A nonvolatile memory apparatus includes a memory cell array and a memory control circuit. The memory cell array includes a plurality of sub arrays each including a plurality of memory cells coupled to a plurality of bit lines. The memory control circuit sequentially couples thereto, based on a single read command signal, at least a single bit line disposed on the respective sub arrays to sequentially access a memory cell coupled to the at least single bit line.

Systems are provided for implementing a hardware accelerator. The hardware accelerator emulate a stochastic neural network, and includes a first memristor crossbar array, and a second memristor crossbar array. The first memristor crossbar array can be programmed to calculate node values of the neural network. The nodes values can be calculated in accordance with rules to reduce an energy function associated with the neural network. The second memristor crossbar array is coupled to the first memristor crossbar array and programmed to introduce noise signals into the neural network. The noise signals can be introduced such that the energy function associated with the neural network converges towards a global minimum and modifies the calculated node values.

In one example, a device to process analog sensor data is described. For example, a device may include at least one analog sensor to generate a first set of analog voltage signals and a crossbar array including a plurality of memristors. In one example, the crossbar array is to receive an input vector of the first set of analog voltage signals, generate an output vector comprising a second set of analog voltage signals that is based upon a dot product of the input vector and a matrix comprising resistance values of the plurality of memristors, detect a pattern of the output vector, and activate a processor upon a detection of the pattern.

Provided are processing and an electronic device including the same. The processing apparatus includes a bit cell line comprising bit cells connected in series, a mirror circuit unit configured to generate a mirror current by replicating a current flowing through the bit cell line at a ratio, a charge charging unit configured to charge a voltage corresponding to the mirror current as the mirror current replicated by the mirror circuit unit is applied, and a voltage measuring unit configured to output a value corresponding to a multiply-accumulate (MAC) operation of weights and inputs applied to the bit cell line, based on the voltage charged by the charge charging unit.

Artificial neuromorphic circuit includes synapse and post-neuron circuits. Synapse circuit includes phase change element and receives first and second pulse signals. Post-neuron circuit includes input, output and integration terminals. Integration terminal is charged to membrane potential according to first pulse signal. Post-neuron circuit further includes first and second control circuits, and first and second delay circuits. First control circuit generates firing signal at output terminal based on membrane potential. Second control circuit generates first control signal based on firing signal. First delay circuit delays firing signal to generate second control signal. Second delay circuit delays second control signal to generate third control signal. First and third control signals control voltage level of integration terminal, maintain integration terminal at fixed voltage during period, and second control signal cooperates with second pulse signal to control state of phase change element to determine weight of artificial neuromorphic circuit.

A resistive random access memory array and an operation method therefor, and a resistive random access memory circuit. The resistive random access memory array includes multiple memory cells, multiple bit lines, multiple word lines, multiple block selection circuits, and multiple initialization circuits. Each memory cell includes a resistive random access memory device and a switching device. The multiple memory cells are arranged into multiple memory cell rows and multiple memory cell columns in a first direction and a second direction, and the multiple bit lines and the multiple memory cell columns are connected in one-to-one correspondence. Each block selection circuit is configured to write a read/write operation voltage into a correspondingly connected bit line in response to a block selection voltage. Each initialization circuit is configured to write an initialization operation voltage to a correspondingly connected bit line in response to an initialization control voltage.

Provided are a switching device and a memory device including the switching device. The switching device includes first and second electrodes, and a switching material layer provided between the first and second electrodes and including a chalcogenide. The switching material layer includes a core portion and a shell portion covering a side surface of the core portion. The switching layer includes a material having an electrical resistance greater than an electrical resistance of the core portion, for example in at least one of the core portion or the shell portion.

A device for implementing spike-timing-dependent plasticity is provided. The device includes a phase-change element, first and second electrodes disposed respective first and second surfaces of the phase-change element. The phase-change element includes a phase-change material with an inverse resistivity characteristic. The first electrode includes a first heater element, and a first electrical insulating layer which electrically insulates the first resistive heater element from the first electrode and the phase-change element. The second electrode includes a second resistive heater element, and a second electrical insulating layer which electrically insulates the second resistive heater element from the second electrode and the phase-change element.

A phase change (PCM) memory device that includes a PCM and a resistance-capacitance (RC) circuit. The PCM has one or more PCM properties, each PCM property has a plurality of PCM property states. As the PCM property states of a given property are Set or Reset, the PCM property states each produce an incremental change to a property level of the respective/associated PCM property, e.g., PCM conductance. The incremental changes to property level of the PCM memory device are in response to application of one or more of a pulse number of voltage pulses. The RC circuit produces a configuring current that flows through the PCM in response to one or more of the voltage pulses. The configuring current modifies one or more of the incremental changes to one or more of the property levels so that the property level changes lineally with respect to the pulse number. The PCM memory device has use in a synapse connector, e.g., in a memory array. The memory array can be used to store and/or read memory values associated with one or more of the property levels. The memory values can be used as weighting values in a neuromorphic computing application/system, like a neural network.

A neuromorphic computing device a method of controlling thereof are provided. The neuromorphic computing device includes a first memory cell array including resistive memory cells that are connected to wordlines, bitlines and source lines, and configured to store data and generate read currents based on input signals and the data; a second memory cell array including reference resistive memory cells that are connected to reference wordlines, reference bitlines and reference source lines, and configured to generate reference currents; and an analog-to-digital converting circuit configured to convert the read currents into digital signals based on the reference currents, wherein a voltage is applied to the reference wordlines, the reference resistive memory cells are arranged in columns to form reference columns, and the reference columns are configured to generate column currents, and one of the reference currents is generated by averaging at least two of the column currents.