Pareto-based multi-objective evolutionary algorithms. The parallel approaches can help to reduce the overall execution time of multi-objective evolutionary algorithms.
Sumit Mishra, Carlos A. Coello Coello
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Connected components in O(lg/sup 3/2 mod V/ mod ) parallel time for the CREW PRAM
[1991] Proceedings 32nd Annual Symposium of Foundations of Computer Science, 2002Computing the connected components of an undirected graph G=(V, E) on mod V mod =n vertices and mod E mod =m edges is addressed. An efficient and simple algorithm that runs in O(lg/sup 3/2/ n) time using n+m CREW processors is presented. >
D.B. Johnson, P. Metaxas
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Time Complexity of Boolean Functions on CREW PRAM
This paper is concerned with parallel random access machines (PRAMS), where each processor can read from and write into a common random access memory.
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