Macronix International Co., Ltd.

Global Unichip Corporation

Taiwan Semiconductor Manufacturing Comp. Ltd.

Glyconex, Inc.

Hyweb Technology Co., Ltd.

Macronix International

Yu-Yu Lin

Feng-Min Lee

Ming-Hsiu Lee

Po-Hao Tseng

Kai-Chieh Hsu

Yu-Hsuan Lin

Feng-Ming Lee

Erh-Kun Lai

Dai-Ying Lee

Yi-Chou Chen

Tong-Hsuan Chang

Jerry Ting

Shu-Yen Chang

Wei-Lun Weng

Li-Hua Lin

Mei-Chun Yang

Chin-Sung Lin

Wei-Fu Wang

Yen-Ying Chen

Shu-Lun Tang

Wei-Chen Chen

Wei-Chih Chien

Kuang-Hao Chiang

Shih Hung Chen

Tian-Cih Bo

Hsiang-Lan Lung

Chao-Hung Wang

Chien-Hung Lu

Longqiang Zu

Liahng-Yirn Liu

Chung-Wei Yu

Tung-Hua Chuang

Kai-Chieh Lu

Liahng-Yim Liu

Chin-Yi Tseng

A memory device includes a first memory cell performing a logic operation. The first memory cell includes first and second switches. The first switch writes a first weight bit into a first storage node. The second switch generates a first current signal according to the first weight bit and a first input bit. The second switch receives a first bit line signal carrying the first input bit and a first word line signal. A control terminal of the second switch is coupled to the first storage node. When the first input bit has a first logic value, the first bit line signal and the first word line signal has a first voltage level. When the first input bit has a second logic value, the first bit line signal has a second voltage level smaller than the first voltage level.

Memory device and operating method thereof

A database circuit comprising data circuits and a processing circuit is provided. The data circuits are configured to receive a query data and respectively store a plurality of feature data that form at least one feature data class. The processing circuit is coupled to the data circuits, and configured to match the query data with the feature data to generate matching signals and take a first reference value as a target reference value to compare the matching signals with the target reference value. When at least one of the matching signals is greater than or equal to the target reference value, the processing circuit selects one of the at least one feature data class as a matching result; otherwise, the processing circuit takes a second reference value lower than the first reference value as the target reference value to compare the matching signals with the target reference value.

Database circuit and data matching method

A memory structure includes insulating layers, gate layers, a first doping layer, second doping layers, third doping layers, a columnar channel, a first dielectric layer, second dielectric layers, and a third dielectric layer. The first doping layer and the columnar channel penetrate through the insulating layers and the gate layers that are alternately stacked. The second doping layers are in direct contact with the first doping layer to form tunnel diodes, in which the second doping layers and the insulating layers are alternately stacked. The third doping layers surround the columnar channel and are connected to the second doping layers. The first dielectric layer is between the first doping layer and the gate layers. The second dielectric layers are between the third doping layers and the gate layers. The third dielectric layer is between the columnar channel and the third doping layers.

Memory structure, manufacturing method thereof, operating method thereof, and memory array

A reservoir device, comprises a first transistor and a second transistor. A gate of the first transistor is coupled to a write word line, a drain of the first transistor is coupled to a write bit line. A source of the second transistor is coupled to a read source line, a drain of the second transistor is coupled to a read bit line, and a gate of the second transistor is coupled to a source of the first transistor. A storage node is located on a coupling point between the gate of the second transistor and the source of the first transistor. The reservoir device selectively performs a write operation, a read operation or a refresh operation in response to an input voltage received by the write word line, the write bit line, the read source line and the read bit line respectively.

Reservoir device and reservoir array

A three-dimensional (3D) memory device comprising word lines, bit lines, a 3D memory array, encoding circuits and sensing circuits is provided in the present disclosure. The 3D memory array comprises two-dimensional (2D) memory arrays and stores first to fourth neural network data related to at least one neural network model. Each of the 2D memory arrays is coupled to the word lines and the bit lines, and is configured to receive first and second input voltages and output corresponding first and second output currents. The encoding circuits are respectively coupled to the 2D memory arrays and configured to generate the first and second input voltages respectively based on the first and second neural network data. The sensing circuits are respectively coupled to the 2D memory arrays and configured to generate the third and fourth neural network data respectively based on the first and second output currents.

Three-dimensional memory device

A memory device for performing an in-memory computation, comprising a plurality of memory cells each stores a weight value and comprises a transistor and a resistor. A gate of the transistor receives an input voltage, the input voltage indicates an input value. When the transistor operates at a first operating point, the input voltage is equal to a first input voltage, when the transistor operates at a second operating point, the input voltage is equal to a second input voltage. The resistor is connected to a drain and a source of the transistor, when the resistor operates in a first state, the weight value is equal to a first weight value, when the resistor operates in a second state, the weight value is equal to a second weight value. Each of the memory cells performs a product computation of the input value and the weight value.

Memory device for performing in-memory computation and operating method thereof

A memory structure includes insulating layers, gate layers, a first doping layer, channel layers, a columnar channel, second doping layers, a first dielectric layer, second dielectric layers, a third dielectric layer, and fourth dielectric layers. The first doping layer and the columnar channel penetrate through the insulating layers and the gate layers that are alternately stacked. The channel layers are connected to the first doping layer, in which the channel layers and the insulating layers are alternately stacked. The second doping layers surround the columnar channel and are connected to the channel layers. The first dielectric layer is between the first doping layer and the gate layers. The second dielectric layers are between the second doping layers and the gate layers. The third dielectric layer is between the columnar channel and the second doping layers. The fourth dielectric layers are between the channel layers and the gate layers.

Memory structure, manufacturing method thereof, and operating method thereof

An in-memory computing (IMC) memory device comprises a plurality of computing memory cells and a plurality of balance computing memory cells forming a plurality of memory strings. In programming, a first resistance state number of the balance computing memory cells is determined based on a first resistance state number of the computing memory cells of the memory string. In IMC operations, when a read voltage is applied to the computing memory cells, the computing memory cells generate a plurality of cell currents which are summed into a plurality of memory string currents; the memory string currents charge a loading capacitor; a capacitor voltage of the loading capacitor is measured; and based a relationship between the capacitor voltage of the loading capacitor, at least one delay time and a predetermined voltage, an operation result of the input values and the weight values is determined.

In-memory computing (IMC) memory device and in-memory computing method

The integrated circuit structure includes a substrate and a first resistive memory string over the substrate. The first resistive memory string includes memory cells, and each of the memory cells includes a word line transistor and a resistor. The word line transistor includes a channel region, a gate over the channel region, and a plurality of source/drain regions on opposite sides of the channel region. The resistor is over the word line transistor and is connected with the word line transistor in parallel. The word line transistors of two adjacent memory cells share a same one of the source/drain regions, and the memory cells are connected in series using the sharing ones of the source/drain regions.

Integrated circuit structure and method for operating the same

An in-memory computing memory device includes: a plurality of computing memory cells forming a plurality of memory strings, the computing memory cells storing a plurality of weight values; a loading capacitor; and a measurement circuit. In IMC operations, a plurality of input voltages, corresponding to a plurality of input values, are input into the computing memory cells; a plurality of effective resistances of the computing memory cells are corresponding to the input voltages and the weight values; when a read voltage is applied to the plurality of computing memory cells, the computing memory cells generate a plurality of cell currents which are summed into a plurality of memory string currents for charging the loading capacitor; and based a capacitor voltage of the loading capacitor, at least one delay time and a predetermined voltage, an operation result of the input values and the weight values is determined.

An in-memory computing (IMC) memory device and an IMC method are provided. The IMC memory device includes: a plurality of memory cells, the memory cells forming a plurality of computing layers; and a plurality of computing layer connectors, the computing layer connectors connecting between the computing layers. A first computing layer input is inputted into a first computing layer of the computing layers. The first computing layer generates a first computing layer output. A first computing layer connector of the computing layer connectors converts the first computing layer output into a second computing layer input. The first computing layer connector inputs the second computing layer input into a second computing layer of the computing layers. The computing layer connectors are a plurality of inverters, a plurality of voltage-to-voltage converters or a plurality of current-to-voltage converters.

In memory computing (IMC) memory device and method

A universal memory for In-Memory Computing and an operation method thereof are provided. The universal memory includes at least one write word line, at least one unit cell and at least one read word line. The unit cell includes a write transistor and a read transistor. The gate of the write transistor is connected to the write word line. The write transistor is a transistor with adjustable threshold voltage. The gate of the read transistor is connected to the drain or the source of the write transistor. The read word line is connected to the drain or the source of the read transistor. The universal memory is used for a training mode and an inference mode. In the training mode and the inference mode, a weight is stored at different locations of the unit cell.

Universal memory for in-memory computing and operation method thereof

An in-memory computation device includes multiple computation blocks, a first reference weight block, and an output result generator. The computation blocks have multiple weighting values, receive multiple input signals respectively, and generate multiple computation results. Each of the computation blocks generates each of the computation results according to each of the corresponding input signals and corresponding weighting values. The first reference weight block provides a first reference resistance according to multiple reference weighting values and generates a first reference signal according to the first reference resistance and a read voltage. The output result generator generates multiple output computation results according to the first reference signal and the computation results.

In-memory computation device

An artificial neural network operation circuit and an in-memory computation device of the artificial neural network operation circuit are proposed. The in-memory computation device includes a memory cell array, a compensation memory cell string, and an operator. The memory cell array has a plurality of memory cells to store a plurality of weight values. The memory cell array has a plurality of word lines and a plurality of bit lines. Each compensation memory cell of the compensation memory cell string stores a unit weight value. The operator multiplies a signal on a compensation bit line by peak weight information of the weight values to generate a first signal and adds the first signal to each signal on the bit lines to obtain a plurality of computation results, respectively.

Artificial neural network operation circuit and in-memory computation device thereof

A memory device and a method for operating the same are provided. The memory device includes a plurality of resistive memory cells and a control circuitry electrically connected to the plurality of resistive memory cells. The control circuitry provides operation modes to operate the plurality of resistive memory cells. The operation modes include a first program operation and a refresh operation. The first program operation includes applying a first program bias voltage to a selected resistive memory cell of the plurality of resistive memory cells to establish a low-resistance state in the selected resistive memory cell. The first program operation establishes a first threshold voltage in the memory device. The refresh operation includes applying a refresh bias voltage to the selected resistive memory cell to refresh the selected resistive memory cell. An absolute value of the refresh bias voltage is greater than the first threshold voltage.

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Taipei, Taiwan

Yu-Yu Lin