Hierarchical reinforcement learning algorithm for NFV server power management
US12001932B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 27, 2020 |
| Grant date | Jun 4, 2024 |
| Priority date | — |
| Expiry date | Oct 5, 2042 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02D10/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and apparatus for hierarchical reinforcement learning (RL) algorithm for network function virtualization (NFV) server power management. A first RL model at a first layer is trained by adjusting a frequency of the core of processor while performing a workload to obtain a first trained RL model. The trained RL model is operated in an inference mode while training a second RL model at a second level in the RL hierarchy by adjusting a frequency of the core and a frequency of processor circuitry external to the core to obtain a second trained RL model. Training may be performed online or offline. The first and second RL models are operated in inference modes during online operations to adjust the frequency of the core and the frequency of the circuitry external to the core while executing software on the plurality of cores of to perform a workload, such as an NFV workload.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.