S. Kumar, S. M. Goddard, and J. F. Prins. Connectedcomponents algorithms for mesh-connected parallel computers. In 3rd DIMACS Implementation Challenge Workshop, October 1994.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... 1 1 Introduction and Motivations Although a significant amount of parallel machines have been built and a lot of parallel algorithms concerning graphs have been written, only a few implementations of those algorithms have been carried out on existing parallel platforms [HRD, KLCY94, KGP94, LKC95, RM94, HRD95] Being interested in graph problems, not only we would like to design parallel graph algorithms to process very large data as fast as possible, but also we would like that the implementations of these algorithms on parallel machines be as efficient as in theory, and this for ....

S. Kumar, S. M. Goddard, and J. F. Prins. Connectedcomponents algorithms for mesh-connected parallel computers. In 3rd DIMACS Implementation Challenge Workshop, October 1994.

....we implemented several different parallel algorithms for the connected components problem, including one randomized algorithm, and tested our code with respect to various fine tuning techniques. Related work on implementing combinatorial algorithms on massively parallel machines can be found in [1, 3, 4, 8, 9, 10, 11, 15, 16, 18, 19, 30, 38, 39, 41, 48]. Also there has been work reported on implementing combinatorial algorithms on a vector super computer [16, 45, 49] and on a distributed memory machine [29] The rest of the paper is organized as follows. Section 2 describes the algorithms implemented which includes an algorithm that we devised ....

....and Vishkin [50] is reported. After fine tuning, they obtain a speedup of 20 using a 32 processor CM 5 on grid graphs and obtain virtually no speedup on sparse random graphs. The performance of our massively parallel implementationseems to be more adaptable to different classes of graphs. In [30], a mesh implementation of hooking and pointer jumping type algorithms is reported on a MasPar MP 1 using 8,192 processors. By using the underlying mesh architecture and the fact that the mesh communication is more than 100 times faster than the global router communication, their implementation is ....

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S. Kumar, S. M. Goddard, and J. F. Prins, Connected-components algorithms for meshconnected parallel computers, Presented at the 3rd DIMACS Implementation Challenge Workshop, October, 1994.

.... arbitrary bandwidth to any memory location, but the inherent contention in the algorithm makes even EREW solutions much more challenging [6, 15, 18, 20] Implementation of the theoretical work has been restricted to shared memory machines [12] and SIMD machines with very slow processors [12, 17, 23]. Many practical solutions have been developed independently of theoretical work for modern MIMD massively parallel platforms (MPP s) 7, 10, 13, 14, 21, 26] and vector machines [9, 26] With the exception of [5] which focuses on 2D graphs for robot vision, these solutions typically emphasize ....

S. Kumar, S. M. Goddard, J. F. Prins, "Connected-Components Algorithms for Mesh-Connected Parallel Computers," to be published in the Proceedings of the 3rd Annual DIMACS Challenge, 1995.

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