- Patent Title: Memory storage format for supporting machine learning acceleration
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Application No.: US17946753Application Date: 2022-09-16
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Publication No.: US12165237B2Publication Date: 2024-12-10
- Inventor: Colin Beaton Verrilli , Natarajan Vaidhyanathan , Matthew Simpson , Geoffrey Carlton Berry , Sandeep Pande
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Agency: QUALCOMM Incorporated
- Main IPC: G06T1/60
- IPC: G06T1/60 ; G06N3/063

Abstract:
A processor-implemented method for a memory storage format to accelerate machine learning (ML) on a computing device is described. The method includes receiving an image in a first layer storage format of a neural network. The method also includes assigning addresses to image pixels of each of three channels of the first layer storage format for accessing the image pixels in a blocked ML storage acceleration format. The method further includes storing the image pixels in the blocked ML storage acceleration format according to the assigned addresses of the image pixels. The method also includes accelerating inference video processing of the image according to the assigned addresses for the image pixels corresponding to the blocked ML storage acceleration format.
Public/Granted literature
- US20240095872A1 MEMORY STORAGE FORMAT FOR SUPPORTING MACHINE LEARNING ACCELERATION Public/Granted day:2024-03-21
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