Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Honeycomb Networks: Topological Properties and Communication Algorithms
IEEE Transactions on Parallel and Distributed Systems
Macro-Star Networks: Efficient Low-Degree Alternatives to Star Graphs
IEEE Transactions on Parallel and Distributed Systems
Transposition Networks as a Class of Fault-Tolerant Robust Networks
IEEE Transactions on Computers
Bubblesort star graphs: a new interconnection network
ICPADS '96 Proceedings of the 1996 International Conference on Parallel and Distributed Systems
The Star Connected Cycles: A Fixed-Degree Network For Parallel Processing
ICPP '93 Proceedings of the 1993 International Conference on Parallel Processing - Volume 01
Generalized Hypercube and Hyperbus Structures for a Computer Network
IEEE Transactions on Computers
The Journal of Supercomputing
Three-dimensional Petersen-torus network: a fixed-degree network for massively parallel computers
The Journal of Supercomputing
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In this paper, we introduce new interconnection networks matrix-star graphsMTSn1,...,nk where a node is represented by n1 × ... × nk matrix and an edge is defined by using matrix operations. A matrix-star graph MTS2,n can be viewed as a generalization of the well-known star graph such as degree, connectivity, scalability, routing, diameter, and broadcasting. Next, we generalize MTS2,n to 2-dimensional and 3-dimensional matrix-star graphs MTSk, n, MTSk, n,p. One of important desirable properties of interconnection networks is network cost which is defined by degree times diameter. The star graph, which is one of popular interconnection topologies, has smaller network cost than other networks. Recently introduced network, the macro-star graph has smaller network cost than the star graph. We further improve network cost of the macro-star graph: Comparing a matrix-star graph $MTS_{k,k,k}(k = \sqrt[3]{n^{2}})$ with n2! nodes to a macro-star graph MS(n–1,n–1) with ((n–1)2+1)! nodes, network cost of MTSk,k, k is O(n2.7) and that of MS(n–1,n–1) is O(n3). It means that a matrix-star graph is better than a star graph and a macro-star graph in terms of network cost.