Invention Grant
- Patent Title: Control wavelet for accelerated deep learning
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Application No.: US16090049Application Date: 2018-04-17
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Publication No.: US10762418B2Publication Date: 2020-09-01
- Inventor: Sean Lie , Gary R. Lauterbach , Michael Edwin James , Michael Morrison , Srikanth Arekapudi
- Applicant: Cerebras Systems Inc.
- Applicant Address: US CA Los Altos
- Assignee: Cerebras Systems Inc.
- Current Assignee: Cerebras Systems Inc.
- Current Assignee Address: US CA Los Altos
- Agency: PatentVentures
- Agent Bennett Smith; Korbin Van Dyke
- International Application: PCT/IB2018/052664 WO 20180417
- International Announcement: WO2018/193377 WO 20181025
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06N3/04 ; G06F13/00 ; G06N3/08 ; G06F9/30 ; H04L12/935 ; G06F9/38 ; H04L12/54 ; H04L12/931

Abstract:
Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements performs flow based computations on wavelets of data. Each processing element has a compute element and a routing element. Each compute element has memory. Each router enables communication via wavelets with nearest neighbors in a 2D mesh. A compute element receives a wavelet. If a control specifier of the wavelet is a first value, then instructions are read from the memory of the compute element in accordance with an index specifier of the wavelet. If the control specifier is a second value, then instructions are read from the memory of the compute element in accordance with a virtual channel specifier of the wavelet. Then the compute element initiates execution of the instructions.
Public/Granted literature
- US20190258921A1 CONTROL WAVELET FOR ACCELERATED DEEP LEARNING Public/Granted day:2019-08-22
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