- 专利标题: WORKLOAD MANAGEMENT USING A TRAINED MODEL
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申请号: US17303883申请日: 2021-06-09
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公开(公告)号: US20220398021A1公开(公告)日: 2022-12-15
- 发明人: Mayukh Dutta , Aesha Dhar Roy , Manoj Srivatsav , Ganesha Devadiga , Geethanjali N. Rao , Prasenjit Saha , Jharna Aggarwal
- 申请人: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
- 申请人地址: US TX Houston
- 专利权人: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
- 当前专利权人: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
- 当前专利权人地址: US TX Houston
- 主分类号: G06F3/06
- IPC分类号: G06F3/06 ; G06N20/00
摘要:
In some examples, a system creates a training data set based on features of sample workloads, the training data set comprising labels associated with the features of the sample workloads, where the labels are based on load indicators generated in a computing environment relating to load conditions of the computing environment resulting from execution of the sample workloads. The system groups selected workloads into a plurality of workload clusters based on features of the selected workloads, and computes, using a model trained based on the training data set, parameters representing contributions of respective workload clusters of the plurality of workload clusters to a load in the computing environment. The system performs workload management in the computing environment based on the computed parameters.
公开/授权文献
- US12093530B2 Workload management using a trained model 公开/授权日:2024-09-17
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