Hardware-based machine learning acceleration
US11651260B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 31, 2018 |
| Grant date | May 16, 2023 |
| Priority date | — |
| Expiry date | Oct 31, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for hardware-based machine learning acceleration is provided. The method may include partitioning, into a first batch of data and a second batch of data, an input data received at a hardware accelerator implementing a machine learning model. The input data may be a continuous stream of data samples. The input data may be partitioned based at least on a resource constraint of the hardware accelerator. An update of a probability density function associated with the machine learning model may be performed in real time. The probability density function may be updated by at least processing, by the hardware accelerator, the first batch of data before the second batch of data. An output may be generated based at least on the updated probability density function. The output may include a probability of encountering a data value. Related systems and articles of manufacture, including computer program products, are also provided.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.