KR102457394B1 - 딥 러닝 신경 네트워크에서 사용되는 아날로그 신경 메모리 시스템 내의 메모리 셀들에 대한 온도 및 누설 보상 - Google Patents

딥 러닝 신경 네트워크에서 사용되는 아날로그 신경 메모리 시스템 내의 메모리 셀들에 대한 온도 및 누설 보상 Download PDF

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KR102457394B1
KR102457394B1 KR1020217007006A KR20217007006A KR102457394B1 KR 102457394 B1 KR102457394 B1 KR 102457394B1 KR 1020217007006 A KR1020217007006 A KR 1020217007006A KR 20217007006 A KR20217007006 A KR 20217007006A KR 102457394 B1 KR102457394 B1 KR 102457394B1
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memory cell
voltage
array
temperature
memory cells
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KR20210032538A (ko
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휴 반 트란
비핀 티와리
마크 레이텐
난 도
스테벤 렘케
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실리콘 스토리지 테크놀로지 인크
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    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C16/00—Erasable programmable read-only memories
    • G11C16/02—Erasable programmable read-only memories electrically programmable
    • G11C16/04—Erasable programmable read-only memories electrically programmable using variable threshold transistors, e.g. FAMOS
    • G11C16/0408—Erasable programmable read-only memories electrically programmable using variable threshold transistors, e.g. FAMOS comprising cells containing floating gate transistors
    • G11C16/0425—Erasable programmable read-only memories electrically programmable using variable threshold transistors, e.g. FAMOS comprising cells containing floating gate transistors comprising cells containing a merged floating gate and select transistor
    • G06N3/0635—
    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C11/00—Digital stores characterised by the use of particular electric or magnetic storage elements; Storage elements therefor
    • G11C11/54—Digital stores characterised by the use of particular electric or magnetic storage elements; Storage elements therefor using elements simulating biological cells, e.g. neuron
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
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    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
    • G06N3/0445—
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    • G06N3/02—Neural networks
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    • G06N3/0464—Convolutional networks [CNN, ConvNet]
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    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/065—Analogue means
    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C16/00—Erasable programmable read-only memories
    • G11C16/02—Erasable programmable read-only memories electrically programmable
    • G11C16/06—Auxiliary circuits, e.g. for writing into memory
    • G11C16/10—Programming or data input circuits
    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C16/00—Erasable programmable read-only memories
    • G11C16/02—Erasable programmable read-only memories electrically programmable
    • G11C16/06—Auxiliary circuits, e.g. for writing into memory
    • G11C16/10—Programming or data input circuits
    • G11C16/14—Circuits for erasing electrically, e.g. erase voltage switching circuits
    • G11C16/16—Circuits for erasing electrically, e.g. erase voltage switching circuits for erasing blocks, e.g. arrays, words, groups
    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C16/00—Erasable programmable read-only memories
    • G11C16/02—Erasable programmable read-only memories electrically programmable
    • G11C16/06—Auxiliary circuits, e.g. for writing into memory
    • G11C16/26—Sensing or reading circuits; Data output circuits
    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C7/00—Arrangements for writing information into, or reading information out from, a digital store
    • G11C7/04—Arrangements for writing information into, or reading information out from, a digital store with means for avoiding disturbances due to temperature effects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
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    • G06N3/04—Architecture, e.g. interconnection topology
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    • G06N3/045—Combinations of networks
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    • G06—COMPUTING OR CALCULATING; COUNTING
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    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11C—STATIC STORES
    • G11C2216/00—Indexing scheme relating to G11C16/00 and subgroups, for features not directly covered by these groups
    • G11C2216/02—Structural aspects of erasable programmable read-only memories
    • G11C2216/04—Nonvolatile memory cell provided with a separate control gate for erasing the cells, i.e. erase gate, independent of the normal read control gate

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KR1020217007006A 2018-08-27 2019-07-23 딥 러닝 신경 네트워크에서 사용되는 아날로그 신경 메모리 시스템 내의 메모리 셀들에 대한 온도 및 누설 보상 Active KR102457394B1 (ko)

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Application Number Priority Date Filing Date Title
US201862723398P 2018-08-27 2018-08-27
US62/723,398 2018-08-27
US16/183,250 2018-11-07
US16/183,250 US10755783B2 (en) 2018-08-27 2018-11-07 Temperature and leakage compensation for memory cells in an analog neural memory system used in a deep learning neural network
PCT/US2019/043101 WO2020046495A1 (en) 2018-08-27 2019-07-23 Temperature and leakage compensation for memory cells in an analog neural memory system used in a deep learning neural network

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KR20210032538A KR20210032538A (ko) 2021-03-24
KR102457394B1 true KR102457394B1 (ko) 2022-10-21

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EP (2) EP4138079B1 (https=)
JP (1) JP7281535B2 (https=)
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CN (1) CN112602095B (https=)
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US20230306246A1 (en) * 2022-02-08 2023-09-28 Silicon Storage Technology, Inc. Calibration of electrical parameters in a deep learning artificial neural network
US11716089B1 (en) * 2022-03-16 2023-08-01 Xilinx, Inc. Delay-tracking biasing for voltage-to-time conversion
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EP4138079A1 (en) 2023-02-22
US20210090654A1 (en) 2021-03-25
JP2021536623A (ja) 2021-12-27
CN112602095B (zh) 2022-05-27
EP3844680A1 (en) 2021-07-07
US11521682B2 (en) 2022-12-06
WO2020046495A1 (en) 2020-03-05
TW202026955A (zh) 2020-07-16
US10755783B2 (en) 2020-08-25
US20200350015A1 (en) 2020-11-05
TWI754162B (zh) 2022-02-01
EP3844680B1 (en) 2022-11-23
CN112602095A (zh) 2021-04-02
US11158374B2 (en) 2021-10-26
EP4138079B1 (en) 2024-08-28
JP7281535B2 (ja) 2023-05-25
KR20210032538A (ko) 2021-03-24
US20200066345A1 (en) 2020-02-27

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