DocumentCode :
1752821
Title :
Low Power Design based on Neural Network Forecasting for Interconnection Networks
Author :
Xie, Jianyang ; Tang, Xianglong ; Li, Tiecai
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol.
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
2979
Lastpage :
2983
Abstract :
Power consumption is a key issue in high-performance interconnection network design. In interconnection network, power consumption of interconnection links will take up an ever larger portion of the power budget as demand for network bandwidth increases. Network traffic is an important factor that influences interconnection network power consumption. In this paper, we presented a traffic forecasting model using neural network method. Our interconnection network traffic forecasting model based on neural network adopted back-propagation learning algorithm and divided network period of time into two parts: stationary-hours and non-stationary-hours. Then we proposed voltage scaling algorithm for links based on our forecasting model. The results show that our forecasting model is well matched to real network traffic, and our links voltage scaling algorithm reduce power consumption of interconnection network effectively
Keywords :
backpropagation; bandwidth allocation; forecasting theory; low-power electronics; multiprocessor interconnection networks; neural nets; power aware computing; backpropagation learning; interconnection network design; low power design; network bandwidth; network traffic; neural network forecasting; power consumption; traffic forecasting model; voltage scaling algorithm; Computer science; Demand forecasting; Energy consumption; Multiprocessor interconnection networks; Neural networks; Predictive models; Technology forecasting; Telecommunication traffic; Traffic control; Voltage; interconnection network; network traffic; neural network; voltage scaling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1712912
Filename :
1712912
Link To Document :
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