Synonyms: Energy-aware computing, Energy-efficient computing.
Power-aware computing is part of the Green AI. Power-aware design strategies strive to maximise performance in high-performance systems within power dissipation and power consumption constraints. Reduced power utilisation on a node is one way to reduce the amount of energy required to compute. Lowering the frequency at which the CPU works on one approach to do this. Reduced clock speed, on the other hand, increases the time to solution, posing a potential compromise.
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Low-power design strategies attempt to decrease power or energy consumption in portable equipment in order to fulfil a particular performance or throughput objective. All of the energy used by a system ultimately dissipates and is converted to heat. Power dissipation and related thermal issues have an impact on performance, packaging, reliability, environmental impact, and heat removal costs; power and energy consumption have an impact on power delivery costs, performance, and reliability, and they are directly related to portable device size and battery life.
Power-aware computing’s major purpose is to save energy while routing communications from source to destination. The contemporary period is characterised by wireless networks, in which nodes connect with one another over many hops. In this technology, many data transfer protocols are employed. Different routing techniques will draw more power from the battery. In power-aware computing, power-aware routing metrics have played an essential role.
This entry was written by Andrea Rossi, Andrea Visentin and Barry O’Sullivan.