DYNAMIC ACCELERATOR SCHEDULING AND GROUPING FOR DEEP LEARNING JOBS IN A COMPUTING CLUSTER

摘要

Embodiments for dynamic accelerator scheduling and grouping for deep learning jobs in a computing cluster. An efficiency metric of each job executing in the computing cluster is calculated to generate a prioritized job queue. Accelerator re-grouping execution plans are then generated based on the prioritized job queue, the accelerator re-grouping execution plans associated with a target cluster topology to be achieved according to the placement of selected jobs from the prioritized job queue in relation to a location of respective ones of a plurality of accelerators within the computing cluster. One of the accelerator re-grouping execution plans is executed to allocate the selected jobs to the respective ones of the plurality of accelerators to thereby shift the computing cluster to the target cluster topology.