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This paper, which is work in progress, describes a new cluster based approach for Image restoration applications. The existing and the past solutions to Image restoration problem has always concentrated on single uniprocessor machines. This has become a major hurdle for large images as well as motion picture which requires large portions to be rendered at a faster rate. We propose a cluster based...
A new parallel algorithm for the maximal independent set problem (MIS) is constructed. It runs in O(log4 n) time when implemented on a linear number of EREW-processors. This is the first deterministic algorithm for MIS whose running time is polylogarithmic and whose processor-time product is optimal up to a polylogarithmic factor.
The following three problems concerning random graphs can be solved in (log n)O(1) expected time using linearly many processors: (1) finding the lexicographically first maximal independent set, (2) coloring the vertices using a number of colors that is almost surely within twice the chromatic number, and (3) finding a Hamiltonian circuit.
In practice, the average time of (deterministic or randomized) sorting algorithms seems to be more relevant than the worst case time of deterministic algorithms. Still, the many known complexity bounds for parallel comparison sorting include no nontrivial lower bounds for the average time required to sort by comparisons n elements with p processors (via deterministic or randomized algorithms). We...
This paper addresses the problem of how to adapt an algorithm designed for fixed topology networks to produce the intended results, when run in a network whose topology changes dynamically, in spite of encountering topological changes during its execution. We present a simple and unified procedure, called a reset procedure, which, when combined with the static algorithm, achieves this adaptation....
We give a parallel implementation of merge sort on a CREW PRAM that uses n processors and O(logn) time; the constant in the running time is small. We also give a more complex version of the algorithm for the EREW PRAM; it also uses n processors and O(logn) time. The constant in the running time is still moderate, though not as small.
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