TY - GEN
T1 - Modeling NoC traffic locality and energy consumption with Rent's communication probability distribution
AU - Bezerra, George B.P.
AU - Forrest, Stephanie
AU - Moses, Melanie
AU - Davis, Al
AU - Zarkesh-Ha, Payman
PY - 2010
Y1 - 2010
N2 - 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 [6], we propose a Rent's rule 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.
AB - 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 [6], we propose a Rent's rule 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.
KW - Communication probability distribution
KW - Energy consumption
KW - Networks on chip
KW - Rent's rule
KW - Synthetic traffic generation
UR - http://www.scopus.com/inward/record.url?scp=77954916665&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954916665&partnerID=8YFLogxK
U2 - 10.1145/1811100.1811103
DO - 10.1145/1811100.1811103
M3 - Conference contribution
AN - SCOPUS:77954916665
SN - 9781450300377
T3 - International Workshop on System Level Interconnect Prediction, SLIP
SP - 3
EP - 8
BT - SLIP'10 - Proceedings of the 2010 Workshop on System Level Interconnect Prediction
T2 - 12th ACM/IEEE International Workshop on System Level Interconnect Prediction, SLIP'10
Y2 - 13 June 2010 through 13 June 2010
ER -