BR112023019150A2 - Técnica de compressão para ponderações de rede neural profunda - Google Patents

Técnica de compressão para ponderações de rede neural profunda

Info

Publication number
BR112023019150A2
BR112023019150A2 BR112023019150A BR112023019150A BR112023019150A2 BR 112023019150 A2 BR112023019150 A2 BR 112023019150A2 BR 112023019150 A BR112023019150 A BR 112023019150A BR 112023019150 A BR112023019150 A BR 112023019150A BR 112023019150 A2 BR112023019150 A2 BR 112023019150A2
Authority
BR
Brazil
Prior art keywords
weighting
frame
compressed
data
weighting data
Prior art date
Application number
BR112023019150A
Other languages
English (en)
Inventor
Haoping Xu
Narayana Macha Lakshmi
Prajakt Kulkarni
Original Assignee
Qualcomm Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Qualcomm Inc filed Critical Qualcomm Inc
Publication of BR112023019150A2 publication Critical patent/BR112023019150A2/pt

Links

Classifications

    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
    • H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
    • H03M7/70—Type of the data to be coded, other than image and sound
    • H03M7/702—Software
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0495—Quantised networks; Sparse networks; Compressed networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
    • H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
    • H03M7/46—Conversion to or from run-length codes, i.e. by representing the number of consecutive digits, or groups of digits, of the same kind by a code word and a digit indicative of that kind

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Evolutionary Computation (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Neurology (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

técnica de compressão para ponderações de rede neural profunda. várias modalidades incluem métodos e dispositivos para compressão e descompressão de conjuntos de dados de ponderação. algumas modalidades podem incluir compressão de dados de ponderação recebendo um conjunto de dados de ponderação de números binários que representam valores de ponderação, gerar uma carga útil de quadro incluindo um primeiro quadro comprimido de um primeiro subconjunto dos valores de ponderação no conjunto de dados de ponderação, e gerar um bloco de dados de ponderação comprimidos tendo a carga útil de quadro. algumas modalidades podem incluir descompressão de dados de ponderação recuperando um bloco de dados de ponderação comprimidos, em que o bloco de dados de ponderação comprimidos inclui um cabeçalho de quadro associado a uma carga útil de quadro, em que o cabeçalho de quadro inclui um indicador de fator de normalização, e em que a carga útil de quadro inclui valores de ponderação comprimidos, e gerar um primeiro quadro descomprimido compreendendo valores de ponderação descomprimidos dos valores de ponderação comprimidos da carga útil de quadro.
BR112023019150A 2021-04-01 2022-03-30 Técnica de compressão para ponderações de rede neural profunda BR112023019150A2 (pt)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US17/220,620 US11757469B2 (en) 2021-04-01 2021-04-01 Compression technique for deep neural network weights
PCT/US2022/022497 WO2022212467A1 (en) 2021-04-01 2022-03-30 Compression technique for deep neural network weights

Publications (1)

Publication Number Publication Date
BR112023019150A2 true BR112023019150A2 (pt) 2023-10-17

Family

ID=81308565

Family Applications (1)

Application Number Title Priority Date Filing Date
BR112023019150A BR112023019150A2 (pt) 2021-04-01 2022-03-30 Técnica de compressão para ponderações de rede neural profunda

Country Status (7)

Country Link
US (1) US11757469B2 (pt)
EP (1) EP4315175A1 (pt)
JP (1) JP2024514448A (pt)
KR (1) KR20230162778A (pt)
CN (1) CN117099109A (pt)
BR (1) BR112023019150A2 (pt)
WO (1) WO2022212467A1 (pt)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240162916A1 (en) * 2022-11-16 2024-05-16 Samsung Electronics Co., Ltd. Runtime reconfigurable compression format conversion

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101498063B1 (ko) * 2008-03-04 2015-03-03 엘지전자 주식회사 디지털 방송 시스템 및 데이터 처리 방법
US8489961B2 (en) * 2009-10-19 2013-07-16 Lg Electronics Inc. Transmitting system and method of processing digital broadcast signal in transmitting system, receiving system and method of receiving digital broadcast signal in receiving system
WO2012003602A1 (zh) * 2010-07-09 2012-01-12 西安交通大学 一种电子喉语音重建方法及其系统
WO2019216514A1 (en) 2018-05-09 2019-11-14 Samsung Electronics Co., Ltd. Electronic apparatus for compression and decompression of data and compression method thereof
US11625245B2 (en) * 2018-09-28 2023-04-11 Intel Corporation Compute-in-memory systems and methods
CN111178490B (zh) * 2019-12-31 2021-08-24 北京百度网讯科技有限公司 数据输出方法、获取方法、装置和电子设备
US11925128B2 (en) * 2020-08-26 2024-03-05 Robert Bosch Gmbh Differential ionic electronic transistors
US20220114454A1 (en) * 2020-10-08 2022-04-14 Samsung Electronics Co., Ltd. Electronic apparatus for decompressing a compressed artificial intelligence model and control method therefor

Also Published As

Publication number Publication date
KR20230162778A (ko) 2023-11-28
US11757469B2 (en) 2023-09-12
EP4315175A1 (en) 2024-02-07
CN117099109A (zh) 2023-11-21
WO2022212467A1 (en) 2022-10-06
US20220321143A1 (en) 2022-10-06
JP2024514448A (ja) 2024-04-02

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