Invention Grant
- Patent Title: Dynamic accelerator scheduling and grouping for deep learning jobs in a computing cluster
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Application No.: US15963331Application Date: 2018-04-26
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Publication No.: US10884795B2Publication Date: 2021-01-05
- Inventor: Junfeng Liu , Kuan Feng , Qing Xu , Zhichao Su
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Griffiths & Seaton PLLC
- Main IPC: G06F9/46
- IPC: G06F9/46 ; G06F9/48 ; G06F9/50 ; H04L29/08 ; G06N20/00

Abstract:
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.
Public/Granted literature
- US20190332422A1 DYNAMIC ACCELERATOR SCHEDULING AND GROUPING FOR DEEP LEARNING JOBS IN A COMPUTING CLUSTER Public/Granted day:2019-10-31
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