Data inspection for compression/decompression configuration and data type determination
US12346835B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Mar 7, 2018 |
| Grant date | Jul 1, 2025 |
| Priority date | — |
| Expiry date | Jul 1, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2212/401
- WIPO fieldBasic communication processes
- WIPO sectorElectrical engineering
Abstract
Distribution of data in a neural network data set is used to determine an optimal compressor configuration for compressing the neural network data set and/or the underlying data type of the neural network data set. By using a generalizable optimization of examining the data prior to compressor invocation, the example non-limiting technology herein makes it possible to tune a compressor to better target the incoming data. For sparse data compression, this step may involve examining the distribution of data (e.g., in one example, zeros in the data). For other algorithms, it may involve other types of inspection. This changes the fundamental behavior of the compressor itself. By inspecting the distribution of data (e.g., zeros in the data), it also possible to very accurately predict the data width of the underlying data. This is useful because this data type is not always known a priori, and lossy compression algorithms useful for deep learning depend on knowing the true data type to achieve good compression rates.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.