Invention Grant
- Patent Title: Feature reordering based on sparsity for improved memory compression transfers during machine learning jobs
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Application No.: US16836741Application Date: 2020-03-31
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Publication No.: US11551089B2Publication Date: 2023-01-10
- Inventor: Mehdi Saeedi , Arash Hariri , Gabor Sines
- Applicant: ATI Technologies ULC
- Applicant Address: CA Markham
- Assignee: ATI Technologies ULC
- Current Assignee: ATI Technologies ULC
- Current Assignee Address: CA Markham
- Agency: Volpe Koenig
- Main IPC: G06N3/08
- IPC: G06N3/08 ; H03M7/30 ; H03M7/46 ; G06N20/00

Abstract:
A processing device for executing a machine learning neural network operation includes memory and a processor. The processor is configured to receive input data at a layer of the machine learning neural network operation, receive a plurality of sorted filters to be applied to the input data, apply the plurality of sorted filters to the input data to produce a plurality of different feature maps, compress the plurality of different feature maps according to a sparsity of the feature maps and store the plurality of different feature maps in the memory.
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