Invention Grant
- Patent Title: Scalable multi-die deep learning system
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Application No.: US16517431Application Date: 2019-07-19
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Publication No.: US11769040B2Publication Date: 2023-09-26
- Inventor: Yakun Shao , Rangharajan Venkatesan , Nan Jiang , Brian Matthew Zimmer , Jason Clemons , Nathaniel Pinckney , Matthew R Fojtik , William James Dally , Joel S. Emer , Stephen W. Keckler , Brucek Khailany
- Applicant: NVIDIA Corp.
- Applicant Address: US CA Santa Clara
- Assignee: NVIDIA CORP.
- Current Assignee: NVIDIA CORP.
- Current Assignee Address: US CA Santa Clara
- Agency: Rowan TELS LLC
- Main IPC: G06F7/02
- IPC: G06F7/02 ; G06N3/049 ; G06F9/445 ; G06F9/54 ; G06N3/082

Abstract:
A distributed deep neural net (DNN) utilizing a distributed, tile-based architecture implemented on a semiconductor package. The package includes multiple chips, each with a central processing element, a global memory buffer, and processing elements. Each processing element includes a weight buffer, an activation buffer, and multiply-accumulate units to combine, in parallel, the weight values and the activation values.
Public/Granted literature
- US20200082246A1 SCALABLE MULTI-DIE DEEP LEARNING SYSTEM Public/Granted day:2020-03-12
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