Invention Grant
- Patent Title: Accelerating neural networks with low precision-based multiplication and exploiting sparsity in higher order bits
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Application No.: US16909295Application Date: 2020-06-23
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Publication No.: US11714998B2Publication Date: 2023-08-01
- Inventor: Avishaii Abuhatzera , Om Ji Omer , Ritwika Chowdhury , Lance Hacking
- 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
- Priority: IN 2041019060 2020.05.05
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06N3/08 ; G06N3/04 ; G06N3/088

Abstract:
An apparatus to facilitate accelerating neural networks with low precision-based multiplication and exploiting sparsity in higher order bits is disclosed. The apparatus includes a processor comprising a re-encoder to re-encode a first input number of signed input numbers represented in a first precision format as part of a machine learning model, the first input number re-encoded into two signed input numbers of a second precision format, wherein the first precision format is a higher precision format than the second precision format. The processor further includes a multiply-add circuit to perform operations in the first precision format using the two signed input numbers of the second precision format; and a sparsity hardware circuit to reduce computing on zero values at the multiply-add circuit, wherein the processor to execute the machine learning model using the re-encoder, the multiply-add circuit, and the sparsity hardware circuit.
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