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Nvidia patents chip math trick to speed up AI calculations

Patent drawing
Patent drawing from the official filing.

Nvidia describes a method for computer chips to perform matrix math, a core task in AI, more efficiently. The system adjusts the size of numbers in the data before multiplying them, using specific scale factors stored in the chip's memory.

Why it mattersThis technique could help processors handle large AI models faster and with less power, which is key for running advanced software on devices.

In the filing’s own words

Apparatuses, systems, and techniques to perform matrix multiply-accumulate operations with block scaling of specified portions of input matrices by scale factors. In at least one embodiment, an input matrix is multiplied by a scaled matrix that is generated by multiplying elements of a second input matrix by one or more corresponding scale factors stored in one or more registers.

What exactly they claim (claim 1)

1. One or more processors, comprising: circuitry to perform an instruction to perform one or more matrix multiply-accumulate (MMA) operations to multiply a first input matrix by a scaled matrix generated by multiplying one or more elements of a second input matrix by one or more corresponding scale factors stored in one or more registers.

Facts

Company
Nvidia (NVIDIA Corporation)
Official title
MATRIX MULTIPLICATION WITH BLOCK SCALING USING REDUCED-SIZE DATA TYPES
Publication number
US20260310751A1
Application number
19317097
Filed
Sep 2, 2025
Published
Oct 8, 2026
Inventors
4
Claims
20

Classified under

G06F 17/16 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.