- 专利标题: Fabric vectors for deep learning acceleration
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申请号: US16603184申请日: 2018-04-17
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公开(公告)号: US11232347B2公开(公告)日: 2022-01-25
- 发明人: Sean Lie , Michael Morrison , Michael Edwin James , Srikanth Arekapudi , Gary R. Lauterbach
- 申请人: Cerebras Systems Inc.
- 申请人地址: US CA Los Altos
- 专利权人: Cerebras Systems Inc.
- 当前专利权人: Cerebras Systems Inc.
- 当前专利权人地址: US CA Los Altos
- 代理机构: PatentVentures
- 代理商 Bennett Smith
- 国际申请: PCT/IB2018/052667 WO 20180417
- 国际公布: WO2018/193380 WO 20181025
- 主分类号: G06F9/30
- IPC分类号: G06F9/30 ; G06N3/04 ; G06F5/06 ; G06N3/063 ; G06F13/00 ; G06N3/08 ; H04L12/935 ; G06F9/38 ; H04L12/54 ; G06F13/40 ; H04L12/931 ; G06F30/392
摘要:
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 respective compute element and a respective routing element. Instructions executed by the compute element include operand specifiers, some specifying a data structure register storing a data structure descriptor describing an operand as a fabric vector or a memory vector. The data structure descriptor further describes various attributes of the fabric vector: length, microthreading eligibility, number of data elements to receive, transmit, and/or process in parallel, virtual channel and task identification information, whether to terminate upon receiving a control wavelet, and whether to mark an outgoing wavelet a control wavelet.
公开/授权文献
- US20200380341A1 Fabric Vectors for Deep Learning Acceleration 公开/授权日:2020-12-03
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