Mobile computers, such as cell phones and personal digital assistants (PDAs), have dramatically increased in sophistication. At the same time, the desire of consumers for portability limits batters size. As a result, many researchers have targeted hardware and software energy optimization. However, most of these techniques focus on compute-intensive applications rather than interactive applications, which are dominant in mobile computers. These systems frequently use graphical user interfaces (GUIs) to handle human-computer interaction. This paper is the first to explore how GUIs can be designed to improve system energy efficiency. We investigate how GUI design approaches should be changed to improve system. Energy efficiency and provide specific suggestions to mobile computer designers to enable them to develop more energy-efficient systems. We demonstrate that energy-efficient GUI (E/sup 2/GUI) design techniques can improve the average system energy of three benchmarks (text-viewer, personnel viewer, and calculator) by 26.9, 45.2, and 16.4 percent, respectively. Average performance is simultaneously improved by 23.7, 34.6, and 19.3 percent, respectively.

In this paper, we describe a comprehensive high-level synthesis system for control-flow intensive as well as data-dominated behaviors. We propose a new control-data flow graph model to preserve the parallelism inherent in the application, as well as to facilitate high-level synthesis. Our algorithm, which is based on an iterative improvement strategy, performs clock selection, scheduling, module selection, resource allocation and assignment simultaneously to fully derive the benefits of design space exploration at the behavior level. The system can be used to optimize area, power or energy, by selecting the cost function accordingly. Experimental results show that for energy-optimized designs, energy is reduced by up to 79.4% (an average of 42.2%), with an average of 24.8% area overhead, compared to area-optimized designs. For power-optimized designs, power is reduced by up to 70.8% (an average of 56.7%), with an average of 25.2% area overhead, compared to area-optimized designs. No Vdd scaling is performed to obtain the above results.