Abstract: A random number generator that includes control circuit, an oscillation circuit, an oscillation detection circuit and a latch circuit is introduced. The control circuit sweeps a configuration of a bias control signal among a plurality of configurations. The oscillation circuit generates an oscillation signal based on the configuration of the bias control signal. The oscillation detection circuit detects an onset of the oscillation signal, and outputs a lock signal. The latch circuit latches the oscillation signal according to a trigger signal to output a random number, wherein the trigger signal is asserted after the lock signal is outputted, and the configuration of bias control signal is locked after the lock signal is outputted. A method for generating a random number and an operation method of a random number generator are also introduced.

Abstract: A resistive memory device includes a bottom electrode, a switching layer including a first horizontal portion, a second horizontal portion over an upper surface of the bottom electrode, and a first vertical portion over a side surface of the bottom electrode, a top electrode including a first horizontal portion over the first horizontal portion of the switching layer, a second horizontal portion over the second horizontal portion of the switching layer, and a first vertical portion over the first vertical portion of the switching layer, and a conductive via contacting the first horizontal portion, the second horizontal portion and the first vertical portion of the top electrode. By providing a switching layer and a top electrode which conform to a non-planar profile of the bottom electrode, charge crowding and a localized increase in electric field may facilitate resistance-state switching and provide a reduced operating voltage.

Abstract: An input-shaping method for a group-modulated input scheme in a plurality of computing-in-memory applications is configured to shape a plurality of multi-bit input signals. The input-shaping method for the group-modulated input scheme in the plurality of computing-in-memory applications includes performing an input splitting step, a threshold setting step and an input shaping step. The input splitting step includes splitting the multi-bit input signals into a plurality of input sub-groups via an input-shaping unit. The threshold setting step includes setting at least one shaping threshold via the input-shaping unit. The input shaping step includes shaping at least one of the input sub-groups according to the at least one shaping threshold via the input-shaping unit to form a plurality of shaped multi-bit input signals so as to increase a probability of a bit equal to 0 occurring in the at least one of the input sub-groups.

Abstract: A system includes a global generator and local generators. The global generator is coupled to a memory array, and is configured to generate global signals, according to a number of a computational output of the memory array. The local generators are coupled to the global generator and the memory array, and are configured to generate local signals, according to the global signals. Each one of the local generators includes a first reference circuit and a local current mirror. The first reference circuit is coupled to the global generator, and is configured to generate a first reference signal at a node, in response to a first global signal of the global signals. The local current mirror is coupled to the first reference circuit at the node, and is configured to generate the local signals, by mirroring a summation of at least one signal at the node.

Abstract: A method, device, and system for performing a partial sum accumulation of a product of input vectors and weight vectors in a wordwise-input and bitwise-weight manner results in a partial accumulated product sum. The partial accumulated product sum is compared with a threshold condition after each weight bit, and when the partial accumulated product sum meets the threshold condition, a skip indicator is asserted to indicate that remaining computations of a sum accumulation are skipped.

Abstract: A memory includes a memory device, a reading device and a feedback device. The memory device stores a plurality of bits. The reading device includes first and second reading circuits coupled to the memory device. The second reading circuit is coupled to the first reading circuit at a first node. The first and second reading circuits cooperates with each other to generate a first voltage signal at the first node based on at least one first bit of the plurality of bits. The feedback device adjusts at least one of the first reading circuit or the second reading circuit based on the first voltage signal. The first and second reading circuits generate a second voltage signal, different from the first voltage signal, corresponding to the bits, after the at least one of the first reading circuit or the second reading circuit is adjusted by the feedback device.

Abstract: A system includes a memory cell array including multi-level cells, an input data scramble circuit configured to receive input data and match lower error tolerant bits with higher error tolerant bits to provide matched bit sets, wherein each of the matched bit sets includes at least one lower error tolerant bit and at least one higher error tolerant bit, and a write driver configured to receive the matched bit sets and store each of the matched bit sets into one memory cell of the multi-level cells.

Abstract: A circuit includes a sense amplifier, a first clamping circuit, a second clamping circuit, and a feedback circuit. The first clamping circuit includes first clamping branches coupled in parallel between the sense amplifier and a memory array. The second clamping circuit includes second clamping branches coupled in parallel between the sense amplifier and a reference array. The feedback circuit is configured to selectively enable or disable one or more of the first clamping branches or one or more of the second clamping branches in response to an output data outputted by the sense amplifier.

Abstract: A method of storing a data into a memory storage having bit cells. The method includes identifying each of the binary one and the binary zero in the data as either a majority bit value or a minority bit value based on the probability of finding the binary one in the data or based on the probability of finding the binary zero in the data. In the method, a bit of the data is stored into the bit cell as the more preferred state if the bit of the data has the majority bit value, and a bit of the data is stored into the bit cell as the less preferred state if the bit of the data has the minority bit value.

Abstract: A sense amplifier of a memory device that includes sense amplifier circuits and a reference sharing circuit is introduced. The sense amplifier circuits are configured to sense the plurality of bit lines according to an enable signal. The reference sharing circuit includes first switches and second switches that are coupled to the reference nodes and second reference nodes of the sense amplifier circuits, respectively. The first switches and second switches are controlled according to a control signal to control a first electrical connection among the first reference nodes, and to control a second electrical connection among the second reference nodes. An operation method of the sense amplifier and a memory device including the sense amplifier are also introduced.

Abstract: An input sequence re-ordering method with a multi input-precision reconfigurable scheme and a pipeline scheme for a computing-in-memory macro in a convolutional neural network application is configured to re-order a plurality of multi-bit input signals and includes performing a scanning step and a re-ordering step. The scanning step includes driving a scanner to scan one group of the multi-bit input signals to determine whether an initial value of a plurality of flag signals in one of a plurality of multi-bit section flags is changed to an inverted initial value according to a plurality of bit numbers of the one group of the multi-bit input signals. The re-ordering step includes driving a sorter to select a part of the one group of the multi-bit input signals corresponding to a plurality of the inverted initial values of the flag signals in the one of the multi-bit section flags.

Abstract: A memory unit is controlled by a first word line and a second word line. The memory unit includes a memory cell and a multi-bit input local computing cell. The memory cell stores a weight. The memory cell is controlled by the first word line and includes a local bit line transmitting the weight. The multi-bit input local computing cell is connected to the memory cell and receives the weight via the local bit line. The multi-bit input local computing cell includes a plurality of input lines and a plurality of output lines. Each of the input lines transmits a multi-bit input value, and the multi-bit input local computing cell is controlled by the second word line to generate a multi-bit output value on each of the output lines according to the multi-bit input value multiplied by the weight.

Abstract: A memory unit with a multiply-accumulate assist scheme for a plurality of multi-bit convolutional neural network based computing-in-memory applications is controlled by a reference voltage, a word line and a multi-bit input voltage. The memory unit includes a non-volatile memory cell, a voltage divider and a voltage keeper. The non-volatile memory cell is controlled by the word line and stores a weight. The voltage divider includes a data line and generates a charge current on the data line according to the reference voltage, and a voltage level of the data line is generated by the non-volatile memory cell and the charge current. The voltage keeper generates an output current on an output node according to the multi-bit input voltage and the voltage level of the data line, and the output current is corresponding to the multi-bit input voltage multiplied by the weight.

Abstract: A control circuit, a memory system and a control method are provided. The control circuit is configured to control a plurality of memory cells of a memory array. The control circuit comprises a program controller. The program is configured to program a first electrical characteristic distribution and a second electrical characteristic distribution of the memory cells according to error tolerance of a first bit of a data type. A first overlapping area between the first electrical characteristic distribution and the second electrical characteristic distribution is smaller than a first predetermined value.

Abstract: A memory unit is controlled by a first word line and a second word line. The memory unit includes a memory cell and a transpose cell. The memory cell stores a weight. The memory cell is controlled by the first word line and includes a local bit line transmitting the weight. The transpose cell is connected to the memory cell and receives the weight via the local bit line. The transpose cell includes an input bit line, an input bit line bar, an output bit line and an output bit line bar. Each of the input bit line and the input bit line bar transmits a multi-bit input value, and the transpose cell is controlled by the second word line to generate a multi-bit output value on each of the output bit line and the output bit line bar according to the multi-bit input value and the weight.

Abstract: An input-shaping method for a group-modulated input scheme in a plurality of computing-in-memory applications is configured to shape a plurality of multi-bit input signals. The input-shaping method for the group-modulated input scheme in the plurality of computing-in-memory applications includes performing an input splitting step, a threshold setting step and an input shaping step. The input splitting step includes splitting the multi-bit input signals into a plurality of input sub-groups via an input-shaping unit. The threshold setting step includes setting at least one shaping threshold via the input-shaping unit. The input shaping step includes shaping at least one of the input sub-groups according to the at least one shaping threshold via the input-shaping unit to form a plurality of shaped multi-bit input signals so as to increase a probability of a bit equal to 0 occurring in the at least one of the input sub-groups.

Abstract: A random number generator that includes control circuit, an oscillation circuit, an oscillation detection circuit and a latch circuit is introduced. The control circuit sweeps a configuration of a bias control signal among a plurality of configurations. The oscillation circuit generates an oscillation signal based on the configuration of the bias control signal. The oscillation detection circuit detects an onset of the oscillation signal, and outputs a lock signal. The latch circuit latches the oscillation signal according to a trigger signal to output a random number, wherein the trigger signal is asserted after the lock signal is outputted, and the configuration of bias control signal is locked after the lock signal is outputted. A method for generating a random number and an operation method of a random number generator are also introduced.

Abstract: A quantization method for a plurality of partial sums of a convolution neural network based on a computing-in-memory hardware includes a probability-based quantizing step and a margin-based quantizing step. The probability-based quantizing step includes a network training step, a quantization-level generating step, a partial-sum quantizing step, a first network retraining step and a first accuracy generating step. The margin-based quantizing step includes a quantization edge changing step, a second network retraining step and a second accuracy generating step. The quantization edge changing step includes changing a quantization edge of at least one of a plurality of quantization levels. The probability-based quantizing step is performed to generate a first accuracy value, and the margin-based quantizing step is performed to generate a second accuracy value. The second accuracy value is greater than the first accuracy value.

Abstract: A system includes a global generator and local generators. The global generator is coupled to a memory array, and is configured to generate global signals, according to a number of a computational output of the memory array. The local generators are coupled to the global generator and the memory array, and are configured to generate local signals, according to the global signals. Each one of the local generators includes a first reference circuit and a local current mirror. The first reference circuit is coupled to the global generator, and is configured to generate a first reference signal at a node, in response to a first global signal of the global signals. The local current mirror is coupled to the first reference circuit at the node, and is configured to generate the local signals, by mirroring a summation of at least one signal at the node.

Abstract: A memory structure with input-aware maximum multiply-and-accumulate value zone prediction for computing-in-memory applications includes a memory array, an input-aware zone prediction circuit and an analog-to-digital converter. An input-aware maximum partial multiply-and-accumulate value voltage generator is configured to generate a maximum partial multiply-and-accumulate value according to at least one input value. A prediction-aware global reference voltage generator is configured to generate a plurality of global reference voltages, a maximum reference voltage and a selected minimum reference voltage. A maximum partial multiply-and-accumulate value zone detector is configured to generate a zone switch signal by comparing the maximum partial multiply-and-accumulate value and the global reference voltages.