Data-driven task-execution scheduling using machine learning
US11755576B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 31, 2023 |
| Grant date | Sep 12, 2023 |
| Priority date | — |
| Expiry date | Jan 31, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/27
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system for improving task scheduling on a cloud data platform is provided. A task is received, from a user of a cloud data platform, for execution on a dataset of a cloud data platform using a plurality of resources. A task graph is generated, and metadata related to the dataset is accessed for use in execution of the task. A predicted resource profile is generated by applying a first machine learning scheme to the task graph and the metadata of the dataset. Assignment data is generated to execute processes of the task on the plurality of resources. The assignment data generated by applying a second machine learning scheme to current state data of a current computational state of the plurality of resources and the predicted resource profile generated by the first machine learning scheme.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.