Nvidia patents method to thin out neural network data for faster math
Nvidia describes a technique to rearrange data in neural networks to make them sparser, meaning they contain more empty or zero values. This structural change helps computers perform calculations more efficiently by skipping unnecessary data points.
In the filing’s own words
Apparatuses, systems, and techniques to transform data sets, such as matrices representing layers of neural networks, to increase sparsity and/or other characteristics of said data sets to improve performance in computations, such as neural network computations. In at least one embodiment, one or more subsets of data in one or more sets of data are rearranged as part of a process to increase sparsity in said one or more sets of data to satisfy one or more one or more structural sparsity constraints.
What exactly they claim (claim 1)
1.- 20. (canceled)
Facts
- Company
- Nvidia (NVIDIA Corporation)
- Official title
- INCREASING SPARSITY IN DATA SETS
- Publication number
- US20260288685A1
- Application number
- 19301080
- Filed
- Aug 15, 2025
- Published
- Sep 24, 2026
- Inventors
- 3
- Claims
- 21
Classified under
G06F 16/215 Physics & computingG06N 3/04 Physics & computingG06N 3/08 Physics & computingMore from Nvidia in AI & software
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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.