A Feedback-Based Approach to DVFS in Data-Flow Applications

Runtime frequency and voltage adaptation has become very attractive for current and next generation embedded multicore platforms because it allows handling the workload variabilities arising in complex and dynamic utilization scenarios. The main challenge of dynamic frequency adaptation is to adjust the processing speed of each element to match the quality-of-service requirements in the presence of workload variations. In this paper, we present a control theoretic approach to dynamic voltage/frequency scaling for data-flow models of computations mapped to multiprocessor systems-on-chip architectures. We discuss, in particular, nonlinear control approaches to deal with general streaming applications containing both pipeline and parallel stages. Theoretical analysis and experiments, carried out by means of a cycle-accurate energy-aware multiprocessor simulation platform, are provided. We have applied the proposed control approach to realistic streaming applications such as Data Encryption Standard and software-based FM radio.