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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...
We consider the relative power of concurrentwrite PRAMs when the number of processors (and input variables) is fixed at n, and infinite shared memory is allowed. Several different models (COMMON, ARBITRARY, PRIORITY) have been used for algorithm design in the literature; these models differ in their method of write-conflict resolution. Recent work in separating these models ([FRW1,2,3], [LY]) has...
We present techniques for parallel divide-and-conquer, resulting in improved parallel algorithms for a number of problems. The problems for which we give improved algorithms include intersection detection, trapezoidal decomposition (hence, polygon triangulation), and planar point location (hence, Voronoi diagram construction). We also give efficient parallel algorithms for fractional cascading, 3-dimensional...
We present a parallel randomized algorithm for finding the connected components of an undirected graph. Our algorithm takes T = O(log (n)) time and p = O(m+n/(log(n) processors, where m = number of edges and n = number of vertices. This algorithm improves the results of Cole and Vishkin1, which use O(log (n)??log (log (n))??log (log (log (n)))) time. Our algorithm is Optimal in the sense that the...
We study two parallel scheduling problems and their use in designing parallel algorithms. First, we define a novel scheduling problem; it is solved by repeated, rapid, approximate reschedulings. This leads to a first optimal PRAM algorithm for list ranking, which runs in logarithmic time. Our second scheduling result is for computing prefix sums of logn bit numbers. We give an optimal parallel algorithm...
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.
The time complexity of sorting n elements using p ≥ n processors on Valiant's parallel comparison tree model is considered. The following results are obtained. 1. We show that this time complexity is Θ(logn/log(1+p/n)). This complements the AKS sorting network in settling the wider problem of comparison sort of n elements by p processors, where the problem for p ≤ n was resolved. To prove the lower...
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