Title :
On self-similarity and hamiltonicity of dual-cubes
Author :
Wu, Changfu ; Wu, Jie
Author_Institution :
Dept. of Comput. Sci. & Eng., Florida Atlantic Univ., Boca Raton, FL, USA
Abstract :
The dual-cube is a newly proposed topology for interconnection networks, which uses low dimensional hypercubes as building blocks. The primary advantages of the dual-cube over the hypercube are that, with the same node degree n, the dual-cube contains 2n-1 times more nodes than the hypercube and, with the same amount of nodes, the dual-cube has approximately 50% less links than the hypercube. This paper was focused on the investigations of the structural self-similarity and the Hamiltonian property of the dual-cube. It was shown that a dual-cube can be recursively constructed from lower dimensional dual-cubes and, conversely, a dual-cube can be recursively decomposed into lower dimensional dual-cubes. It was also proved that all dual-cubes are Hamiltonian. There exist multiple Hamiltonian cycles on a dual-cube, among which, [(n-1)/2] cycles are edge-disjoint. It was illustrated that rings and linear arrays can be effectively emulated on dual-cubes. Some strategies for track sharing in efficient VLSI layout design were also discussed.
Keywords :
VLSI; circuit layout CAD; hypercube networks; VLSI layout design; dual cube topology; hamiltonicity; linear arrays; low dimensional hypercubes; self similarity; track sharing; Computer architecture; Computer science; Costs; Hypercubes; Multiprocessor interconnection networks; Network topology; Parallel processing; Routing; Silicon; Very large scale integration;
Conference_Titel :
Parallel and Distributed Processing Symposium, 2003. Proceedings. International
Print_ISBN :
0-7695-1926-1
DOI :
10.1109/IPDPS.2003.1213490