ACM Computing Surveys (CSUR)
Fundamentals of data structures in PASCAL
Fundamentals of data structures in PASCAL
A fully distributed (minimal) spanning tree algorithm
Information Processing Letters
Data movement techniques for the pyramid computer
SIAM Journal on Computing
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Optimal Graph Algorithms on a Fixed-Size Linear Array
IEEE Transactions on Computers
Minimum-cost spanning tree as a path-finding problem
Information Processing Letters
Transputer reference manual
The design and analysis of parallel algorithms
The design and analysis of parallel algorithms
Implementing parallel sorting algorithms on a linear array of transputers
Proceedings of the 1989 ACM/IEEE conference on Supercomputing
Graph Problems on a Mesh-Connected Processor Array
Journal of the ACM (JACM)
A Distributed Algorithm for Minimum-Weight Spanning Trees
ACM Transactions on Programming Languages and Systems (TOPLAS)
Communicating sequential processes
Communications of the ACM
Efficient VLSI Networks for Parallel Processing Based on Orthogonal Trees
IEEE Transactions on Computers
Solving some graph problems with optimal or near-optimal speedup on mesh-of-trees networks
SFCS '85 Proceedings of the 26th Annual Symposium on Foundations of Computer Science
A Systolic Design for Connectivity Problems
IEEE Transactions on Computers
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This paper presents empirical performance of parallel algorithms for connected graphs on the transputer and Unix systems, where processes are configured as a one-dimensional array. We conduct experiments for implementing (i) spanning tree algorithm (SPT-list) with unordered list of edges as input, (ii) SPT algorithm with adjacency matrix, (iii) minimum spanning tree algorithm (MST) with weight matrix as input, and (iv) SPT algorithm derived from MST algorithm by assigning each edge-weight equal to 1. The empirical study is performed with a wide range of random graphs, generated for various (uniformly distributed) edge-densities (d) for a given number (n) of vertices. We plot curves for resulting speedups as functions of n, d, and p. The edge-density d is varied between 0.1 and 0.9; maximum number of vertices (or edges) considered are 300 (or 40 000) and 500 (or 110 000) for transputer and Unix systems, respectively; and the number of processors p varies from 1 through 8 in the transputer system while 1 through 4 in the Unix system. A maximum speedup of 2.98 is obtained on transputers, and that for the Unix system is 3.0. We observe that the speedups of all algorithms vary with increasing number of vertices or edge-density. However, employing more processing units in an algorithm does not necessarily enhance its speedup because of additional communication overhead.