Cross-Component Energy Management: Joint Adaptation of Processor and Memory

Researchers have proposed the use of adaptation to reduce the energy consumption of different hardware components, such as the processor, memory, disk, and display for general-purpose applications. Previous algorithms to control these adaptations, however, have focused on a single component. This work takes the first step toward developing algorithms that can jointly control adaptations in multiple interacting components for general-purpose applications, with the goal of minimizing the total energy consumed within a specified performance loss. Specifically, we develop a joint-adaptation algorithm for processor and memory adaptations.We identify two properties that enable per-component algorithms to be easily used in a cross-component context—the algorithms’ performance impact must be guaranteed and composable. We then modify a current processor and a memory algorithm to obey these properties. This allows the cross-component problem to be reduced to determine an appropriate (energy-optimal) allocation of the target performance loss (slack) between the two components. We develop such an optimal slack allocation algorithm that exploits the above properties. The result is an efficient cross-component adaptation framework that minimizes the total energy of the processor and memory without exceeding the target performance loss, while substantially leveraging current per-component algorithms. Our experiments show that joint processor and memory adaptation provides significantly more energy savings than adapting either component alone; intelligent slack distribution is specifically effective for highly computeor memory-intensive applications; and the performance slowdown never exceeds the specification.