公开(公告)号：US11799005B2

公开(公告)日：2023-10-24

申请号：US17346524

申请日：2021-06-14

Applicant: Silicon Storage Technology, Inc.

Inventor： Leo Xing ,  Chunming Wang ,  Xian Liu ,  Nhan Do ,  Guo Xiang Song

IPC: H01L29/423 ,  H01L29/788 ,  H01L29/66 ,  H01L21/28

CPC classification number: H01L29/42328 ,  H01L29/40114 ,  H01L29/66825 ,  H01L29/7883

Abstract: A method of forming a memory device that includes forming a first insulation layer, a first conductive layer, and a second insulation layer on a semiconductor substrate, forming a trench in the second insulation layer to expose the upper surface of the first conductive layer, performing an oxidation process and a sloped etch process to reshape the upper surface to a concave shape, forming a third insulation layer on the reshaped upper surface, forming a conductive spacer on the third insulation layer, removing portions of the first conductive layer leaving a floating gate under the conductive spacer with the reshaped upper surface terminating at a side surface at a sharp edge, and forming a word line gate laterally adjacent to and insulated from the floating gate. The conductive spacer includes a lower surface that faces and matches the shape of the reshaped upper surface.

公开(公告)号：US20230268004A1

公开(公告)日：2023-08-24

申请号：US18140103

申请日：2023-04-27

Applicant: Silicon Storage Technology, Inc.

Inventor： Hieu Van Tran ,  Stanley Hong ,  Stephen Trinh ,  Thuan Vu ,  Steven Lemke ,  Vipin Tiwari ,  Nhan Do

IPC: G11C16/10 ,  G11C16/04 ,  G11C16/34 ,  G11C11/56 ,  G11C16/14 ,  G06N3/065

CPC classification number: G11C16/10 ,  G11C16/0425 ,  G11C16/0433 ,  G11C16/3459 ,  G11C11/5628 ,  G11C16/14 ,  G06N3/065

Abstract: In one example, a method comprises determining a program resolution current value; and setting levels for a programming operation of a plurality of non-volatile memory cells in a neural network array such that a delta current between levels of each pair of adjacent cells in the plurality is a multiple of the program resolution current value.

公开(公告)号：US20230262975A1

公开(公告)日：2023-08-17

申请号：US17745639

申请日：2022-05-16

Applicant: Silicon Storage Technology, Inc.

Inventor： Zhuoqiang Jia ,  Leo Xing ,  Xian Liu ,  Serguei Jourba ,  Nhan Do

IPC: H01L27/11546 ,  H01L27/11524 ,  H01L21/28 ,  H01L29/66 ,  H01L27/11529

CPC classification number: H01L27/11546 ,  H01L27/11524 ,  H01L29/40114 ,  H01L29/66825 ,  H01L27/11529 ,  H01L29/42328

Abstract: A method of forming a device on a semiconductor substrate having first, second, third and dummy areas, includes recessing the substrate upper surface in the first, second and dummy areas, forming a first conductive layer over the substrate, removing the first conductive layer from the third area and a second portion of the dummy area, forming a first insulation layer over the substrate, forming first trenches through the first insulation layer and into the substrate in the third area and the second portion of the dummy area, forming second trenches through the first insulation layer, the first conductive layer and into the substrate in the first and second areas and a first portion of the dummy area, and filling the first and second trenches with insulation material. Then, memory cells are formed in the first area, HV devices in the second area and logic devices in the third area.

公开(公告)号：US20230229888A1

公开(公告)日：2023-07-20

申请号：US18123921

申请日：2023-03-20

Applicant: Silicon Storage Technology, Inc. ,  The Regents of the University of California

Inventor： Farnood Merrikh Bayat ,  Xinjie Guo ,  Dmitri Strukov ,  Nhan Do ,  Hieu Van Tran ,  Vipin Tiwari ,  Mark Reiten

IPC: G06N3/04 ,  G06N3/063 ,  G11C11/54 ,  G11C16/34 ,  G11C29/38 ,  G06N3/045 ,  G11C16/08 ,  G11C16/12 ,  G11C16/16 ,  G06F3/06

CPC classification number: G06N3/04 ,  G06N3/063 ,  G11C11/54 ,  G11C16/3436 ,  G11C29/38 ,  G06N3/045 ,  G11C16/08 ,  G11C16/12 ,  G11C16/16 ,  G06F3/061 ,  G06F3/0655 ,  G06F3/0688

Abstract: Numerous examples of summing circuits for a neural network are disclosed. In one example, a circuit for summing current received from a plurality of synapses in a neural network comprises a voltage source; a load coupled between the voltage source and an output node; a voltage clamp coupled to the output node for maintaining a voltage at the output node; and a plurality of synapses coupled between the output node and ground; wherein an output current flows through the output node, the output current equal to a sum of currents drawn by the plurality of synapses.

公开(公告)号：US11646075B2

公开(公告)日：2023-05-09

申请号：US17471099

申请日：2021-09-09

Applicant: Silicon Storage Technology, Inc.

Inventor： Hieu Van Tran ,  Steven Lemke ,  Vipin Tiwari ,  Nhan Do ,  Mark Reiten

IPC: G11C11/54 ,  H01L29/423 ,  G11C16/04 ,  G11C16/10 ,  G11C16/14 ,  H01L29/788 ,  G06N3/045

CPC classification number: G11C11/54 ,  G06N3/045 ,  G11C16/0483 ,  G11C16/10 ,  G11C16/14 ,  H01L29/42324 ,  H01L29/42328 ,  H01L29/7883 ,  H10B41/30

Abstract: A neural network device with synapses having memory cells each having a floating gate and a first gate over first and second portions of a channel region disposed between source and drain regions, and a second gate over the floating gate or the source region. First lines each electrically connect the first gates in one of the memory cell rows, second lines each electrically connect the second gates in one of the memory cell rows, third lines each electrically connect the source regions in one of the memory cell columns, and fourth lines each electrically connect the drain regions in one of the memory cell columns. The synapses receive a first plurality of inputs as electrical voltages on the first or second lines, and provide a first plurality of outputs as electrical currents on the third or fourth lines.

公开(公告)号：US11636322B2

公开(公告)日：2023-04-25

申请号：US16829757

申请日：2020-03-25

Applicant: Silicon Storage Technology, Inc.

Inventor： Hieu Van Tran ,  Steven Lemke ,  Vipin Tiwari ,  Nhan Do ,  Mark Reiten

IPC: G06N3/063 ,  G11C11/54 ,  G06F1/03 ,  G06F17/16 ,  G11C11/56 ,  G06F11/16 ,  G11C13/00 ,  G11C29/44 ,  G06F7/78

Abstract: Numerous embodiments of a precision programming algorithm and apparatus are disclosed for precisely and quickly depositing the correct amount of charge on the floating gate of a non-volatile memory cell within a vector-by-matrix multiplication (VMM) array in an artificial neural network. Selected cells thereby can be programmed with extreme precision to hold one of N different values.

公开(公告)号：US11621335B2

公开(公告)日：2023-04-04

申请号：US17701840

申请日：2022-03-23

Applicant: Silicon Storage Technology, Inc.

Inventor： Chunming Wang ,  Xian Liu ,  Guo Xiang Song ,  Leo Xing ,  Nhan Do

IPC: G11C11/34 ,  H01L29/423 ,  H01L29/788 ,  H01L29/66 ,  G11C16/04

Abstract: A memory device, and method of making the same, that includes a substrate of semiconductor material of a first conductivity type, first and second regions spaced apart in the substrate and having a second conductivity type different than the first conductivity type, with a first channel region in the substrate extending between the first and second regions, a first floating gate disposed over and insulated from a first portion of the first channel region adjacent to the second region, a first coupling gate disposed over and insulated from the first floating gate, a first word line gate disposed over and insulated from a second portion of the first channel region adjacent the first region, and a first erase gate disposed over and insulated from the first word line gate.

公开(公告)号：US20230031487A1

公开(公告)日：2023-02-02

申请号：US17949962

申请日：2022-09-21

Applicant: Silicon Storage Technology, Inc.

Inventor： Hieu Van Tran ,  Steven Lemke ,  Vipin Tiwari ,  Nhan Do ,  Mark Reiten

IPC: H01L27/11531 ,  G11C16/04 ,  G06N3/08 ,  H01L29/788

Abstract: Numerous examples of an input function circuit block and an output neuron circuit block coupled to a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. In one example, an artificial neural network comprises a vector-by-matrix multiplication array comprising a plurality of non-volatile memory cells organized into rows and columns; an input function circuit block to receive digital input signals, convert the digital input signals into analog signals, and apply the analog signals to control gate terminals of non-volatile memory cells in one or more rows of the array during a programming operation; and an output neuron circuit block to receive analog currents from the columns of the array during a read operation and generate an output signal.

公开(公告)号：US20220405564A1

公开(公告)日：2022-12-22

申请号：US17893075

申请日：2022-08-22

Applicant: Silicon Storage Technology, Inc.

Inventor： Hieu Van Tran ,  Thuan Vu ,  Stephen Trinh ,  Stanley Hong ,  Anh Ly ,  Steven Lemke ,  Nha Nguyen ,  Vipin Tiwari ,  Nhan Do

IPC: G06N3/063 ,  G06N3/04 ,  G11C16/04 ,  G11C16/10 ,  G11C16/34

Abstract: Testing circuitry and methods are disclosed for use with analog neural memory in deep learning artificial neural networks. In one example, a method comprises programming a plurality of analog neural non-volatile memory cells in an array of analog neural non-volatile memory cells to store one of N different values, where N is a number of different levels that can be stored in any of the analog neural non-volatile memory cells; measuring a current drawn by the plurality of analog neural non-volatile memory cells; comparing the measured current to a target value; and identifying the plurality of the analog neural non-volatile memory cells as bad if the difference between the measured value and the target value exceeds a threshold.

公开(公告)号：US20220391682A1

公开(公告)日：2022-12-08

申请号：US17885431

申请日：2022-08-10

Applicant: Silicon Storage Technology, Inc.

Inventor： Hieu Van Tran ,  Vipin Tiwari ,  Nhan Do

IPC: G06N3/063 ,  G06N3/04 ,  G06F3/06 ,  G06F17/16 ,  G06N3/08 ,  G11C11/56 ,  G11C13/00 ,  G11C16/04 ,  G11C16/28

Abstract: Numerous embodiments are disclosed for compensating for differences in the slope of the current-voltage characteristic curve among reference transistors, reference memory cells, and flash memory cells during a read operation in an analog neural memory in a deep learning artificial neural network. In one embodiment, a method comprises receiving a first voltage, multiplying the first voltage by a coefficient to generate a second voltage, applying the first voltage to a gate of one of a reference transistor and a selected memory cell, applying the second voltage to a gate of the other of a reference transistor and a selected memory cell, and using the reference transistor in a sense operation to determine a value stored in the selected memory cell.