SG10201804284XA - Performing Kernel Striding In Hardware - Google Patents
Performing Kernel Striding In HardwareInfo
- Publication number
- SG10201804284XA SG10201804284XA SG10201804284XA SG10201804284XA SG10201804284XA SG 10201804284X A SG10201804284X A SG 10201804284XA SG 10201804284X A SG10201804284X A SG 10201804284XA SG 10201804284X A SG10201804284X A SG 10201804284XA SG 10201804284X A SG10201804284X A SG 10201804284XA
- Authority
- SG
- Singapore
- Prior art keywords
- tensor
- neural network
- convolutional neural
- network layer
- generate
- Prior art date
Links
Classifications
-
- 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
-
- 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
-
- 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
-
- 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
Abstract
PERFORMING KERNEL STRIDING IN HARDWARE Methods for receiving a request to process, on a hardware circuit, a neural network comprising a first convolutional neural network layer having a stride greater than one, and in response, generating instructions that cause the hardware circuit to, during processing of an input tensor, generate a layer output tensor equivalent to an output of the first convolutional neural network layer by processing the input tensor using a second convolutional neural network layer having a stride equal to one but that is otherwise equivalent to the first convolutional neural network layer to generate a first tensor, zeroing out elements of the first tensor that would not have been generated if the second convolutional neural network layer had the stride of the first convolutional neural network layer to generate a second tensor, and performing max pooling on the second tensor to generate the layer output tensor. Fig. 9
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US15/348,199 US10733505B2 (en) | 2016-11-10 | 2016-11-10 | Performing kernel striding in hardware |
US15/467,382 US9721203B1 (en) | 2016-11-10 | 2017-03-23 | Performing kernel striding in hardware |
Publications (1)
Publication Number | Publication Date |
---|---|
SG10201804284XA true SG10201804284XA (en) | 2018-07-30 |
Family
ID=59382805
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
SG10201804284XA SG10201804284XA (en) | 2016-11-10 | 2017-09-18 | Performing Kernel Striding In Hardware |
SG10201707700WA SG10201707700WA (en) | 2016-11-10 | 2017-09-18 | Performing Kernel Striding In Hardware |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
SG10201707700WA SG10201707700WA (en) | 2016-11-10 | 2017-09-18 | Performing Kernel Striding In Hardware |
Country Status (11)
Country | Link |
---|---|
US (3) | US10733505B2 (en) |
EP (2) | EP4336411A3 (en) |
JP (2) | JP6987860B2 (en) |
KR (2) | KR102512936B1 (en) |
CN (2) | CN114897132A (en) |
DE (2) | DE202017105729U1 (en) |
GB (2) | GB2556670B (en) |
HK (1) | HK1254699A1 (en) |
IE (1) | IE20170205A1 (en) |
SG (2) | SG10201804284XA (en) |
WO (1) | WO2018089079A1 (en) |
Families Citing this family (55)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9959498B1 (en) | 2016-10-27 | 2018-05-01 | Google Llc | Neural network instruction set architecture |
US10360163B2 (en) | 2016-10-27 | 2019-07-23 | Google Llc | Exploiting input data sparsity in neural network compute units |
US10175980B2 (en) | 2016-10-27 | 2019-01-08 | Google Llc | Neural network compute tile |
US10733505B2 (en) * | 2016-11-10 | 2020-08-04 | Google Llc | Performing kernel striding in hardware |
TWI634490B (en) * | 2016-11-14 | 2018-09-01 | 美商耐能股份有限公司 | Convolution operation device and convolution operation method |
US10198401B2 (en) * | 2016-12-30 | 2019-02-05 | Intel Corporation | Max pooling in a matrix processing architecture |
TWI607389B (en) * | 2017-02-10 | 2017-12-01 | 耐能股份有限公司 | Pooling operation device and method for convolutional neural network |
US10346944B2 (en) | 2017-04-09 | 2019-07-09 | Intel Corporation | Machine learning sparse computation mechanism |
US10643297B2 (en) * | 2017-05-05 | 2020-05-05 | Intel Corporation | Dynamic precision management for integer deep learning primitives |
DE102018110687A1 (en) | 2017-05-05 | 2018-11-08 | Intel Corporation | Dynamic accuracy management for deep learning integer primitives |
KR102442055B1 (en) * | 2017-09-26 | 2022-09-13 | 삼성전자주식회사 | Electronic apparatus and control method thereof |
CN110020716A (en) | 2017-11-06 | 2019-07-16 | 畅想科技有限公司 | Neural network hardware |
CN108108811B (en) * | 2017-12-18 | 2021-07-30 | 南京地平线机器人技术有限公司 | Convolution calculation method in neural network and electronic device |
CN108133270B (en) * | 2018-01-12 | 2020-08-04 | 清华大学 | Convolutional neural network acceleration method and device |
US11164074B2 (en) | 2018-02-08 | 2021-11-02 | Western Digital Technologies, Inc. | Multi-core systolic processor system for neural network processing |
US11461579B2 (en) | 2018-02-08 | 2022-10-04 | Western Digital Technologies, Inc. | Configurable neural network engine for convolutional filter sizes |
JP7108702B2 (en) * | 2018-03-22 | 2022-07-28 | アマゾン テクノロジーズ インコーポレイテッド | Processing for multiple input datasets |
US10621489B2 (en) | 2018-03-30 | 2020-04-14 | International Business Machines Corporation | Massively parallel neural inference computing elements |
US20190332925A1 (en) * | 2018-04-30 | 2019-10-31 | International Business Machines Corporation | Neural hardware accelerator for parallel and distributed tensor computations |
US11783174B2 (en) | 2018-05-04 | 2023-10-10 | Apple Inc. | Splitting of input data for processing in neural network processor |
CN108764182B (en) * | 2018-06-01 | 2020-12-08 | 阿依瓦(北京)技术有限公司 | Optimized acceleration method and device for artificial intelligence |
US20190392287A1 (en) * | 2018-06-22 | 2019-12-26 | Samsung Electronics Co., Ltd. | Neural processor |
CN109036460B (en) * | 2018-08-28 | 2020-01-07 | 百度在线网络技术(北京)有限公司 | Voice processing method and device based on multi-model neural network |
CN109190758B (en) * | 2018-09-04 | 2021-06-15 | 地平线(上海)人工智能技术有限公司 | Method and apparatus for unwrapping tensor data for convolutional neural networks |
WO2020062252A1 (en) * | 2018-09-30 | 2020-04-02 | 华为技术有限公司 | Operational accelerator and compression method |
CN110969247B (en) * | 2018-09-30 | 2024-04-09 | 北京地平线信息技术有限公司 | Tensor processing method and device based on neural network and electronic equipment |
CN109376843B (en) * | 2018-10-12 | 2021-01-08 | 山东师范大学 | FPGA-based electroencephalogram signal rapid classification method, implementation method and device |
US11636325B2 (en) | 2018-10-24 | 2023-04-25 | Macronix International Co., Ltd. | In-memory data pooling for machine learning |
JP7315317B2 (en) | 2018-11-09 | 2023-07-26 | 株式会社Preferred Networks | Processors and how they transfer data |
US11301546B2 (en) * | 2018-11-19 | 2022-04-12 | Groq, Inc. | Spatial locality transform of matrices |
US11562229B2 (en) * | 2018-11-30 | 2023-01-24 | Macronix International Co., Ltd. | Convolution accelerator using in-memory computation |
US11934480B2 (en) | 2018-12-18 | 2024-03-19 | Macronix International Co., Ltd. | NAND block architecture for in-memory multiply-and-accumulate operations |
US20200202198A1 (en) * | 2018-12-21 | 2020-06-25 | Waymo Llc | Neural network processor |
CN109919321A (en) * | 2019-02-01 | 2019-06-21 | 京微齐力(北京)科技有限公司 | Unit has the artificial intelligence module and System on Chip/SoC of local accumulation function |
US11783176B2 (en) | 2019-03-25 | 2023-10-10 | Western Digital Technologies, Inc. | Enhanced storage device memory architecture for machine learning |
US10929058B2 (en) | 2019-03-25 | 2021-02-23 | Western Digital Technologies, Inc. | Enhanced memory device architecture for machine learning |
US20200311543A1 (en) * | 2019-03-30 | 2020-10-01 | Microsoft Technology Licensing, Llc | Embedded learning for response prediction in content item relevance |
US11671111B2 (en) | 2019-04-17 | 2023-06-06 | Samsung Electronics Co., Ltd. | Hardware channel-parallel data compression/decompression |
CN110135580B (en) * | 2019-04-26 | 2021-03-26 | 华中科技大学 | Convolution network full integer quantization method and application method thereof |
US11880760B2 (en) | 2019-05-01 | 2024-01-23 | Samsung Electronics Co., Ltd. | Mixed-precision NPU tile with depth-wise convolution |
KR102373802B1 (en) * | 2019-06-12 | 2022-03-16 | 주식회사 사피온코리아 | Neural network accelerator for neural network computing efficiency and operation method thereof |
US11449739B2 (en) * | 2019-08-22 | 2022-09-20 | Google Llc | General padding support for convolution on systolic arrays |
TWI774067B (en) * | 2019-10-18 | 2022-08-11 | 旺宏電子股份有限公司 | Memory device and computing in memory method thereof |
JP7462140B2 (en) | 2019-10-29 | 2024-04-05 | 国立大学法人 熊本大学 | Neural network circuit and neural network operation method |
CN110852424B (en) * | 2019-11-15 | 2023-07-25 | 广东工业大学 | Processing method and device for countermeasure generation network |
JP7298713B2 (en) | 2019-12-06 | 2023-06-27 | 日本電気株式会社 | Parameter optimization device, parameter optimization method, and parameter optimization program |
CN111027683A (en) * | 2019-12-09 | 2020-04-17 | Oppo广东移动通信有限公司 | Data processing method, data processing device, storage medium and electronic equipment |
US11604975B2 (en) | 2020-04-09 | 2023-03-14 | Apple Inc. | Ternary mode of planar engine for neural processor |
US11507817B2 (en) | 2020-04-17 | 2022-11-22 | Samsung Electronics Co., Ltd. | System and method for performing computations for deep neural networks |
US11488066B2 (en) * | 2020-04-21 | 2022-11-01 | SiMa Technologies, Inc. | Efficient convolution of multi-channel input samples with multiple kernels |
JP6931252B1 (en) * | 2020-08-07 | 2021-09-01 | LeapMind株式会社 | Neural network circuit and neural network circuit control method |
KR102430837B1 (en) * | 2020-08-24 | 2022-08-09 | 울산과학기술원 | Method of dividing plurality of layers included in machine learning model and determining processor that performs divided layers, and device performing method |
CN112070067B (en) * | 2020-10-12 | 2023-11-21 | 乐普(北京)医疗器械股份有限公司 | Scatter diagram classification method and device for photoplethysmograph signals |
JP7413249B2 (en) | 2020-12-25 | 2024-01-15 | 日立Astemo株式会社 | Information processing device, information processing method |
KR102361249B1 (en) * | 2021-08-02 | 2022-02-14 | 오픈엣지테크놀로지 주식회사 | Method for optimizing broadcast multiply and a hardware accelerator and computing device using the same |
Family Cites Families (31)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6505224B1 (en) | 1999-09-29 | 2003-01-07 | Sun Microsystems, Inc. | System and computer-implemented method for performing multi-stage fast Walsh transform |
US7107304B2 (en) | 2001-11-30 | 2006-09-12 | Apple Computer, Inc. | Single-channel convolution in a vector processing computer system |
US7653675B2 (en) | 2005-08-08 | 2010-01-26 | Freescale Semiconductor, Inc. | Convolution operation in a multi-mode wireless processing system |
JP5075861B2 (en) | 2009-03-16 | 2012-11-21 | 株式会社東芝 | Image processing apparatus and image processing method |
US8583896B2 (en) * | 2009-11-13 | 2013-11-12 | Nec Laboratories America, Inc. | Massively parallel processing core with plural chains of processing elements and respective smart memory storing select data received from each chain |
US8458635B2 (en) | 2009-12-04 | 2013-06-04 | Synopsys, Inc. | Convolution computation for many-core processor architectures |
US9811775B2 (en) | 2012-12-24 | 2017-11-07 | Google Inc. | Parallelizing neural networks during training |
US9858220B2 (en) * | 2014-03-17 | 2018-01-02 | Purdue Research Foundation | Computing architecture with concurrent programmable data co-processor |
IL231862A (en) * | 2014-04-01 | 2015-04-30 | Superfish Ltd | Neural network image representation |
US20150311050A1 (en) * | 2014-04-28 | 2015-10-29 | Thermo Finnigan Llc | Method for Determining a Spectrum from Time-Varying Data |
CN104035751B (en) * | 2014-06-20 | 2016-10-12 | 深圳市腾讯计算机系统有限公司 | Data parallel processing method based on multi-graphics processor and device |
US20160026912A1 (en) * | 2014-07-22 | 2016-01-28 | Intel Corporation | Weight-shifting mechanism for convolutional neural networks |
FR3025344B1 (en) * | 2014-08-28 | 2017-11-24 | Commissariat Energie Atomique | NETWORK OF CONVOLUTIONAL NEURONS |
US10223333B2 (en) | 2014-08-29 | 2019-03-05 | Nvidia Corporation | Performing multi-convolution operations in a parallel processing system |
EP3035204B1 (en) | 2014-12-19 | 2018-08-15 | Intel Corporation | Storage device and method for performing convolution operations |
US9418458B2 (en) | 2015-01-05 | 2016-08-16 | Superfish Ltd. | Graph image representation from convolutional neural networks |
JP6360802B2 (en) * | 2015-02-20 | 2018-07-18 | 株式会社デンソーアイティーラボラトリ | Neural network processing device, neural network processing method, detection device, detection method, and vehicle |
US10762894B2 (en) * | 2015-03-27 | 2020-09-01 | Google Llc | Convolutional neural networks |
CN104915322B (en) * | 2015-06-09 | 2018-05-01 | 中国人民解放军国防科学技术大学 | A kind of hardware-accelerated method of convolutional neural networks |
US9734567B2 (en) * | 2015-06-24 | 2017-08-15 | Samsung Electronics Co., Ltd. | Label-free non-reference image quality assessment via deep neural network |
CN105488565A (en) * | 2015-11-17 | 2016-04-13 | 中国科学院计算技术研究所 | Calculation apparatus and method for accelerator chip accelerating deep neural network algorithm |
CN105426517B (en) * | 2015-12-02 | 2020-02-18 | 上海越峰信息科技有限公司 | Intelligent storage device with image processing function |
CN105589938A (en) * | 2015-12-13 | 2016-05-18 | 公安部第三研究所 | Image retrieval system and retrieval method based on FPGA |
US10460231B2 (en) * | 2015-12-29 | 2019-10-29 | Samsung Electronics Co., Ltd. | Method and apparatus of neural network based image signal processor |
CN105681628B (en) * | 2016-01-05 | 2018-12-07 | 西安交通大学 | A kind of convolutional network arithmetic element and restructural convolutional neural networks processor and the method for realizing image denoising processing |
CN105678379B (en) * | 2016-01-12 | 2020-08-07 | 腾讯科技(深圳)有限公司 | CNN processing method and device |
CN205621018U (en) * | 2016-02-26 | 2016-10-05 | 陈进民 | Cell -phone cell convolutional neural network accelerator |
US10706348B2 (en) | 2016-07-13 | 2020-07-07 | Google Llc | Superpixel methods for convolutional neural networks |
US10402697B2 (en) * | 2016-08-01 | 2019-09-03 | Nvidia Corporation | Fusing multilayer and multimodal deep neural networks for video classification |
US9779786B1 (en) * | 2016-10-26 | 2017-10-03 | Xilinx, Inc. | Tensor operations and acceleration |
US10733505B2 (en) * | 2016-11-10 | 2020-08-04 | Google Llc | Performing kernel striding in hardware |
-
2016
- 2016-11-10 US US15/348,199 patent/US10733505B2/en active Active
-
2017
- 2017-03-23 US US15/467,382 patent/US9721203B1/en active Active
- 2017-08-23 WO PCT/US2017/048123 patent/WO2018089079A1/en active Search and Examination
- 2017-08-23 KR KR1020227011437A patent/KR102512936B1/en active IP Right Grant
- 2017-08-23 EP EP24153561.6A patent/EP4336411A3/en active Pending
- 2017-08-23 EP EP17761170.4A patent/EP3539059B1/en active Active
- 2017-08-23 JP JP2019524156A patent/JP6987860B2/en active Active
- 2017-08-23 KR KR1020197016416A patent/KR102385843B1/en active IP Right Grant
- 2017-09-18 SG SG10201804284XA patent/SG10201804284XA/en unknown
- 2017-09-18 SG SG10201707700WA patent/SG10201707700WA/en unknown
- 2017-09-21 DE DE202017105729.1U patent/DE202017105729U1/en active Active
- 2017-09-21 DE DE102017121887.4A patent/DE102017121887A1/en active Pending
- 2017-09-22 GB GB1715309.9A patent/GB2556670B/en active Active
- 2017-09-22 GB GB2008121.2A patent/GB2583594B/en active Active
- 2017-09-28 IE IE20170205A patent/IE20170205A1/en unknown
- 2017-09-29 CN CN202210408223.6A patent/CN114897132A/en active Pending
- 2017-09-29 CN CN201710909648.4A patent/CN108073983B/en active Active
-
2018
- 2018-10-25 HK HK18113684.4A patent/HK1254699A1/en unknown
-
2020
- 2020-07-06 US US16/921,436 patent/US11816532B2/en active Active
-
2021
- 2021-12-01 JP JP2021195320A patent/JP7394104B2/en active Active
Also Published As
Publication number | Publication date |
---|---|
EP3539059B1 (en) | 2024-02-28 |
JP7394104B2 (en) | 2023-12-07 |
KR20220047680A (en) | 2022-04-18 |
US20180129936A1 (en) | 2018-05-10 |
US10733505B2 (en) | 2020-08-04 |
WO2018089079A1 (en) | 2018-05-17 |
GB201715309D0 (en) | 2017-11-08 |
DE202017105729U1 (en) | 2018-01-03 |
GB2556670A (en) | 2018-06-06 |
GB2583594A (en) | 2020-11-04 |
US11816532B2 (en) | 2023-11-14 |
JP2022037022A (en) | 2022-03-08 |
US9721203B1 (en) | 2017-08-01 |
GB2583594B (en) | 2021-07-28 |
DE102017121887A1 (en) | 2018-05-17 |
JP2019537139A (en) | 2019-12-19 |
HK1254699A1 (en) | 2019-07-26 |
SG10201707700WA (en) | 2018-06-28 |
EP4336411A2 (en) | 2024-03-13 |
CN108073983A (en) | 2018-05-25 |
EP4336411A3 (en) | 2024-04-24 |
EP3539059A1 (en) | 2019-09-18 |
KR102512936B1 (en) | 2023-03-21 |
CN114897132A (en) | 2022-08-12 |
JP6987860B2 (en) | 2022-01-05 |
GB202008121D0 (en) | 2020-07-15 |
KR20190084088A (en) | 2019-07-15 |
KR102385843B1 (en) | 2022-04-11 |
CN108073983B (en) | 2022-04-26 |
IE20170205A1 (en) | 2018-05-16 |
US20200334536A1 (en) | 2020-10-22 |
GB2556670B (en) | 2020-07-15 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
SG10201707700WA (en) | Performing Kernel Striding In Hardware | |
SG10201707701PA (en) | Performing Average Pooling In Hardware | |
WO2019046317A8 (en) | Key data processing method and apparatus, and server | |
PH12019500771A1 (en) | Business processing method and apparatus | |
BR112019000541A2 (en) | superpixel methods for convolutional neural networks | |
MX2017009879A (en) | Batch normalization layers. | |
EP4235462A3 (en) | Depth concatenation using a matrix computation unit | |
MY190598A (en) | Blockchain data processing method and apparatus | |
KR20180084289A (en) | Compressed neural network system using sparse parameter and design method thereof | |
MX2020000952A (en) | Accelerated mathematical engine. | |
SG11201806674TA (en) | Electronic payment service processing method and device, and electronic payment method and device | |
MY188759A (en) | Cnn processing method and device | |
EP4235449A3 (en) | Batch processing in a neural network processor | |
EP4283526A3 (en) | Dynamic task allocation for neural networks | |
GB2555365A (en) | Seismic constrained discrete fracture network | |
MX2017015844A (en) | System and method for the generation of an adaptive user interface in a website building system. | |
EP4242892A3 (en) | Code pointer authentication for hardware flow control | |
GB2543183A (en) | Improvements related to forecasting systems | |
MY194652A (en) | Information recommendation method and apparatus | |
SG10201810036QA (en) | Processing queries containing a union-type operation | |
AU2015364405A8 (en) | Methods for simultaneous source separation | |
MX2017001231A (en) | Apparatus and method for generating an enhanced signal using independent noise-filling. | |
SG11201811808VA (en) | Database data modification request processing method and apparatus | |
SG10201907393WA (en) | Position information providing method and device | |
SG11201909119YA (en) | Search method and apparatus and non-temporary computer-readable storage medium |