IL307304A - Pipeline operation in neural networks - Google Patents
Pipeline operation in neural networksInfo
- 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
Links
- 238000013528 artificial neural network Methods 0.000 title 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/38—Concurrent instruction execution, e.g. pipeline or look ahead
- G06F9/3867—Concurrent instruction execution, e.g. pipeline or look ahead using instruction pipelines
- G06F9/3875—Pipelining a single stage, e.g. superpipelining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
- G06F17/153—Multidimensional correlation or convolution
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
- G06F7/38—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation
- G06F7/48—Methods 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
- G06F7/52—Multiplying; Dividing
- G06F7/523—Multiplying only
- G06F7/53—Multiplying only in parallel-parallel fashion, i.e. both operands being entered in parallel
-
- 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
- G06N3/0464—Convolutional networks [CNN, ConvNet]
-
- 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
-
- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy 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)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (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)
- Artificial Intelligence (AREA)
- Computational Linguistics (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Databases & Information Systems (AREA)
- Neurology (AREA)
- Algebra (AREA)
- Complex Calculations (AREA)
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 | Pipeline operation in neural networks |
Country Status (5)
Country | Link |
---|---|
EP (1) | EP4323864A1 (ko) |
JP (1) | JP2024514659A (ko) |
KR (1) | KR20240024782A (ko) |
IL (1) | IL307304A (ko) |
WO (1) | WO2022221092A1 (ko) |
Family Cites Families (4)
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 |
US10528864B2 (en) * | 2016-08-11 | 2020-01-07 | Nvidia Corporation | Sparse convolutional neural network accelerator |
US10410098B2 (en) * | 2017-04-24 | 2019-09-10 | Intel Corporation | Compute optimizations for neural networks |
KR102637735B1 (ko) * | 2018-01-09 | 2024-02-19 | 삼성전자주식회사 | 근사 곱셈기를 구비하는 뉴럴 네트워크 처리 장치 및 이를 포함하는 시스템온 칩 |
-
2022
- 2022-04-05 EP EP22788657.9A patent/EP4323864A1/en active Pending
- 2022-04-05 KR KR1020237039259A patent/KR20240024782A/ko active Search and Examination
- 2022-04-05 JP JP2023563294A patent/JP2024514659A/ja active Pending
- 2022-04-05 WO PCT/US2022/023434 patent/WO2022221092A1/en active Application Filing
- 2022-04-05 IL IL307304A patent/IL307304A/en unknown
Also Published As
Publication number | Publication date |
---|---|
EP4323864A1 (en) | 2024-02-21 |
KR20240024782A (ko) | 2024-02-26 |
WO2022221092A1 (en) | 2022-10-20 |
JP2024514659A (ja) | 2024-04-02 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
GB2600356B (en) | Performing matrix operations in neural networks | |
SG11202002468RA (en) | Processing data elements stored in blockchain networks | |
GB2590482B (en) | Fault detection in neural networks | |
GB201812150D0 (en) | Processing method using binary intermediate representations | |
ZA202301872B (en) | Improvements in pipeline networks | |
IL307304A (en) | Pipeline operation in neural networks | |
GB2568230B (en) | Processing in neural networks | |
GB2577732B (en) | Processing data in a convolutional neural network | |
GB202107304D0 (en) | Verifying neural networks | |
GB202019034D0 (en) | Verifying Neural Networks | |
GB201716570D0 (en) | Identifying interfering links in local area networks | |
GB202100936D0 (en) | Another just in case | |
GB202117398D0 (en) | Just in case | |
GB202115693D0 (en) | Just in case | |
GB202114167D0 (en) | Just in case | |
GB202112429D0 (en) | Just in case | |
GB202109841D0 (en) | Just in case | |
GB202105541D0 (en) | Just in case | |
GB202104400D0 (en) | Just in case | |
GB202103345D0 (en) | Just in case | |
GB2611751B (en) | Neural network processing | |
GB202102274D0 (en) | Just in case | |
GB202102066D0 (en) | Just in case | |
GB202306610D0 (en) | Just in case | |
GB202304964D0 (en) | Just in case |