Performance Analysis of k-ary n-cube Interconnection Networks
IEEE Transactions on Computers
SAC '97 Proceedings of the 1997 ACM symposium on Applied computing
Limits on Interconnection Network Performance
IEEE Transactions on Parallel and Distributed Systems
Principles and Practices of Interconnection Networks
Principles and Practices of Interconnection Networks
VLSID '08 Proceedings of the 21st International Conference on VLSI Design
A Markovian Performance Model for Networks-on-Chip
PDP '08 Proceedings of the 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008)
Scalability of network-on-chip communication architecture for 3-D meshes
NOCS '09 Proceedings of the 2009 3rd ACM/IEEE International Symposium on Networks-on-Chip
Analysis of worst-case delay bounds for on-chip packet-switching networks
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
An analytical method for evaluating network-on-chip performance
Proceedings of the Conference on Design, Automation and Test in Europe
Flow regulation for on-chip communication
Proceedings of the Conference on Design, Automation and Test in Europe
Buffer optimization in network-on-chip through flow regulation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
An analytical approach for network-on-chip performance analysis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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A general expression for the average distance for meshes of any dimension and radix, including unequal radices in different dimensions, valid for any traffic pattern under zero-load condition is formulated rigorously to allow its calculation without network-level simulations. The average distance expression is solved analytically for uniform random traffic and for a set of local random traffic patterns. Hot spot traffic patterns are also considered and the formula is empirically validated by cycle true simulations for uniform random, local, and hot spot traffic. Moreover, a methodology to attain closed-form solutions for other traffic patterns is detailed. Furthermore, the model is applied to guide design decisions. Specifically, we show that the model can predict the optimal 3-D topology for uniform and local traffic patterns. It can also predict the optimal placement of hot spots in the network. The fidelity of the approach in suggesting the correct design choices even for loaded and congested networks is surprising. For those cases we studied empirically it is 100%.