Hierarchical adaptive Multi-objective resource management for many-core systems

摘要

The typical workload of many-core systems produces peaks and valleys of resources utilization throughout the time. The power capping limits the full system utilization in a workload peak, but also creates a power slack to apply different resource management (RM) policy in a valley phase. Related works do not consider this workload behavior, by proposing RMs with fixed goals. This work proposes a hierarchical adaptive Multi-Objective Resource Management (MORM) for many-core systems under a power cap. MORM works with dynamic workloads, which presents peaks and valleys of utilization. The hierarchical approach allows clusters of processing elements (PEs) to execute applications according to different objectives simultaneously. A cluster can drive the PEs to optimize either performance or energy. MORM can dynamically shift the goals of a cluster according to the workload behavior. Comparison with a state-of-the-art RM optimized for single objective shows that MORM achieves equivalent results in a workload valley while outperforming up to 37.19-49.03% the performance in a workload peak regardless of the power cap. The comparison reveals relevant features to be considered in large many-core systems: hierarchical organization, multi-task mapping, and joint adaptability between software (remapping) and hardware (DVFS) actuation.