Abstract:
Heterogeneous multicore systems are composed of multiple cores with varying energy and performance characteristics. A controller dynamically detects phase changes in applications and migrates execution onto the most efficient core that meets the performance requirements. In this paper, we show that existing techniques that react to performance changes break down at fine-grain intervals, as performance variations between consecutive intervals are high. We propose a predictive trace-based switching controller that predicts an upcoming phase change in a program and preemptively migrates execution onto a more suitable core. This prediction is based on a phase�s individual history and the current program context. Our implementation detects repeatable code sequences to build history, uses these histories to predict an phase change, and preemptively migrates execution to the most appropriate core. We compare our method to phase prediction schemes that track the frequency of code blocks touched during execution as well as traditional reactive controllers, and demonstrate significant increases in prediction accuracy at fine-granularities. For a big-little heterogeneous system that is comprised of a high performing out-of-order core (Big) and an energy-efficient, in-order core (Little), at granularities of 300 instructions, the trace based predictor can spend 28% of execution time on the Little, while targeting a maximum performance degradation of 5%. This translates to an increased energy savings of 15% on average over running only on Big, representing a 60% increase over existing techniques.