SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79 . 1.45 . 1.18-competitive separately for traditional timeout PM . adaptive predictive PM and stochastic PM.

The design structure system - A method for managing the design of complex systems

Systems design involves the determination of interdependent variables. Thus the precedence ordering for the tasks of determining these variables involves circuits. Circuits require planning decisions abut how to iterate and where to use estimates. Conventional planning techniques, such as critical path, do not deal with these problems. Techniques are shown in this paper which acknowledge these circuits in the design of systems. These techniques can be used to develop an effective engineering plan, showing where estimates are to be used, how design iterations and reviews are handled, and how information flows during the design work.