Butterfly Automorphisms and Edge Faults

Wagh, Meghanad D.; Bendjilali, K.

doi:10.1109/ispdc.2010.11

Cited by 1 publication

(2 citation statements)

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“…In addition, this new model allows one to exploit the powerful results in finite fields that have been developed over a century. A similar algebraic model for Wrapped Butterflies has previously allowed highly efficient mappings of cycles and trees [2] as well as investigations into automorphisms and fault avoidance [13,14]. The new models proposed here can be used to obtain similar results in case of the Cube Connected Cycles networks.…”

Section: Discussionmentioning

confidence: 83%

“…With these new models, one can avail of powerful algebraic techniques to investigate the structure and mappings of these networks. Similar algebraic models developed previously for the deBruijn network [12] and the Wrapped Butterflies [2] have allowed efficient mappings of cycles and trees on the Butterflies and provided insights into intricate structural properties such as the automorphisms [13,14]. The new models proposed here help solve similar problems in CCC n .…”

Section: Introductionmentioning

confidence: 73%

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Algebraic Models for the Cube Connected Cycles and Shuffle Exchange Graphs

Wagh

Bendjilali

2011

2011 IEEE International Conference on High Performance Computing and Communications

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Interconnection networks often constrain the performance of multi-cores chips or parallel computers. Cube Connected Cycles (CCC) is an attractive interconnection network because of its symmetry, small constant node degree and a small diameter. This paper develops an algebraic model for the CCC using the direct product of a cyclic group and a finite field. This model allows the use of powerful algebraic techniques to study the structural properties of the network. This paper exploits these techniques to find optimal paths in the CCC and to explore the relationships between the Cube Connected Cycles, the Shuffle Exchange and the deBruijn networks.

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Section: Discussionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 73%