A memory, including a selected memory cell block and a first sense amplifying device, is provided. The selected memory cell block and the first sense amplifying device are both coupled to a first global bit line. The first sense amplifying device is configured to: in a leakage current detection mode, detect a leakage current of the selected memory cell block on a first global bit line to generate leakage current information; and in a data reading mode, provide a reference signal according to the leakage current information, and compare a readout signal on the first global bit line with the reference signal to generate readout data, wherein the leakage current detection mode happens before the data reading mode.

There are provided a method for testing failure of a memory, an apparatus for testing failure of a memory, a computer-readable storage medium, and an electronic device. The method for testing failure of a memory includes: writing preset storage data into a storage array of the memory (S310); raising a bit line voltage, and controlling a part of word lines of the storage array to enter a test mode (S320); exiting the test mode after waiting for preset time (S330); turning off sense amplifiers corresponding to a preset part of bit lines, and reading data from a remaining part of the bit lines (S340); comparing the data read from the remaining part of the bit lines with the preset storage data to obtain a comparison result (S350); and determining a failure state of the memory according to the comparison result (S360).

A method of operating a memory circuit includes generating a first voltage by a first amplifier circuit of a first driver circuit coupled to a first column of memory cells, and generating a first current in response to the first voltage. The first current includes a first set of leakage currents and a first write current. The method further includes generating, by a tracking circuit, a second set of leakage currents configured to track the first set of leakage currents of the first column of memory cells, and mirroring the first current in a first path with a second current in a second path by a first current mirror. The second current includes the second set of leakage currents and a second write current. The first write current corresponds to the second write current. The first set of leakage currents corresponds to the second set of leakage currents.

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 an analog neural non-volatile memory cell in an array to a target value representing one of N different values, where N is an integer; verifying that a value stored in the analog neural non-volatile memory cell is within an acceptable window of values around the target value; repeating the programming and verifying for each of the N values; and identifying the analog neural non-volatile memory cell as bad if any of the verifying indicates a value stored in the cell outside of the acceptable window of values around the target value.

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.

In an aspect, the memory device includes not limited to a memory array, a leakage current verifying circuit, and a controller. The controller is configured to perform an erase operation for a first column of memory cells connected to a first WL, set a verify condition including a leakage current threshold, perform a leakage current verifying operation for the first column of the memory cells by comparing a leakage current of a cell of the first column of the memory cells to the leakage current threshold, detect a failure of the first column in response to a cell having the leakage current being above the leakage current threshold, and perform a post-program operation to repair the failure of the first column of the memory cells.

A method of operating a nonvolatile memory device which includes at least one memory block is provided. The method includes providing a plurality of word-lines with a voltage during a word-line set-up period, precharging a plurality of driving lines with a voltage during a word-line development period, detecting a voltage drop of a sensing node during a sensing period, and detecting leakage based on the voltage drop.

A method of operating a nonvolatile memory device which includes at least one memory block is provided. The method includes providing a plurality of word-lines with a voltage during a word-line set-up period, precharging a plurality of driving lines with a voltage during a word-line development period, detecting a voltage drop of a sensing node during a sensing period, and detecting leakage based on the voltage drop.

The present disclosure relates to an apparatus, and a method for memory management and more a memory device structured with internal analogic measurement mode features. The memory device includes memory component having a memory array, a memory controller coupled to the memory component, a JTAG interface in the memory controller, voltage and current reference generators, and an analogic measurement block driven by the JTAG interface.

Circuitry and methods are disclosed for compensating for leakage in analog neural memory in deep learning artificial neural networks. In one example, a method is disclosed of compensating for leakage in an array of analog neural non-volatile memory cells, wherein the array is arranged in rows and columns, wherein each row is coupled to a word line and each column is coupled to a bitline, the method comprising measuring leakage for a column of analog neural non-volatile memory cells coupled to a bitline; storing the measured leakage value; and applying the measured leakage value during a read operation of the column of analog neural non-volatile memory cells to compensate for the leakage.