Invention Grant
- Patent Title: Compression for deep learning in case of sparse values mapped to non-zero value
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Application No.: US17390528Application Date: 2021-07-30
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Publication No.: US11763183B2Publication Date: 2023-09-19
- Inventor: Ajit Singh , Bharat Daga , Michael Behar
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Jaffery Watson Mendonsa & Hamilton LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F13/10 ; G06N3/04 ; G06N5/046 ; G06T15/20 ; G06F17/16 ; G06F13/28 ; G06N20/00 ; G06T9/00

Abstract:
Embodiments described herein provide a processing apparatus comprising compute circuitry to generate neural network data for a convolutional neural network (CNN) and write the neural network data to a memory buffer. The compute circuitry additionally includes a direct memory access (DMA) controller including a hardware codec having encode circuitry and a decode circuitry. The DMA controller reads the neural network data from the memory buffer, encode the neural network data via the encode circuit, writes encoded neural network data to a memory device coupled with the processing apparatus, writes metadata for the encoded neural network data to the memory device coupled with the processing apparatus, and decodes encoded neural network data via the decode circuit in response to a request from the compute circuitry.
Public/Granted literature
- US20210357793A1 COMPRESSION FOR DEEP LEARNING IN CASE OF SPARSE VALUES MAPPED TO NON-ZERO VALUE Public/Granted day:2021-11-18
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