Invention Grant
- Patent Title: Convolution acceleration with embedded vector decompression
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Application No.: US16909673Application Date: 2020-06-23
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Publication No.: US11531873B2Publication Date: 2022-12-20
- Inventor: Thomas Boesch , Giuseppe Desoli , Surinder Pal Singh , Carmine Cappetta
- Applicant: STMICROELECTRONICS S.r.l. , STMicroelectronics International N.V.
- Applicant Address: IT Agrate Brianza; CH Geneva
- Assignee: STMICROELECTRONICS S.r.l.,STMicroelectronics International N.V.
- Current Assignee: STMICROELECTRONICS S.r.l.,STMicroelectronics International N.V.
- Current Assignee Address: IT Agrate Brianza; CH Geneva
- Agency: Seed Intellectual Property Law Group LLP
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06F9/50 ; H03M7/30

Abstract:
Techniques and systems are provided for implementing a convolutional neural network. One or more convolution accelerators are provided that each include a feature line buffer memory, a kernel buffer memory, and a plurality of multiply-accumulate (MAC) circuits arranged to multiply and accumulate data. In a first operational mode the convolutional accelerator stores feature data in the feature line buffer memory and stores kernel data in the kernel data buffer memory. In a second mode of operation, the convolutional accelerator stores kernel decompression tables in the feature line buffer memory.
Public/Granted literature
- US20210397933A1 CONVOLUTION ACCELERATION WITH EMBEDDED VECTOR DECOMPRESSION Public/Granted day:2021-12-23
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