Neural network activation compression with non-uniform mantissas
US11562247B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 24, 2019 |
| Grant date | Jan 24, 2023 |
| Priority date | — |
| Expiry date | Oct 12, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH03M7/702
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Apparatus and methods for training a neural network accelerator using quantized precision data formats are disclosed, and in particular for storing activation values from a neural network in a compressed format having lossy or non-uniform mantissas for use during forward and backward propagation training of the neural network. In certain examples of the disclosed technology, a computing system includes processors, memory, and a compressor in communication with the memory. The computing system is configured to perform forward propagation for a layer of a neural network to produced first activation values in a first block floating-point format. In some examples, activation values generated by forward propagation are converted by the compressor to a second block floating-point format having a non-uniform and/or lossy mantissa. The compressed activation values are stored in the memory, where they can be retrieved for use during back propagation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.