A Control-Theoretic Approach to Dynamic Voltage Scheduling

摘要

The development of energy-conscious embedded and/or mobile systems exposes a trade-off between energy consumption and system performance. Recent microprocessors have incorporated dynamic voltage scaling as a tool that system software can use to explore this trade-off. Developing appropriate heuristics to control this feature is a non-trivial venture; as has been shown in the past, voltage-scaling heuristics that closely track perceived performance requirements do not save much energy, while those that save the most energy tend to do so at the expense of performance—resulting in poor response time, for example. We note that the task of dynamically scaling processor speed and voltage to meet changing performance requirements resembles a classical control-systems problem, and so we apply a bit of control theory to the task in order to define a new voltage-scaling algorithm. We find that, using our nqPID (not quite PID) algorithm, one can improve upon the current best-of-class heuristic—Pering's AVG_N algorithm, based on Govil's AGED_AVERAGES algorithm and Weiser's PAST algorithm—in both energy consumption and performance. The study is execution-based, not trace-based; the voltage-scaling heuristics were integrated into an embedded operating system running on a Motorola M-CORE processor model. The applications studied are all members of the MediaBench benchmark suite.