Using artificial intelligence to optimize software to run on heterogeneous computing resource
US11789711B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 22, 2021 |
| Grant date | Oct 17, 2023 |
| Priority date | — |
| Expiry date | Dec 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are described that implement a tool chain which receives original software source code, analyzes the code and divides the code into modules that run optimally on the available heterogeneous resources. For example, the toolchain system segments original source code into code segments, and determine the specialized processor resource, such as a digital signal processing (DSP) processor, Field Programming Gate Array (FPGA), Graphical Processing Unit (GPU), and the like, that most optimally performs computations of the particular code segment. A parsing engine determines the processor of the heterogenous resources, based on a set of rules and/or a trained classifier (e.g., a trained machine learning model). New code segments can be generated that can be executed on the determined type of processor. Further, the system enables application programming interfaces (APIs) that can interface the new code segment with other generated code segments and/or some portions of the original code.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.