Invention Application
- Patent Title: DYNAMIC TASK ALLOCATION FOR NEURAL NETWORKS
-
Application No.: US16776338Application Date: 2020-01-29
-
Publication No.: US20200167193A1Publication Date: 2020-05-28
- Inventor: Francesco ROSSI , Gaurav KAPOOR , Michael R. SIRACUSA , William B. MARCH
- Applicant: Apple Inc.
- Main IPC: G06F9/50
- IPC: G06F9/50 ; G06F8/41 ; G06N3/02 ; G06N3/063

Abstract:
The subject technology provides for dynamic task allocation for neural network models. The subject technology determines an operation performed at a node of a neural network model. The subject technology assigns an annotation to indicate whether the operation is better performed on a CPU or a GPU based at least in part on hardware capabilities of a target platform. The subject technology determines whether the neural network model includes a second layer. The subject technology, in response to determining that the neural network model includes a second layer, for each node of the second layer of the neural network model, determines a second operation performed at the node. Further the subject technology assigns a second annotation to indicate whether the second operation is better performed on the CPU or the GPU based at least in part on the hardware capabilities of the target platform.
Public/Granted literature
- US11520629B2 Dynamic task allocation for neural networks Public/Granted day:2022-12-06
Information query