Invention Application
- Patent Title: WORKLOAD PERFORMANCE PREDICTION
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Application No.: US17415766Application Date: 2019-07-25
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Publication No.: US20220147430A1Publication Date: 2022-05-12
- Inventor: Carlos Haas Costa , Christian Makaya , Madhu Sudan Athreya , Raphael Gay , Pedro Henrique Garcez Monteiro
- Applicant: Hewlett-Packard Development Company, L.P.
- Applicant Address: US TX Spring
- Assignee: Hewlett-Packard Development Company, L.P.
- Current Assignee: Hewlett-Packard Development Company, L.P.
- Current Assignee Address: US TX Spring
- International Application: PCT/US2019/043458 WO 20190725
- Main IPC: G06F11/34
- IPC: G06F11/34 ; G06N20/00

Abstract:
For each of a number of workloads, time intervals within execution performance information that was collected during execution of the workload on a first hardware platform are correlated with corresponding time intervals within execution performance information that was collected during execution of the workload on a second hardware platform. For a workload, the time intervals within the execution performance information on the second hardware platform are correlated to the time intervals within the execution performance information the first hardware platform during which the same parts of the workload were executed. A machine learning model that outputs predicted performance on the second hardware platform relative to known performance on the first hardware platform is trained. The model is trained from the correlated time intervals within the execution performance information for each workload on the hardware platforms.
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