Abstract: The disclosure provides an in-memory computing (IMC) memory device and an IMC method thereof. The IMC memory device includes; a memory array including a plurality of computing units, each of the computing units including a plurality of parallel-coupling computing cells, the parallel-coupling computing cells of the same computing unit receiving a same input voltage; wherein a plurality of input data is converted into a plurality input voltages; after receiving the input voltages, the computing units generate a plurality of output currents; and based on the output currents, a multiply accumulate (MAC) of the input data and a plurality of conductance of the computing cells is generated.

Abstract: A memory device includes a high density or 3D data memory and a 3D reference memory. The reference memory is used to generate a reference signal used to sense data in the data memory. Conversion circuitry converts signals from one memory cell or a group of memory cells in the reference memory into a reference signal. The reference signal is applied to a sense amplifier to sense data stored in a selected memory cell in the data memory.

Abstract: A memory device includes a high density or 3D data memory and a 3D reference memory. The reference memory is used to generate a reference signal used to sense data in the data memory. Conversion circuitry converts signals from one memory cell or a group of memory cells in the reference memory into a reference signal. The reference signal is applied to a sense amplifier to sense data stored in a selected memory cell in the data memory.

Abstract: A memory device includes a high density or 3D data memory and a 3D reference memory. The reference memory is used to generate a reference signal used to sense data in the data memory. Conversion circuitry converts signals from one memory cell or a group of memory cells in the reference memory into a reference signal. The reference signal is applied to a sense amplifier to sense data stored in a selected memory cell in the data memory.

Abstract: A memory device includes a high density or 3D data memory and a 3D reference memory. The reference memory is used to generate a reference signal used to sense data in the data memory. Conversion circuitry converts signals from one memory cell or a group of memory cells in the reference memory into a reference signal. The reference signal is applied to a sense amplifier to sense data stored in a selected memory cell in the data memory.

Abstract: A spiking neural networks circuit and an operation method thereof are provided. The spiking neural networks circuit includes a bit-line input synapse array and a neuron circuit. The bit-line input synapse array includes a plurality of page buffers, a plurality of bit line transistors, a plurality of bit lines, a plurality of memory cells, one word line, a plurality of source lines and a plurality of source line transistors. The page buffers provides a plurality of data signals. Each of the bit line transistors is electrically connected to one of the page buffers. Each of the bit lines receives one of the data signals. The source line transistors are connected together. The neuron circuit is for outputting a feedback pulse.

Abstract: A semiconductor device is provided. The semiconductor device includes a first vertical stack, a first vertical channel line, a first data storage structure, and a first gate dielectric structure. The first vertical stack includes a first conductive line and a second conductive line. The first vertical channel line vertically passes through the first conductive line and the second conductive line, and the first vertical channel line is a P-type channel. The first data storage structure is disposed between the first conductive line and the first vertical channel line. The first gate dielectric structure is disposed between the second conductive line and the first vertical channel line.

Abstract: A spiking neural networks circuit and an operation method thereof are provided. The spiking neural networks circuit includes a bit-line input synapse array and a neuron circuit. The bit-line input synapse array includes a plurality of page buffers, a plurality of bit line transistors, a plurality of bit lines, a plurality of memory cells, one word line, a plurality of source lines and a plurality of source line transistors. The page buffers provides a plurality of data signals. Each of the bit line transistors is electrically connected to one of the page buffers. Each of the bit lines receives one of the data signals. The source line transistors are connected together. The neuron circuit is for outputting a feedback pulse.

Abstract: A multi-gate transistor includes; a doped drain region; a doped source region; a gate group including a first gate and a second gate; a channel, the doped drain region and the doped source region being on respective two sides of the channel; and an interlayer, formed between the channel and the gate group, wherein a first gate voltage and a second gate voltage are applied to the first gate and the second gate of the gate group, respectively, the channel is induced as at least a P sub-channel and at least an N sub-channel and the multi-gate transistor equivalently behaves as a PNPN structure.

Abstract: A multi-gate transistor includes: a doped drain region; a doped source region; a gate group including a first gate and a second gate; a channel, the doped drain region and the doped source region being on respective two sides of the channel; and an interlayer, formed between the channel and the gate group, wherein a first gate voltage and a second gate voltage are applied to the first gate and the second gate of the gate group, respectively, the channel is induced as at least a P sub-channel and at least an N sub-channel and the multi-gate transistor equivalently behaves as a PNPN structure.