GB2568102B - Exploiting sparsity in a neural network - Google Patents
Exploiting sparsity in a neural network Download PDFInfo
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- GB2568102B GB2568102B GB1718358.3A GB201718358A GB2568102B GB 2568102 B GB2568102 B GB 2568102B GB 201718358 A GB201718358 A GB 201718358A GB 2568102 B GB2568102 B GB 2568102B
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- neural network
- exploiting sparsity
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- 238000013528 artificial neural network Methods 0.000 title 1
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- 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
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- 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
- G06N3/045—Combinations of networks
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- 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
- G06N3/048—Activation functions
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- 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
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
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- Biophysics (AREA)
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- Evolutionary Computation (AREA)
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- General Engineering & Computer Science (AREA)
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Priority Applications (19)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
GB1718358.3A GB2568102B (en) | 2017-11-06 | 2017-11-06 | Exploiting sparsity in a neural network |
US16/182,471 US11182668B2 (en) | 2017-11-06 | 2018-11-06 | Neural network architecture using convolution engine filter weight buffers |
CN201811315075.3A CN110020716B (en) | 2017-11-06 | 2018-11-06 | Neural network hardware |
US16/181,559 US11574171B2 (en) | 2017-11-06 | 2018-11-06 | Neural network architecture using convolution engines |
CN201811314394.2A CN110033080B (en) | 2017-11-06 | 2018-11-06 | Single plane filtering |
GB1818109.9A GB2570187B (en) | 2017-11-06 | 2018-11-06 | Single plane filters |
EP18204739.9A EP3480747A1 (en) | 2017-11-06 | 2018-11-06 | Single plane filters |
CN201811311595.7A CN110059798B (en) | 2017-11-06 | 2018-11-06 | Exploiting sparsity in neural networks |
US16/182,369 US11551065B2 (en) | 2017-11-06 | 2018-11-06 | Neural network architecture using control logic determining convolution operation sequence |
GB1818103.2A GB2570186B (en) | 2017-11-06 | 2018-11-06 | Weight buffers |
EP18204740.7A EP3480748A1 (en) | 2017-11-06 | 2018-11-06 | Neural network hardware |
CN201811314022.XA CN110059811B (en) | 2017-11-06 | 2018-11-06 | Weight buffer |
EP18204741.5A EP3480749B1 (en) | 2017-11-06 | 2018-11-06 | Exploiting sparsity in a neural network |
EP18204733.2A EP3480746A1 (en) | 2017-11-06 | 2018-11-06 | Weight buffers |
US16/182,426 US11610099B2 (en) | 2017-11-06 | 2018-11-06 | Neural network architecture using single plane filters |
US17/511,363 US11803738B2 (en) | 2017-11-06 | 2021-10-26 | Neural network architecture using convolution engine filter weight buffers |
US18/093,768 US11907830B2 (en) | 2017-11-06 | 2023-01-05 | Neural network architecture using control logic determining convolution operation sequence |
US18/104,749 US12050986B2 (en) | 2017-11-06 | 2023-02-01 | Neural network architecture using convolution engines |
US18/119,590 US20230214631A1 (en) | 2017-11-06 | 2023-03-09 | Neural Network Architecture Using Single Plane Filters |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
GB1718358.3A GB2568102B (en) | 2017-11-06 | 2017-11-06 | Exploiting sparsity in a neural network |
Publications (3)
Publication Number | Publication Date |
---|---|
GB201718358D0 GB201718358D0 (en) | 2017-12-20 |
GB2568102A GB2568102A (en) | 2019-05-08 |
GB2568102B true GB2568102B (en) | 2021-04-14 |
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Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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GB1718358.3A Active GB2568102B (en) | 2017-11-06 | 2017-11-06 | Exploiting sparsity in a neural network |
Country Status (1)
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GB (1) | GB2568102B (en) |
Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110059811B (en) | 2017-11-06 | 2024-08-02 | 畅想科技有限公司 | Weight buffer |
EP3750113A1 (en) * | 2018-02-09 | 2020-12-16 | DeepMind Technologies Limited | Contiguous sparsity pattern neural networks |
US11501141B2 (en) * | 2018-10-12 | 2022-11-15 | Western Digital Technologies, Inc. | Shifting architecture for data reuse in a neural network |
US20220004856A1 (en) * | 2018-11-06 | 2022-01-06 | Genesys Logic, Inc. | Multichip system and data processing method adapted to the same for implementing neural network application |
WO2020160653A1 (en) * | 2019-02-06 | 2020-08-13 | Lei Zhang | Method and system for convolution model hardware accelerator |
CN111144558B (en) * | 2020-04-03 | 2020-08-18 | 深圳市九天睿芯科技有限公司 | Multi-bit convolution operation module based on time-variable current integration and charge sharing |
CN111626405B (en) * | 2020-05-15 | 2024-05-07 | Tcl华星光电技术有限公司 | CNN acceleration method, acceleration device and computer readable storage medium |
CN116261736B (en) * | 2020-06-12 | 2024-08-16 | 墨芯国际有限公司 | Method and system for double sparse convolution processing and parallelization |
FR3117645B1 (en) * | 2020-12-16 | 2023-08-25 | Commissariat Energie Atomique | Taking advantage of low data density or non-zero weights in a weighted sum calculator |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170316312A1 (en) * | 2016-05-02 | 2017-11-02 | Cavium, Inc. | Systems and methods for deep learning processor |
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2017
- 2017-11-06 GB GB1718358.3A patent/GB2568102B/en active Active
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170316312A1 (en) * | 2016-05-02 | 2017-11-02 | Cavium, Inc. | Systems and methods for deep learning processor |
Non-Patent Citations (3)
Title |
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Angshuman Parashar Et Al. : "An Accelerator for Compressed-sparse Convolutional Neural Networks", 23 May 2017, pages 1-12, XP055569818 * |
SONG HAN ; XINGYU LIU ; HUIZI MAO ; JING PU ; ARDAVAN PEDRAM ; MARK A. HOROWITZ ; WILLIAM J. DALLY: "EIE", ACM SIGARCH COMPUTER ARCHITECTURE NEWS, ACM SPECIAL INTEREST GROUP ON COMPUTER ARCHITECTURE, 2 PENN PLAZA, SUITE 701 NEW YORK NY 10121-0701 USA, vol. 44, no. 3, 18 June 2016 (2016-06-18), 2 Penn Plaza, Suite 701 New York NY 10121-0701 USA, pages 243 - 254, XP058300624, ISSN: 0163-5964, DOI: 10.1145/3007787.3001163 * |
ZHANG SHIJIN; DU ZIDONG; ZHANG LEI; LAN HUIYING; LIU SHAOLI; LI LING; GUO QI; CHEN TIANSHI; CHEN YUNJI: "Cambricon-X: An accelerator for sparse neural networks", 2016 49TH ANNUAL IEEE/ACM INTERNATIONAL SYMPOSIUM ON MICROARCHITECTURE (MICRO), IEEE, 15 October 2016 (2016-10-15), pages 1 - 12, XP033022466, DOI: 10.1109/MICRO.2016.7783723 * |
Also Published As
Publication number | Publication date |
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GB201718358D0 (en) | 2017-12-20 |
GB2568102A (en) | 2019-05-08 |
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732E | Amendments to the register in respect of changes of name or changes affecting rights (sect. 32/1977) |
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