Reinforced computer learning system and method for minimizing power consumed by underutilized data center hardware components
US11996988B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 27, 2023 |
| Grant date | May 28, 2024 |
| Priority date | — |
| Expiry date | Apr 27, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/1012
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
An information handling system executing a reinforcement learning (RL) based data center power consumption minimizing system may comprise a network interface device to receive operational telemetry measurements for a plurality of data center processors forming a processing node, including performance and utilization analytics, and a user-specified low-utility threshold value, a hardware processor to predict a future time window in which a utilization rate for the processing node executing a future workload falls below the user-specified low-utility threshold value, the hardware processor to identify an optimal load-balancing instruction for redistributing the future workload across a sub-portion of the processing system associated with a highest reward value for satisfying quality of service (QoS) requirements, and the network interface device to transmit the optimal load-balancing instruction and an instruction to throttle power supplied to a remainder of the processing system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.