A method for multiple copies of a set of multi-kernel set operations in a hardware accelerated neural network includes a word line for receiving a pixel value of an input image. A bit line communicates a modified pixel value. An analog memory cell including a first capacitor stores a first kernel weight of a first kernel in one of a plurality of kernel sets such that the pixel value is operated on by the first kernel weight to produce the modified pixel value. A charge connection connects the first capacitor to at least a second capacitor storing a second kernel weight of a related kernel of a second one of the plurality of kernel sets such that charge is shared between the first capacitor and at least the second capacitor to normalize the first kernel weight and the second kernel weight.

A method for multiple copies of a set of multi-kernel set operations in a hardware accelerated neural network includes a word line for receiving a pixel value of an input image. A bit line communicates a modified pixel value. An analog memory cell including a first capacitor stores a first kernel weight of a first kernel in one of a plurality of kernel sets such that the pixel value is operated on by the first kernel weight to produce the modified pixel value. A charge connection connects the first capacitor to at least a second capacitor storing a second kernel weight of a related kernel of a second one of the plurality of kernel sets such that charge is shared between the first capacitor and at least the second capacitor to normalize the first kernel weight and the second kernel weight.

An embodiment in the application may include an analog memory structure, and methods of writing to such a structure, including a volatile memory element in series with a non-volatile memory element. The analog memory structure may change resistance upon application of a voltage. This may enable accelerated writing of the analog memory structure.

An analog content addressable memory (aCAM) that enables parallel searching of analog ranges of values and generates analog outputs that quantify matches between input data and stored data is disclosed. The input data can be compared with the stored data, and the input data can be determined to match the stored data based on a value associated with the input data being within a range associated with the stored data. The aCAM can generate an analog output that represents a number of matches and a number of mismatches between the input data and the stored data. Based on the analog output, whether the input data matches the stored data and a degree to which the input data matches the stored data can be determined.

A memory system may include a magnetic tunnel junction stack, a first high resistance tunnel barrier, and a first voltage controlled magnetic anisotropy write layer. The first voltage controlled magnetic anisotropy write layer may be adjacent the high resistance tunnel barrier, and the voltage controlled magnetic anisotropy write line may include a magnetic material in direct contact with a high resistance tunnel barrier.

A neuromorphic system according to an embodiment of the invention includes an input signal section that generates an input signal, a synapse section that includes a plurality of synaptic units that receive the input signal and makes a current to flow according to a set weight, each of the plurality of synaptic units including a plurality of non-volatile memory cells capable of selectively storing a logical state, the non-volatile memory cells being arranged in a memory array that include input electrode lines and output electrode lines crossing each other, and generates an output signal for each output electrode line by the input signal, a digital calculation section that digitizes the output signal generated for each output electrode line and calculates a sum of the digitized output signals, and a controller section that controls the input signal section, the synapse section, and the digital calculation section, and the controller section designates the number of digitized digits for each output electrode line and stores the logic state in the plurality of non-volatile memory cells according to a predetermined weight in each of the plurality of synaptic units, causes the input signal generated by the input signal section to be applied to each of a plurality of non-volatile memory cells of each of the plurality of synaptic units through the input electrode lines, generates, as the output signal, a sum of currents flowing from the plurality of non-volatile memory cells of each of the plurality of synaptic units by the applied input signal for each output electrode line, and causes the digital calculation section to digitize the output signal generated for each output electrode line according to the number of digits and calculate the sum of the digitized output signals.

Various examples of memory systems comprising an address fault detection system are disclosed. The memory system comprises a first memory array, a row decoder, and an address fault detection system comprising a second array, wherein the row decoder decodes row addresses into word lines, each word line coupled to a row of cells in the first array and a row of cells in the second array. The second array contains digital bits and/or analog values that are used to identify address faults.

Methods, systems, and devices for analog storing information are described herein. Such methods, systems and devices are suitable for synaptic weight storage in electronic neuro-biological mimicking architectures. A memory device may include a plurality of memory cells each respective memory cell in the plurality of memory cells with a respective programming sensitivity different from the respective programming sensitivity of other memory cells in the plurality. Memory cells may be provided on different decks of a multi-deck memory array. A storage element material of a respective memory cell may have a thickness and/or a composition different from another thickness or composition of a respective storage element material of another respective memory cell on a different deck in the multi-deck memory array. The memory device may further include reading circuitry configured to analogically read respective information programmed in the respective memory cells and to provide an output based on a combination of the respective information analogically read from the respective memory cells.

A floating-node memory device includes a metal-oxide-semiconductor (MOS) transistor including a first polysilicon gate, a source region, and a drain region in a first well region, a tunneling device including a second polysilicon gate in a second well region, and a metal-insulator-metal (MIM) capacitor including a conductive top plate and a bottom plate formed in a metal interconnect layer. The floating-node device includes a floating-node comprising the first polysilicon gate, the second polysilicon gate, and the conductive top plate of the MIM capacitor coupled together, a control node at the bottom plate of the MIM capacitor, an erase node in the second well region, a source node at the source region of the MOS transistor, and a drain node at the drain region of the MOS transistor.

A non-volatile memory device includes a floating-node memory cell disposed in an integrated circuit (IC). The memory cell includes a floating-node, a control node, an erase node, a source node, and a drain node. The memory device also includes a high-voltage input node for coupling to an external programmable high-voltage source external to the IC. The memory device also includes a high-voltage switch circuit coupled to the high-voltage input node for providing a voltage signal for performing hot-electron programming of charges to the floating node and tunneling erase of charges from the floating node.