Hybrid scheduling method for deep learning workloads, and computing apparatus with hybrid scheduling
US12056525B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 10, 2021 |
| Grant date | Aug 6, 2024 |
| Priority date | — |
| Expiry date | Mar 25, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A scheduling method performed by a computing apparatus includes: generating an input vector including a resource status and metadata of each of tasks for parallel execution; determining an action for the input vector by executing an actor network based on the input vector; performing first resource scheduling for each of the tasks based on the determined action; performing second resource scheduling for each of the tasks based on the input vector; evaluating performance of first resource scheduling results of the first resource scheduling and second resource scheduling results of the second resource scheduling, for each of the tasks, using a critic network; selecting one of the first and second resource scheduling results for each of the tasks based on a result of the evaluating; and allocating resources to each of the tasks based on a resource scheduling result selected for each of the tasks.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.