Machine-learning (ML)-based resource utilization prediction and management engine

Abstract

Systems and methods for optimizing resource utilization in a computing system are provided. Methods include compiling training data, running a machine-learning (ML) model using the training data to determine a set of resource parameters, receiving a request to schedule the computing job on the computing system, computing, for each of a plurality of potential runtimes, an amalgam distance value, selecting the potential runtime with the optimal distance value for scheduling the computing job, and generating a job execution schedule based on the selected potential runtime.

CPC Classifications