Invention Grant
- Patent Title: Deep neural network workload scheduling
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Application No.: US15906963Application Date: 2018-02-27
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Publication No.: US10942767B2Publication Date: 2021-03-09
- Inventor: Ranveer Chandra , Rahul Anand Sharma
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G06F9/48
- IPC: G06F9/48 ; G06F9/50 ; G06N3/00 ; G06N3/08 ; G06N3/04 ; G06N3/063 ; G06N3/02

Abstract:
Systems, methods, and computer-executable instructions for scheduling neural network workloads on an edge device. A performance model for each neural network model is received. Parameters for each neural network workload is determined based on an associated performance model. Processing core assignments are determined from a plurality of processing cores for each neural network workload based on the corresponding performance model and processing core utilization. Image streams are received and associated with a neural network workload. Each neural network workload is scheduled to run on the processing cores based on the processing core assignments.
Public/Granted literature
- US20190266015A1 DEEP NEURAL NETWORK WORKLOAD SCHEDULING Public/Granted day:2019-08-29
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