Abstract: Techniques and systems are provided that work to minimize the energy usage of computing devices by building and using models that predict the future work required of one or more components of a computing system, based on observations, and using such forecasts in a decision analysis that weighs the costs and benefits of transitioning components to a lower power and performance state. Predictive models can be generated by machine learning methods from libraries of data collected about the future performance requirements on components, given current and recent observations. The models may be used to predict in an ongoing manner the future performance requirements of a computing device from cues. In various aspects, models that predict performance requirements that take into consideration the latency preferences and tolerances of users are used in cost-benefit analyses that guide powering decisions.

Abstract: Techniques and systems are provided that work to minimize the energy usage of computing devices by building and using models that predict the future work required of one or more components of a computing system, based on observations, and using such forecasts in a decision analysis that weighs the costs and benefits of transitioning components to a lower power and performance state. Predictive models can be generated by machine learning methods from libraries of data collected about the future performance requirements on components, given current and recent observations. The models may be used to predict in an ongoing manner the future performance requirements of a computing device from cues. In various aspects, models that predict performance requirements that take into consideration the latency preferences and tolerances of users are used in cost-benefit analyses that guide powering decisions.

Abstract: A computer system, method and computer readable medium for memory management with intelligent trimming of pages of working sets are disclosed. The computer system has memory space allocatable in chunks, known as pages, to specific application programs or processes. The pages allocated to a specific application program or process define a working set of pages for the program or process. Occasionally, a system runs short of free memory space and needs to reduce the size of working sets using a process called trimming. A trimming method is disclosed that estimates numbers of trimmable pages for working sets based upon a measure of how much time has elapsed since the memory pages were last accessed by the corresponding application program. This estimation is performed prior to the need to trim working sets, and the trimming method uses these estimates to facilitate faster and more accurate trimming and thus faster recovery from shortages of free memory.