2006 1st International Conference on Nano-Networks and Workshops 2006
DOI: 10.1109/nanonet.2006.346216
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Area and Power Modeling Methodologies for Networks-on-Chip

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Cited by 12 publications
(4 citation statements)
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References 24 publications
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“…In [79] and in [80] Networks are configurable by a set of nineteen parameters that represent the network configuration and can be divided in two main categories: network architecture and router architecture. The traffic description involves three additional parameters.…”
Section: Application Examplesmentioning
confidence: 99%
“…In [79] and in [80] Networks are configurable by a set of nineteen parameters that represent the network configuration and can be divided in two main categories: network architecture and router architecture. The traffic description involves three additional parameters.…”
Section: Application Examplesmentioning
confidence: 99%
“…We have built accurate analytical models for calculating the power consumption, area and delay of the  pipes network components [48]. To get an accurate estimate of these parameters, they are extracted from real placed&routed NoC designs.…”
Section: Area Power Models For Noc Componentsmentioning
confidence: 99%
“…From this plot we can infer that at low operating frequencies, a topology with few, but large switches results in the most power optimal design. This is due to the fact that the increase in power consumption is mostly linear with the increase in switch size [48]. Thus, in a design with fewer switches, the traffic flows traverse shorter paths, thereby leading to designs with better power consumption.…”
Section: Impact Of Frequency Constraintsmentioning
confidence: 99%
“…The characterization is dependent on the target technology library, but can be easily scripted and automated. A major novel feature of our study, improving on our previous work [1], is that we explore the accuracy of our modeling style against placed and routed test instances; we feel that this is an essential step given the uncertainties intrinsic in today's technology processes. We also show that model coefficients can be made even more accurate by using a placed and routed training set for characterization, albeit at a modeling effort cost, and that the remaining inaccuracies can mostly be attributed to the intrinsic variations induced by synthesis tools.…”
Section: Introductionmentioning
confidence: 99%