Early-Convergence Detection for Online Resource Allocation Policies for Iterative Workloads

摘要

Techniques are provided for adaptive resource allocation for workloads with early-convergence detection. One method comprises obtaining a dynamic system model based on a relation between an amount of a resource for multiple workloads and a predefined service metric; obtaining an instantaneous value of the predefined service metric; obtaining an adjustment to the amount of the resource for a given workload based on a difference between the instantaneous value and a target value of the predefined service metric; determining whether the given workload has converged based on an evaluation of one or more predefined convergence criteria; and removing the given workload from a controlled workload list when the given workload has converged. The given workload can be reinserted in the controlled workload list when the given one of the plurality of workloads fails to satisfy a predefined divergence threshold.