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Google patents chip system that predicts heat to manage performance

Patent drawing
Patent drawing from the official filing.

This filing describes a system-on-chip that uses a machine-learning model to predict future operating conditions, such as processor temperature. Based on these predictions, the system adjusts settings like frequency, voltage, or task assignments to balance performance and heat.

Why it mattersThis approach could help devices maintain smooth performance without overheating by anticipating changes before they happen.

In the filing’s own words

Techniques and apparatuses are described for implementing a machine-learning (ML) based prediction and dynamic core allocation architecture. In example aspects, a plurality of parameters related to one or more operating conditions (e.g., temperature of a core) of one or more processors are generated. The plurality of parameters are used as an input for an ML-based model, which outputs a prediction of future parameters. The prediction is used as input for one or more process modules. The one or more process modules parse the prediction to provide a decision output, which is used to modify one or more facets of the one or more processors (a frequency, a voltage, core assignments for tasks, etc.). In this way, a system-on-chip can dynamically manage multiple operations concerns for the one or more processors, such as balancing performance and temperature concerns to realize a tailored user experience.

What exactly they claim (claim 1)

1. A method performed by a system-on-chip, the method comprising: generating a plurality of parameters related to one or more operating conditions of one or more processors; receiving one or more prediction outputs from a machine-learned (ML) model, the ML model: configured to use an ML input, the ML input based on the plurality of parameters related to the one or more operating conditions of the one or more processors and the one or more prediction outputs based on the ML input; and trained on data related to the one or more operating conditions of the one or more processors; and generating, by one or more process modules and based on the one or more prediction outputs, a command for the one or more processors, the command configured to change one or more of the one or more operating conditions of the one or more processors.

Facts

Company
Google (Google LLC)
Official title
Machine-Learning-Based Prediction and Dynamic Core Allocation Architecture
Publication number
US20260310960A1
Application number
19574897
Filed
Mar 23, 2026
Published
Oct 8, 2026
Inventors
2
Claims
20

Classified under

G06N 3/08 Physics & computingG06N 3/0464 Physics & computing
Read the full filing (official PDF) ↗ Open in the Patent Tracker

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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.