Higher Dimensional Gaussian Networks

Gaussian interconnection networks have been introduced as a useful alternative to the classical toroidal networks, and in this paper this concept is generalized to higher dimensions. We also explore many important properties of this new topology, including distance distribution and the decomposition of higher dimensional Gaussian networks into edge-disjoint tori and Hamiltonian cycles. In addition, an optimal shortest path routing algorithm and a one-to-all broadcast algorithm for higher dimensional Gaussian networks are given. Simulation results show that the routing algorithm proposed for higher dimensional Gaussian networks outperforms the routing algorithm of the corresponding torus network of the same node-degree and the same number of nodes.

[1]  Yaagoub Ashir,et al.  Lee Distance and Topological Properties of k-ary n-cubes , 1995, IEEE Trans. Computers.

[2]  William J. Dally,et al.  Principles and Practices of Interconnection Networks , 2004 .

[3]  Ramón Beivide,et al.  Modeling Toroidal Networks with the Gaussian Integers , 2008, IEEE Transactions on Computers.

[4]  Myung M. Bae,et al.  Edge Disjoint Hamiltonian Cycles in k-Ary n-Cubes and Hypercubes , 2003, IEEE Trans. Computers.

[5]  Ramón Beivide,et al.  Practicable layouts for optimal circulant graphs , 2005, 13th Euromicro Conference on Parallel, Distributed and Network-Based Processing.

[6]  Philip Heidelberger,et al.  The IBM Blue Gene/Q interconnection network and message unit , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[7]  Larry Kaplan,et al.  The Gemini System Interconnect , 2010, 2010 18th IEEE Symposium on High Performance Interconnects.

[8]  Hamid Sarbazi-Azad,et al.  XMulator: A Listener-Based Integrated Simulation Platform for Interconnection Networks , 2007, First Asia International Conference on Modelling & Simulation (AMS'07).

[9]  Dirk Stroobandt,et al.  The interpretation and application of Rent's rule , 2000, IEEE Trans. Very Large Scale Integr. Syst..

[10]  George Karypis,et al.  Introduction to Parallel Computing , 1994 .

[11]  Martin Cohn Affine m-ary Gray Codes , 1963, Inf. Control..

[12]  Jan M. Van Campenhout,et al.  Rent's rule and parallel programs: characterizing network traffic behavior , 2008, SLIP '08.

[13]  Zarka Cvetanovic Performance analysis of the Alpha 21364-based HP GS1280 multiprocessor , 2003, ISCA '03.

[14]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[15]  Abdel Elah Al-Ayyoub,et al.  The Cross Product of Interconnection Networks , 1997, IEEE Trans. Parallel Distributed Syst..

[16]  Ramón Beivide,et al.  Modeling hexagonal constellations with Eisenstein-Jacobi graphs , 2008, Probl. Inf. Transm..

[17]  George Varghese,et al.  A 22nm IA multi-CPU and GPU System-on-Chip , 2012, 2012 IEEE International Solid-State Circuits Conference.

[18]  Bella Bose,et al.  The Topology of Gaussian and Eisenstein-Jacobi Interconnection Networks , 2010, IEEE Transactions on Parallel and Distributed Systems.

[19]  Yuanyuan Yang,et al.  Efficient All-to-All Broadcast in Gaussian On-Chip Networks , 2013, IEEE Transactions on Computers.

[20]  Abdou Youssef Design and analysis of product networks , 1995, Proceedings Frontiers '95. The Fifth Symposium on the Frontiers of Massively Parallel Computation.

[21]  Cruz Izu,et al.  Dense Gaussian Networks: Suitable Topologies for On-Chip Multiprocessors , 2006, International Journal of Parallel Programming.