A combinational logic circuit includes input circuitry to receive a first and second input signals that transition between supply voltages of first and second voltage domain, respectively. The input circuitry generates, based on the first and second input signals, a first internal signal that transitions between one of the supply voltages of the first voltage domain and one of the supply voltages of the second voltage domain. Output circuitry within the combinational logic circuit generates an output signal that transitions between the upper and lower supply voltages of the first voltage domain in response to transition of the first internal signal.

Examples generally relate a programmable device having a unified programmable computational memory (PCM) and configuration network. In an example, a programmable device includes a die that includes a PCM integrated circuit having a PCM tile. The PCM tile includes a configuration memory (CM) and combinational logic (CL). The CM is capable of storing configuration data received via a node in the PCM tile. The CL is configured to receive internal control signal(s) and first and second input signals and to output a result signal. The CL is capable of outputting the result signal resulting from a logic function that is responsive to the internal control signal(s) and a signal of a group of signals including the first and second input signals. The CL is configured to receive the first input signal via the node in the PCM tile.

The Non-Volatile Arithmetic Memory Operator (NV-AMO) including a non-volatile memory cell for storing non-volatile data and a first input terminal for receiving volatile variable data is applied to perform the arithmetic operations over the volatile variable data and the non-volatile data. The NV-AMO can also be configured multiple-times for new computations. The constructions of NV-AMO in Arithmetic Logic Units (ALU) can be applied in DSP (Digital Signal Processor) computations and DNN (Deep Neural Network) computations.

The Non-Volatile Arithmetic Memory Operator (NV-AMO) including a non-volatile memory cell for storing non-volatile data and a first input terminal for receiving volatile variable data is applied to perform the arithmetic operations over the volatile variable data and the non-volatile data. The NV-AMO can also be configured multiple-times for new computations. The constructions of NV-AMO in Arithmetic Logic Units (ALU) can be applied in DSP (Digital Signal Processor) computations and DNN (Deep Neural Network) computations.

A data processing apparatus is provided, which includes addition circuitry that performs a calculation of a sum of a first operand and a second operand. The addition circuitry produces an intermediate data prior to the calculation completing. Determination circuitry uses the intermediate data to produce the sum of the first operand and the second operand plus 1. Further determination circuitry configured to use the intermediate data to produce the sum of the first operand and the second operand plus 2.

A data processing apparatus is provided, which includes addition circuitry that performs a calculation of a sum of a first operand and a second operand. The addition circuitry produces an intermediate data prior to the calculation completing. Determination circuitry uses the intermediate data to produce the sum of the first operand and the second operand plus 1. Further determination circuitry configured to use the intermediate data to produce the sum of the first operand and the second operand plus 2.

A circuit includes a plurality of first counting gates, a first ternary half adder (THA) and a second THA that are connected to the plurality of first counting gates, a third THA configured to receive a sum output signal of the first THA and a sum output signal of the second THA, a first ternary sum gate configured to receive a carry output signal of the first THA and a carry output signal of the second THA, and a second ternary sum gate configured to receive a carry output signal of the third THA and an output signal of the first ternary sum gate, wherein the third THA and the second ternary sum gate may be configured to output voltage signals corresponding to a number of drain voltages among input signals applied to the plurality of first counting gates.

A multiplication accumulating device and a method thereof are provided. The multiplication accumulating device includes a product generator, a plurality of registers, a product reducer, and an adder. The product generator performs a product operation on a multiplicand and a multiplier to generate a product result of 2N−1 columns. The product reducer is used to append data from a portion of the plurality of registers to the columns in the product result to generate an appending result of 2N−1 columns. The product reducer performs a reduction operation on the appending result according to a column height of each column in the appending result to obtain a reduced result. The product reducer renews the data in the plurality of registers according to the reduced result. The adder adds the data in the plurality of registers according to an accumulation signal to generate a multiplication accumulating operation result.

A multiplication accumulating device and a method thereof are provided. The multiplication accumulating device includes a product generator, a plurality of registers, a product reducer, and an adder. The product generator performs a product operation on a multiplicand and a multiplier to generate a product result of 2N−1 columns. The product reducer is used to append data from a portion of the plurality of registers to the columns in the product result to generate an appending result of 2N−1 columns. The product reducer performs a reduction operation on the appending result according to a column height of each column in the appending result to obtain a reduced result. The product reducer renews the data in the plurality of registers according to the reduced result. The adder adds the data in the plurality of registers according to an accumulation signal to generate a multiplication accumulating operation result.

Neuronal gate devices that function as a biological equivalent of AND, OR, and NOT digital logic gates are described. The neuronal gate devices comprise microstructures that support the patterned growth of two or more populations of neurons that are synaptically coupled. Also described are reconfigurable biological computers that comprise two or more coupled neuronal gates and may be trained to process a set of one or more input signals and generate a corresponding set of one or more output signals.