Patent classifications
G11C16/0425
WORD LINE AND CONTROL GATE LINE TANDEM DECODER FOR ANALOG NEURAL MEMORY IN DEEP LEARNING ARTIFICIAL NEURAL NETWORK
Various embodiments of tandem row decoders are disclosed. Each embodiment of a tandem row decoder comprises a word line decoder and a control gate decoder. The tandem row decoder exhibits reduced leakage current on the word line and the control gate line when the tandem row decoder is not enabled.
METHOD AND APPARATUS FOR DATA ERASE IN MEMORY DEVICES
Aspects of the disclosure provide a method for data erase in a memory device. The method includes providing first erase carriers from a body portion for the memory cell string, during an erase operation in a memory cell string. The first erase carriers flow in a first direction from a source side of the memory cell string to a drain side of the memory cell string. Further, the method includes providing second erase carriers from a junction at the drain side of the memory cell string. The second erase carriers flow in a second direction from the drain side of the memory cell string to the source side of the memory cell string. Then, the method includes injecting the first erase carriers and the second erase carriers to charge storage portions of the memory cells in the memory cell string.
METHOD OF TESTING A MEMORY CIRCUIT AND MEMORY CIRCUIT
A method of testing a three dimensional (3D) memory cell array includes writing data to each layer of memory cells in the 3D memory cell array, simultaneously performing a read operation of each memory cell in at least a first pillar of the 3D memory cell array, determining whether a memory cell in the 3D memory cell array has failed in response to the read operation, and replacing at least one failed memory cell in the 3D memory cell array with a spare memory cell in response to determining that the memory cell in the 3D memory cell array has failed. The first pillar includes memory cells on each corresponding layer of the 3D memory cell array.
MEMORY CELL SENSING
Sensing devices might include a first voltage node configured to receive a first voltage level, a second voltage node configured to receive a second voltage level lower than the first voltage level, a p-type field-effect transistor (pFET) selectively connected to a data line, and a sense node selectively connected to the pFET. The pFET might be connected between the first voltage node and the data line, between the second voltage node and the data line, and between the first voltage node and the data line. Memories might have controllers configured to cause the memories to determine whether a memory cell has an intended threshold voltage using similar sensing devices.
SPLIT-GATE MEMORY CELLS
Memory might include an array of memory cells having a plurality of strings of series-connected split-gate memory cells each including a primary memory cell portion and an assist memory cell portion, a plurality of primary access lines each connected to a control gate of the primary memory cell portion of a respective split-gate memory cell of each string of series-connected split-gate memory cells of the plurality of strings of series-connected split-gate memory cells, and a plurality of assist access lines each connected to a control gate of the assist memory cell portion of its respective split-gate memory cell of each string of series-connected split-gate memory cells of the plurality of strings of series-connected split-gate memory cells.
Method and apparatus for configuring array columns and rows for accessing flash memory cells
A non-volatile memory device is disclosed. The non-volatile memory device comprises an array of flash memory cells comprising a plurality of flash memory cells organized into rows and columns, wherein the array is further organized into a plurality of sectors, each sector comprising a plurality of rows of flash memory cells, and a row driver selectively coupled to a first row and a second row.
DEVICE AND METHOD TO GENERATE BIAS VOLTAGES IN NON-VOLATILE MEMORY
The present disclosure is directed to an integrated circuit that includes a non-volatile memory (NVM). The integrated circuit includes a bias generator that produces stable wordline and bitline voltages for a reliable read operation of the NVM. This disclosure is directed to low voltage memory operations of memory read, erase verify, and program verify. The present disclosure is directed to non-volatile memory circuits that can also operate at low supply voltages in digital voltage supply range.
Programmable neuron for analog non-volatile memory in deep learning artificial neural network
Numerous embodiments for processing the current output of a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. The embodiments comprise a summer circuit and an activation function circuit. The summer circuit and/or the activation function circuit comprise circuit elements that can be adjusted in response to the total possible current received from the VMM to optimize power consumption.
Analog neural memory array in artificial neural network with substantially constant array source impedance with adaptive weight mapping and distributed power
Numerous embodiments of analog neural memory arrays are disclosed. In certain embodiments, each memory cell in the array has an approximately constant source impedance when that cell is being operated. In certain embodiments, power consumption is substantially constant from bit line to bit line within the array when cells are being read. In certain embodiments, weight mapping is performed adaptively for optimal performance in power and noise.
WORD LINE AND CONTROL GATE LINE TANDEM DECODER FOR ANALOG NEURAL MEMORY IN DEEP LEARNING ARTIFICIAL NEURAL NETWORK
Various embodiments of tandem row decoders are disclosed. Each embodiment of a tandem row decoder comprises a word line decoder and a control gate decoder. The tandem row decoder exhibits reduced leakage current on the word line and the control gate line when the tandem row decoder is not enabled.