IP Library › Granted Patent US 12,353,503
Granted Patent B2
US 12,353,503 · App. 16/449,205 · Granted Jul 8, 2025

Output array neuron conversion and calibration for analog neural memory in deep learning artificial neural network

Inventors: Hieu Van Tran (San Jose, CA); Stephen Trinh (San Jose, CA); Thuan Vu (San Jose, CA); Stanley Hong (San Jose, CA); Vipin Tiwari (Dublin, CA); Mark Reiten (Alamo, CA); Nhan Do (Saratoga, CA)
Assignee: Silicon Storage Technology, Inc.
G06F17/16G06N3/065G11C11/54G11C16/0483G11C16/08G11C2216/04
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,353,503
App. No.
16/449,205
Granted
Jul 8, 2025
Kind
B2
Abstract

Configurable input blocks and output blocks and physical layouts are disclosed for analog neural memory systems that utilize non-volatile memory cells. An input block can be configured to support different numbers of arrays arranged in a horizontal direction, and an output block can be configured to support different numbers of arrays arranged in a vertical direction. Adjustable components are disclosed for use in the configurable input blocks and output blocks. Systems and methods are utilized for compensating for leakage and offset in the input blocks and output blocks the in analog neural memory systems.

Claims (21)

1. A method, comprising:

measuring leakage current from one or more decoding circuits and one or more column write circuits for use with a non-volatile memory array and storing a measured leakage current value in a register;

retrieving the leakage current value from the register; and

converting a neuron output from the non-volatile memory array into a digital value and subtracting the leakage current value from the digital value.

2. A method comprising:

measuring leakage current from one or more decoding circuits and one or more write circuits for use with an array of analog neural memory cells using an analog-to-digital converter to generate a digital leakage current value;

storing the digital leakage current value as a first value in a counter; and

generating an output from a neuron output from the array using the counter and the first value, wherein the output is equal to the neuron output minus the first value.

3. The method in claim 2 , wherein the generating comprises converting a current from the array of analog neural memory cells into the output by counting down on the counter from the stored first value until the counter reaches zero and then counting up to generate the output.

4. The method in claim 2 , wherein the generating comprises measuring a current from the array of analog neural memory cells using the counter and then subtracting the stored first value from the measured current to generate the output.

5. The method of claim 2 , wherein the analog-to-digital converter comprises an integrating analog-to-digital converter.

6. The method of claim 2 , wherein the analog-to-digital converter comprises a ramp analog-to-digital converter.

7. The method of claim 2 , wherein the analog-to-digital converter comprises an algorithmic analog-to-digital converter.

8. The method of claim 2 , wherein the analog-to-digital converter comprises a sigma delta analog-to-digital converter.

9. The method of claim 2 , wherein the analog-to-digital converter comprises a successive approximation register analog-to-digital converter.

10. The method of claim 2 , further comprising:

converting the output into a voltage.

11. The method of claim 2 , further comprising:

converting the output into one or more pulses where the width of the one or more pulses is proportional to the value of the output.

12. The method of claim 2 , wherein the analog neural memory cells are split-gate flash memory cells.

13. The method of claim 2 , wherein the analog neural memory cells are stacked-gate flash memory cells.

Assignments (13)
RELEASE OF SECURITY INTEREST Recorded Mar 14, 2022
From: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
To: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
Reel/Frame 060894/0437 →
RELEASE OF SECURITY INTEREST Recorded Mar 11, 2022
From: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
To: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
Reel/Frame 059363/0001 →
RELEASE OF SECURITY INTEREST Recorded Mar 10, 2022
From: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
To: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
Reel/Frame 059863/0400 →
RELEASE OF SECURITY INTEREST Recorded Mar 9, 2022
From: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
To: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
Reel/Frame 059358/0335 →
RELEASE OF SECURITY INTEREST Recorded Feb 28, 2022
From: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
To: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
Reel/Frame 059263/0001 →
GRANT OF SECURITY INTEREST IN PATENT RIGHTS Recorded Nov 19, 2021
From: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
Reel/Frame 058214/0625 →
SECURITY INTEREST Recorded Jun 4, 2021
From: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
Reel/Frame 057935/0474 →
SECURITY INTEREST Recorded Dec 24, 2020
From: MICROCHIP TECHNOLOGY INCORPORATED; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 055671/0612 →
SECURITY INTEREST Recorded Jun 5, 2020
From: MICROCHIP TECHNOLOGY INC.; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION
Reel/Frame 053468/0705 →
SECURITY INTEREST Recorded Jun 5, 2020
From: MICROCHIP TECHNOLOGY INC.; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 052856/0909 →
RELEASE OF SECURITY INTEREST Recorded May 30, 2020
From: JPMORGAN CHASE BANK, N.A, AS ADMINISTRATIVE AGENT
To: MICROCHIP TECHNOLOGY INC.; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
Reel/Frame 053466/0011 →
SECURITY INTEREST Recorded Apr 24, 2020
From: MICROCHIP TECHNOLOGY INC.; SILICON STORAGE TECHNOLOGY, INC.; ATMEL CORPORATION; MICROSEMI CORPORATION; MICROSEMI STORAGE SOLUTIONS, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 053311/0305 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 17, 2019
From: TRAN, HIEU VAN; TRINH, STEPHEN; VU, THUAN; HONG, STANLEY; TIWARI, VIPIN; REITEN, MARK; DO, NHAN
To: SILICON STORAGE TECHNOLOGY, INC.
Reel/Frame 051031/0379 →
Continuity (2)
Provisional Application 62842279 · May 2, 2019
Related Publication 20200349422A1 · Nov 5, 2020
References Cited (108)
US 5029130A · Yeh · 1991 [cited by applicant]
US 5131072A · Yoshizawa · 1992 [cited by examiner]
US 5142666A · Yoshizawa · 1992 [cited by examiner]
US 5222193A · Brooks · 1993 [cited by examiner]
US 5298796A · Tawel · 1994 [cited by applicant]
US 6523018B1 · Louis · 2003 [cited by examiner]
US 6747310B2 · Fan · 2004 [cited by applicant]
US 7272585B2 · Nomura · 2007 [cited by examiner]
US 9164526B2 · Pan · 2015 [cited by examiner]
US 9646685B2 · Park · 2017 [cited by examiner]
US 10123143B2 · Parupalli et al. · 2018 [cited by applicant]
US 10205463B1 · Milkov et al. · 2019 [cited by applicant]
US 10489700B1 · Asnaashari · 2019 [cited by examiner]
US 10594334B1 · Far · 2020 [cited by examiner]
US 20020075729A1 · Choi · 2002 [cited by examiner]
US 20050131973A1 · Chambers · 2005 [cited by applicant]
US 20060028360A1 · Tittel · 2006 [cited by applicant]
US 20080158988A1 · Taylor · 2008 [cited by applicant]
US 20080205158A1 · Pagano · 2008 [cited by examiner]
US 20080310245A1 · Baker · 2008 [cited by examiner]
US 20100046291A1 · Dudeck · 2010 [cited by examiner]
US 20100097254A1 · Huang · 2010 [cited by applicant]
US 20120150781A1 · Arthur · 2012 [cited by examiner]
US 20140104934A1 · McLaury · 2014 [cited by examiner]
US 20140269133A1 · McCollum · 2014 [cited by examiner]
US 20140355381A1 · Lal · 2014 [cited by examiner]
US 20140365416A1 · Kim · 2014 [cited by examiner]
US 20160328645A1 · Lin · 2016 [cited by examiner]
US 20170012636A1 · Venca · 2017 [cited by applicant]
US 20170185891A1 · Hosokawa · 2017 [cited by examiner]
US 20170228345A1 · Gupta · 2017 [cited by applicant]
US 20170277658A1 · Pratas · 2017 [cited by examiner]
US 20170337466A1 · Bayat et al. · 2017 [cited by applicant]
US 20180075339A1 · Ma · 2018 [cited by examiner]
US 20180108403A1 · Ge · 2018 [cited by applicant]
US 20180225564A1 · Haiut · 2018 [cited by examiner]
US 20190013037A1 · Haiut · 2019 [cited by examiner]
US 20190019564A1 · Li · 2019 [cited by applicant]
US 20190042199A1 · Sumbul · 2019 [cited by examiner]
US 20190058483A1 · Kim · 2019 [cited by applicant]
US 20190156208A1 · Park · 2019 [cited by examiner]
US 20190164617A1 · Tran et al. · 2019 [cited by applicant]
US 20190370640A1 · Peng · 2019 [cited by examiner]
US 20200035305A1 · Choi · 2020 [cited by examiner]
US 20200105346A1 · Yang · 2020 [cited by examiner]
US 20200202586A1 · Li · 2020 [cited by examiner]
US 20200234108A1 · Kurokawa · 2020 [cited by examiner]
US 20200349440A1 · Gokmen · 2020 [cited by examiner]
US 20210019609A1 · Strukov · 2021 [cited by examiner]
US 20220123847A1 · Ghozlan · 2022 [cited by examiner]
US 20220172677A1 · Harada · 2022 [cited by examiner]
EP 0385436A2 · 1990 [cited by applicant]
JP S55130229A · 1980 [cited by applicant]
JP 2005122465A · 2005 [cited by applicant]
JP 2005122467 · 2005 [cited by applicant]
JP 2012504820 · 2012 [cited by applicant]
JP 2018133016 · 2018 [cited by applicant]
KR 20020049942 · 2002 [cited by applicant]
KR 20070058488 · 2007 [cited by applicant]
KR 20110061650 · 2011 [cited by applicant]
KR 20170134444 · 2017 [cited by applicant]
KR 20180110080 · 2018 [cited by applicant]
KR 20190020408 · 2019 [cited by applicant]
TW 201837737 · 2018 [cited by applicant]
WO 2010039859 · 2010 [cited by applicant]
WO WO2016164049A1 · 2016 [cited by examiner]
WO 2018189620 · 2018 [cited by applicant]
WO 2019055182A1 · 2019 [cited by applicant]
Tagliavini, Giuseppe. “Optimization Techniques for Parallel Programming of Embedded Many-Core Computing Platforms.” (2017): i-192 (Year: 2017). [cited by examiner]
Du, Yuan, et al. “An Analog Neural Network Computing Engine using CMOS-Compatible Charge-Trap-Transistor (CTT).” arXiv preprint arXiv:1709.06614 v4 (2018): 1-11 (Year: 2018). [cited by examiner]
Mittal, Sparsh. “A survey of ReRAM-based architectures for processing-in-memory and neural networks.” Machine learning and knowledge extraction 1.1 (2018): 75-114. (Year: 2018). [cited by examiner]
Tadayoni, Mandana, et al. “Modeling split-gate flash memory cell for advanced neuromorphic computing.” 2018 IEEE International Conference on Microelectronic Test Structures (ICMTS). IEEE, 2018:27-30 (Year: 2018). [cited by examiner]
O'Halloran, Micah, and Rahul Sarpeshkar. “A 10-nW 12-bit accurate analog storage cell with 10-aA leakage.” IEEE journal of solid-state circuits 39.11 (2004): 1985-1996. (Year: 2004). [cited by examiner]
Dlugosz, Rafal, Tomasz Talaska, and Witold Pedrycz. “Current-mode analog adaptive mechanism for ultra-low-power neural networks.” IEEE Transactions on Circuits and Systems II: Express Briefs 58.1 (2011): 31-35. (Year: 2… [cited by examiner]
Seo, Jae-sun, et al. “A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons.” 2011 IEEE Custom Integrated Circuits Conference (CICC). IEEE, 2011. (Year: 2011). [cited by examiner]
Meinerzhagen, Pascal, et al. “A 500 fW/bit 14 fJ/bit-access 4kb standard-cell based sub-V T memory in 65nm CMOS.” 2012 Proceedings of the ESSCIRC (ESSCIRC). IEEE, 2012: 321-324 (Year: 2012). [cited by examiner]
Rovere, Giovanni, et al. “Ultra low leakage synaptic scaling circuits for implementing homeostatic plasticity in neuromorphic architectures.” 2014 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2014… [cited by examiner]
Bankman, Daniel, et al. “An Always-On 3.8 mu J/86% CIFAR-10 mixed-signal binary CNN processor with all memory on chip in 28-nm CMOS.” IEEE Journal of Solid-State Circuits 54.1 (2018): 158-172. (Year: 2018). [cited by examiner]
Om'mani, Henry, et al. “A novel test structure to implement a programmable logic array using split-gate flash memory cells.” 2013 IEEE International Conference on Microelectronic Test Structures (ICMTS). IEEE, 2013: 192… [cited by examiner]
Do, Nhan. “eNVM technologies scaling outlook and emerging NVM technologies for embedded applications.” 2016 IEEE 8th International Memory Workshop (IMW). IEEE, 2016. (Year: 2016). [cited by examiner]
Diorio, Chris, David Hsu, and Miguel Figueroa. “Adaptive CMOS: from biological inspiration to systems-on-a-chip.” Proceedings of the IEEE 90.3 (2002): 345-357. (Year: 2002). [cited by examiner]
Maliuk, Dzmitry, and Yiorgos Makris. “An experimentation platform for on-chip integration of analog neural networks: A pathway to trusted and robust analog/RF ICs.” IEEE transactions on neural networks and learning syst… [cited by examiner]
Tadayoni, Mandana, et al. “Modeling split-gate flash memory cell for advanced neuromorphic computing.” 2018 IEEE International Conference on Microelectronic Test Structures (ICMTS). IEEE, Mar. 2018: 27-30 (Year: 2018). [cited by examiner]
Mayr, Christian, et al. “A biological-realtime neuromorphic system in 28 nm CMOS using low-leakage switched capacitor circuits.” IEEE transactions on biomedical circuits and systems 10.1 (2015): 243-254. (Year: 2015). [cited by examiner]
Shafiee, Ali, et al. “ISAAC: A convolutional neural network accelerator with in-situ analog arithmetic in crossbars.” ACM SIGARCH Computer Architecture News 44.3 (2016): 14-26. (Year: 2016). [cited by examiner]
Klachko, et al., “Improving Noise Tolerance of Mixed-Signal Neural Networks,” Cornell University Library, Apr. 3, 2019, 2020 IEEE. [cited by applicant]
Lin, et al., “A Novel Voltage-Accumulation Vector-Matrix Multiplication Architecture Using Resistor-shunted Floating Gate Flash Memory Device for Low-power and High-density Neural Network Applications,” pp. 2.4.1-2.4.4,… [cited by applicant]
Guo, et al., “Temperature-Insensitive Analog Vector-by-Matrix Multiplier Based on 55nm NOR Flash Memory Cells,” Apr. 30, 2017, IEEE. [cited by applicant]
Bavandpour, et al., “Energy-Efficient Time-Domain Vector-by-Matrix Multiplier for Neurocomputing and Beyond,” pp. 1-6, Nov. 29, 2017 (retrieved from the Internet: url:https://arxiv.org/pdf/1711.10673.pdf). [cited by applicant]
Bayat, et al., “Model-Based High-Precision Runing of NOR Flash Memory Cells for Analog Computing Applications,” pp. 1-2, 2016 74 [cited by applicant]
AVR127: “Understanding ADC Parameters,” https://www.microchip.com/wwwAppNotes/AppNotes.aspx?appnote=en590903—Dec. 10, 2016. [cited by applicant]
Taiwanese Search Report dated Jun. 2, 2021 for the related Taiwanese Patent Application No. 109109710. [cited by applicant]
Yuan Du et al., “A Memristive Neural Network Computing Engine Using CMOS-Compatible Charge-Trap-Transistor,” pp. 1-8, retrieved from the Internet, Sep. 2017. (See attached). [cited by applicant]
PCT Search Report & Written Opinion corresponding to the related PCT/US2019/062073. [cited by applicant]
Taiwanese Office Action mailed on Nov. 7, 2022 corresponding to the counterpart Taiwanese Patent Application No. 109109709. [cited by applicant]
Japanese Office Action mailed on Dec. 13, 2022 corresponding to the related Japanese Patent Application No. 2021-564790. [cited by applicant]
Mahmoodi, et al. “An Ultra-Low Energy Internally Analog, Externally Digital Vector-Matrix Multiplier Based on NOR Flash Memory Technology,” 6 pages, DAC '18, Jun. 24-29, 2018, Association for Computing Machinery. https:… [cited by applicant]
S. Korean Office Action mailed on Mar. 29, 2023 corresponding to the related S. Korean Patent Application No. 10-2021-7035908. [cited by applicant]
European Examiner's Report mailed on Mar. 28, 2023 corresponding to the related European Patent Application No. 19 821 455.3. [cited by applicant]
Japanese Office Action mailed on May 9, 2023 corresponding to the related Japanese Patent Application No. 2021-564790. [cited by applicant]
S. Korean Office Action mailed on Apr. 25, 2023, 2023 corresponding to the related S. Korean Patent Application No. 10-2021-7035930. [cited by applicant]
European Summons to Attend Oral Proceedings mailed on Oct. 9, 2023 corresponding to the related European Patent Application No. 19 821 455.3. [cited by applicant]
Japanese Office Action mailed on Jun. 18, 2024 corresponding to the related Japanese Patent Application No. 2023-109273. [cited by applicant]
S. Korean Office Action mailed on Jan. 25, 2024 corresponding to the related S. Korean Patent Application No. 10-2021-7035908. [cited by applicant]
S. Korean Notice of Allowance mailed on Feb. 26, 2024 corresponding to the related S. Korean Patent Application No. 10-2021-7035930. [cited by applicant]
Japanese Office Action mailed on Oct. 8, 2024 corresponding to the related Japanese Patent Application No. 2023-109273. (Google English translations and original Japanese Office Action are attached.). [cited by applicant]
Chinese Office Action mailed on Jan. 9, 2025 corresponding to the related Chinese Patent Application No. 201980095991.7. [cited by applicant]
Japanese Decision to Grant mailed on Jan. 28, 2025 corresponding to the related Japanese Patent Application No. 2023-109273. [cited by applicant]