A coding framework for low-power address and data busses
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Address bus encoding techniques for system-level power optimization
Proceedings of the conference on Design, automation and test in Europe
Bus energy minimization by transition pattern coding (TPC) in deep sub-micron technologies
Proceedings of the 2000 IEEE/ACM international conference on Computer-aided design
A bus energy model for deep submicron technology
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Adaptive Bus Encoding Technique for Switching Activity Reduced Data Transfer over Wide System Buses
PATMOS '00 Proceedings of the 10th International Workshop on Integrated Circuit Design, Power and Timing Modeling, Optimization and Simulation
Intra-Bus Crosstalk Estimation Using Word-Level Statistics
VLSID '04 Proceedings of the 17th International Conference on VLSI Design
Energy reduction through crosstalk avoidance coding in networks on chip
Journal of Systems Architecture: the EUROMICRO Journal
ISQED '09 Proceedings of the 2009 10th International Symposium on Quality of Electronic Design
Data Encoding for Low-Power in Wormhole-Switched Networks-on-Chip
DSD '09 Proceedings of the 2009 12th Euromicro Conference on Digital System Design, Architectures, Methods and Tools
ORION 2.0: a fast and accurate NoC power and area model for early-stage design space exploration
Proceedings of the Conference on Design, Automation and Test in Europe
Efficient on-chip crosstalk avoidance CODEC design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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As technology reaches nanoscale order, interconnection systems account for the largest part of power consumption in Systemson-Chip. Hence, an early and sufficiently accurate power estimation technique is needed for making the right design decisions. In this paper we present a method for system-level power estimation of interconnection fabrics in Systems-on-Chip. Estimations with simple average assumptions regarding the data stream are compared against estimations considering bit level statistics in order to include low level effects like activity factors and crosstalk capacitances. By examining different data patterns and traces of a video decoding system as a realistic example, we found that the data dependent effects are not negligible influences on power consumption in the interconnection system of nanoscale chips. Due to the use of statistical data there is no degradation of simulation speed in our approach.