Asynchronous distributed data flow for machine learning workloads
US12112198B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 15, 2022 |
| Grant date | Oct 8, 2024 |
| Priority date | — |
| Expiry date | Dec 15, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/098
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributing machine learning workloads, e.g., computations for training a neural network or computing an inference using a neural network, across multiple hardware accelerators. One of the systems comprises a plurality of accelerator islands, each hardware accelerator island comprising a respective plurality of hardware devices that include a plurality of hardware accelerators and a corresponding host for each of the plurality of hardware accelerators; and a respective scheduler for each of the accelerator islands that is configured to schedule workloads across the plurality of accelerators and corresponding hosts in the accelerator island, wherein the system is configured to: receive data representing a machine learning workload; and assign a respective portion of the machine learning workload to each of the plurality of accelerator islands for scheduling by the respective scheduler for the accelerator island.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.