Invention Application
- Patent Title: HARDWARE CIRCUIT FOR DEEP LEARNING TASK SCHEDULING
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Application No.: US17374361Application Date: 2021-07-13
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Publication No.: US20220382592A1Publication Date: 2022-12-01
- Inventor: Yilin Zhang , Geng Chen , Yan Zhou , Qifei Fan , Prashant Gaikwad
- Applicant: NVIDIA Corporation
- Applicant Address: US CA Santa Clara
- Assignee: NVIDIA Corporation
- Current Assignee: NVIDIA Corporation
- Current Assignee Address: US CA Santa Clara
- Main IPC: G06F9/50
- IPC: G06F9/50 ; G06F9/48 ; G06N3/063

Abstract:
Apparatuses, systems, and techniques for scheduling deep learning tasks in hardware are described. One accelerator circuit includes multiple fixed-function circuits that each processes a different layer type of a neural network. A scheduler circuit receives state information associated with a respective layer being processed by a respective fixed-function circuit and dependency information that indicates a layer dependency condition for the respective layer. The scheduler circuit determines that the layer dependency condition is satisfied using the state information and the dependency information and enables the fixed-function circuit to process the current layer at the respective fixed-function circuit.
Public/Granted literature
- US11983566B2 Hardware circuit for deep learning task scheduling Public/Granted day:2024-05-14
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