IL307304A - Pipelined operations in neural networks - Google Patents

Pipelined operations in neural networks

Info

Publication number
IL307304A
IL307304A IL307304A IL30730423A IL307304A IL 307304 A IL307304 A IL 307304A IL 307304 A IL307304 A IL 307304A IL 30730423 A IL30730423 A IL 30730423A IL 307304 A IL307304 A IL 307304A
Authority
IL
Israel
Prior art keywords
neural networks
pipelined operations
pipelined
operations
neural
Prior art date
Application number
IL307304A
Other languages
Hebrew (he)
Inventor
Mark Ashley Mathews
Original Assignee
Gigantor Tech Inc
Mark Ashley Mathews
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
Priority claimed from US17/231,711 external-priority patent/US11099854B1/en
Application filed by Gigantor Tech Inc, Mark Ashley Mathews filed Critical Gigantor Tech Inc
Publication of IL307304A publication Critical patent/IL307304A/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/30Arrangements for executing machine instructions, e.g. instruction decode
    • G06F9/38Concurrent instruction execution, e.g. pipeline or look ahead
    • G06F9/3867Concurrent instruction execution, e.g. pipeline or look ahead using instruction pipelines
    • G06F9/3875Pipelining a single stage, e.g. superpipelining
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/15Correlation function computation including computation of convolution operations
    • G06F17/153Multidimensional correlation or convolution
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • G06F7/38Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation
    • G06F7/48Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices
    • G06F7/52Multiplying; Dividing
    • G06F7/523Multiplying only
    • G06F7/53Multiplying only in parallel-parallel fashion, i.e. both operands being entered in parallel
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0464Convolutional networks [CNN, ConvNet]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00Energy efficient computing, e.g. low power processors, power management or thermal management

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Pure & Applied Mathematics (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Data Mining & Analysis (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computational Linguistics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Databases & Information Systems (AREA)
  • Algebra (AREA)
  • Neurology (AREA)
  • Complex Calculations (AREA)
IL307304A 2021-04-15 2022-04-05 Pipelined operations in neural networks IL307304A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US17/231,711 US11099854B1 (en) 2020-10-15 2021-04-15 Pipelined operations in neural networks
PCT/US2022/023434 WO2022221092A1 (en) 2021-04-15 2022-04-05 Pipelined operations in neural networks

Publications (1)

Publication Number Publication Date
IL307304A true IL307304A (en) 2023-11-01

Family

ID=83640568

Family Applications (1)

Application Number Title Priority Date Filing Date
IL307304A IL307304A (en) 2021-04-15 2022-04-05 Pipelined operations in neural networks

Country Status (5)

Country Link
EP (1) EP4323864A1 (en)
JP (1) JP2024514659A (en)
KR (1) KR20240024782A (en)
IL (1) IL307304A (en)
WO (1) WO2022221092A1 (en)

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160328645A1 (en) * 2015-05-08 2016-11-10 Qualcomm Incorporated Reduced computational complexity for fixed point neural network
US10997496B2 (en) * 2016-08-11 2021-05-04 Nvidia Corporation Sparse convolutional neural network accelerator
US10410098B2 (en) * 2017-04-24 2019-09-10 Intel Corporation Compute optimizations for neural networks
KR102637735B1 (en) * 2018-01-09 2024-02-19 삼성전자주식회사 Neural network processing unit including approximate multiplier and system on chip including the same

Also Published As

Publication number Publication date
EP4323864A1 (en) 2024-02-21
KR20240024782A (en) 2024-02-26
JP2024514659A (en) 2024-04-02
WO2022221092A1 (en) 2022-10-20

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