An Opportunistic Prediction-based Thread Scheduling to Maximize Throughput/Watt in AMPs

Abstract—The importance of dynamic thread scheduling is increasing with the emergence of Asymmetric Multicore Proces-sors (AMPs). Since the computing needs of a thread often vary during its execution, a fixed thread-to-core assignment is sub-optimal. Reassigning threads to cores (thread swapping) when the threads start a new phase with different computational needs, can significantly improve the energy efficiency of AMPs. Although identifying phase changes in the threads is not difficult, deter-mining the appropriate thread-to-core assignment is a challenge. Furthermore, the problem of thread reassignment is aggravated by the multiple power states that may be available in the cores. To this end, we propose a novel technique to dynamically assess the program phase needs and determine whether swapping threads between core-types and/or changing the voltage/frequency levels (DVFS) of the cores will result in higher throughput/Watt. This is achieved by predicting the expected throughput/Watt of the current program phase at different voltage/frequency levels on all the available core-types in the AMP. We show that the benefits from thread swapping and DVFS are orthogonal, demonstrating the potential of the proposed scheme to achieve significant benefits by seamlessly combining the two. We illustrate our approach using a dual-core High-Performance (HP)/Low-Power (LP) AMP with two power states and demonstrate significant throughput/Watt improvement over different baselines. Index Terms—Asymmetric Multicore Processor (AMP); dy-namic thread scheduling; Hardware Performance Counter