The interpretation and application of Rent's rule
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on system-level interconnect prediction
Principles and Practices of Interconnection Networks
Principles and Practices of Interconnection Networks
Mapping embedded systems onto NoCs: the traffic effect on dynamic energy estimation
SBCCI '05 Proceedings of the 18th annual symposium on Integrated circuits and system design
Energy-aware mapping for tile-based NoC architectures under performance constraints
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
A Statistical Traffic Model for On-Chip Interconnection Networks
MASCOTS '06 Proceedings of the 14th IEEE International Symposium on Modeling, Analysis, and Simulation
Implications of Rent's Rule for NoC Design and Its Fault-Tolerance
NOCS '07 Proceedings of the First International Symposium on Networks-on-Chip
Rent's rule and parallel programs: characterizing network traffic behavior
Proceedings of the 2008 international workshop on System level interconnect prediction
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
Hybrid network on chip (HNoC): local buses with a global mesh architecture
Proceedings of the 12th ACM/IEEE international workshop on System level interconnect prediction
Reducing energy and increasing performance with traffic optimization in many-core systems
Proceedings of the System Level Interconnect Prediction Workshop
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In systems on chip, the energy consumed by the Network on Chip (NoC) depends heavily on the network traffic pattern. The higher the communication locality, the lower the energy consumption will be. In this paper, we use the Communication Probability Distribution (CPD) to model communication locality and energy consumption in NoC. Firstly, based on recent results showing that communication patterns of many parallel applications follow Rent's rule, we propose a Rent's rule [6] traffic generator. In this method, the probability of communication between cores is derived directly from Rent's rule, which results in CPDs displaying high locality. Next, we provide a model for predicting NoC energy consumption based on the CPD. The model was tested on two NoC systems and several workloads, including Rent's rule traffic, and obtained accurate results when compared to simulations. The results also show that Rent's rule traffic has lower energy consumption than commonly used synthetic workloads, due to its higher communication locality. Finally, we exploit the tunability of our traffic generator to study applications with different locality, analyzing the impact of the Rent's exponent on energy consumption.