Abstract: A combined adder for N logical bits to produce a sum from a first addend having N first addend bits and a second addend having N second addend bits. A least significant adder produces a segment sum of the least significant bits and a carry out. Segment adder pairs are used for each higher order of significant sums. One segment adder produces a segment sum portion, and the other produces an incremented segment sum portion. Carry logic associated with each segment is utilized with a multiplexer to select the incremented segment sum portion or the segment sum portion. The selected segment sum portions are assembled with a most significant carry out to produce the sum.

Abstract: A device (e.g., integrated circuit chip) includes a first operand register, a second operand register, a multiplication unit, and a hardware logic component. The first operand register is configured to store a first operand value. The second operand register is configured to store a second operand value. The multiplication unit is configured to at least multiply the first operand value with the second operand value. The hardware logic component is configured to detect whether a zero value is provided and in response to a detection that the zero value is being provided: cause an update of at least the first operand register to be disabled, and cause a result of a multiplication of the first operand value with the second operand value to be a zero-value result.

Abstract: A signal processing apparatus comprises an operation processing part that performs operation processing on data represented in the two's complement representation and a storage processing part that performs storage processing on data represented in a second representation format as a data representation format, and in the second representation format, a data value is identical to one in the two's complement representation when the value is positive or zero, and all the bits lower than the most significant bit that indicates the sign in the two's complement representation are inverted when a data value is negative.

Abstract: A computation device includes: a list generation unit that generates a list indicating element values of first elements comprised in a plurality of computational matrices having equal numbers of rows and columns, the element values being indicated for the respective positions of the first elements in the computational matrices; and a computation execution unit that carries out computation based on the element values of the first elements indicated in the list and the element values of second elements comprised in a partial matrix belonging to a computation target matrix and having the same number of rows and columns as the computational matrices.

Abstract: In a general aspect, an optimization problem is solved using a hybrid computing system. A classical processor unit receives a first data structure that represents the optimization problem. The classical processor unit executes a branch-and-bound process on the first data structure to generate values for a first subset of elements of a solution to the optimization problem. A second data structure is generated based on the first data structure and the first subset of elements. The second data structure represents a reduced version of the optimization problem. A quantum processor unit and a classical processor unit are used to execute a quantum approximate optimization algorithm (QAOA) on the second data structure to generate values for a second subset of the elements of the solution to the optimization problem. The first subset and second subset are combined to obtain the solution to the optimization problem.

Abstract: A pseudo speckle pattern generation apparatus includes a light source, a beam expander, and a spatial light modulator. The spatial light modulator has an intensity modulation distribution based on a pseudo speckle pattern calculated from a pseudo random number pattern and a correlation function, receives light output from the light source and increased in beam diameter by the beam expander, spatially modulates the received light according to the modulation distribution, and outputs modulated light.

Abstract: A neural network circuit having a novel structure is provided. A plurality of arithmetic circuits each including a register, a memory, a multiplier circuit, and an adder circuit are provided. The memory outputs different weight data in response to switching of a context signal. The multiplier circuit outputs multiplication data of the weight data and input data held in the register. The adder circuit performs a product-sum operation by adding the obtained multiplication data to data obtained by a product-sum operation in an adder circuit of another arithmetic circuit. The obtained product-sum operation data is output to an adder circuit of another arithmetic circuit, so that product-sum operations of different weight data and input data are performed.

Abstract: Embodiments of a telemetry device and methods to convert a binary floating point number to a compressed number is described herein. The binary floating point number may comprise a mantissa and an exponent. The telemetry device may determine a first number based on a product of the exponent and a constant, wherein the constant may be proportional to a logarithm of the number two. The telemetry device may determine a second number using one or more bits of the mantissa as an index into a predetermined lookup table. Values of the lookup table may be proportional to logarithms of candidate mantissa values. The telemetry device may determine the compressed number based on rounding of a sum. The sum may include the first and second numbers. The rounding may be based on a predetermined step size.

Abstract: A semiconductor memory device includes a plurality of memory bank groups configured to be accessed in parallel; an internal memory bus configured to receive external data from outside the plurality of memory bank groups; and a first computation circuit configured to receive internal data from a first memory bank group of the plurality of memory bank groups during each first period of a plurality of first periods, receive the external data through the internal memory bus during each second period of a plurality of second periods, the second period being shorter than the first period, and perform a processing in memory (PIM) arithmetic operation on the internal data and the external data during each second period.

Abstract: An improved electronic mixed mode multiplier and accumulate circuit for artificial intelligence and computing system applications that perform vector-vector, vector-matrix and other multiply-accumulate computations. The circuit is provided is a high resolution, high linearity, low area, low power multiply—accumulate (MAC) unit to interface with a memory device for storing computation output results. The MAC unit uses a less number of current carrying elements resulting in much lower integrated circuit area, and provides a tight matching between the current elements thus preserving inherent linearity requirements due to current mode operation. Further the MAC performs current scaling using switches and current division where the current switches occupy minimum size transistors requiring a small area to implement that renders it compatible with MRAM such as a magnetic tunnel junction device.

Abstract: A processing unit and a method for multiplying at least two multiplicands. The multiplicands are present in an exponential notation, that is, each multiplicand is assigned an exponent and a base. The processing unit is configured to carry out a multiplication of the multiplicands and includes at least one bitshift unit, the bitshift unit shifting a binary number a specified number of places, in particular, to the left; an arithmetic unit, which carries out an addition of two input variables and a subtraction of two input variables; and a storage device. A computer program, which is configured to execute the method, and a machine-readable storage element, in which the computer program is stored, are also described.

Abstract: A zero-insertion FIR filter architecture for filtering a signal with a target band and a secondary band. Digital filter circuitry includes an L-tap FIR (finite impulse response) filter, with a number L filter tap elements (L=0, 1, 2, . . . (L?1)), each with an assigned coefficient from a defined coefficient sequence. The L-tap FIR filter is configurable with a defined zero-insertion coefficient sequence of a repeating sub-sequence of a nonzero coefficient followed by one or more zero-inserted coefficients, with a number Nj of nonzero coefficients, and a number Nk of zero-inserted coefficients, so that L=Nj+Nk. The L-tap FIR filter is configurable as an M-tap FIR filter with a nonzero coefficient sequence in which each of the L filter tap elements is assigned a non-zero coefficient, the M-tap FIR filter having an effective length of M=(Nj+Nk) non-zero coefficients.

Abstract: A device for computing the inner product of vectors includes a vector data arranger, a vector data pre-accumulator, a number converter, and a post-accumulator. The vector data arranger stores a first vector and sequentially outputs a plurality of vector data based on the first vector. The vector data pre-accumulator stores a second vector, receives each of the vector data, and pre-accumulates the second vector, so as to generate a plurality accumulation results. The number converter and the post-accumulator receive and process all the accumulation results corresponding to each of the vector data to generate an inner product value. The present invention implements a lookup table with the vector data pre-accumulator and the number converter to increase calculation speed and reduce power consumption.

Abstract: An aspect includes executing, by a binary based floating-point arithmetic unit of a processor, a calculation having two or more operands in hexadecimal format based on a hexadecimal floating-point (HFP) instruction and providing a condition code for a calculation result of the calculation. The floating-point arithmetic unit includes a condition code anticipator circuit that is configured to provide the condition code to the processor prior to availability of the calculation result.

Abstract: A convolutional operation device for performing convolutional neural network processing includes an input sharing network including first and second input feature map registers configured to shift each input feature map, which is inputted in row units, in a row or column direction and output the shifted input feature map and arranged in rows and columns, a first MAC array connected to the first input feature map registers, an input feature map switching network configured to select one of the first and second input feature map registers, a second MAC array connected to one selected by the input feature map switching network among the first and second input feature map registers, and an output shift network configured to shift the output feature map from the first MAC array and the second MAC array to transmit the shifted output feature map to an output memory.

Abstract: An apparatus and method for performing multiply-accumulate (MAC) operations on complex numbers to generate real results.

Abstract: A memory device is provided. The memory device includes: a cell region including a first metal pad, a memory cell in the cell region configured to store weight data, a peripheral region including a second metal pad and vertically connected to the memory cell by the first metal pad and the second metal pad, a buffer memory in the peripheral region configured to read the weight data from the memory cell, an input/output pad in the peripheral region configured to receive input data; and a multiply-accumulate (MAC) operator in the peripheral region configured to receive the weight data from the buffer memory and receive the input data from the input/output pad to perform a convolution operation of the weight data and the input data, wherein the input data is provided to the MAC operator during a first period, and wherein the MAC operator performs the convolution operation of the weight data and the input data during a second period overlapping with the first period.

Abstract: The multi-digit binary in-memory multiplication devices are disclosed. The multi-digit binary in-memory multiplication devices of the invention can dramatically reduce the operational steps in comparison with the conventional binary multiplier device. In one embodiment with the expense of more hardware, the in-memory multiplication device can achieve one single step operation. Consequently, the multi-digit binary in-memory multiplication device can improve the computation efficiency and save the computation power by eliminating the data transportations between Arithmetic Logic Unit (ALU), registers, and memory units.

Abstract: According to an embodiment, an arithmetic device includes a comparator, M cross switches, and M coefficient circuits. The comparator compares a first voltage generated at a first comparison terminal and a second voltage generated at a second comparison terminal. The M cross switches are provided corresponding to the M input signals. The M coefficient circuits are provided corresponding to the M coefficients, and each includes a first constant current source and a second constant current source. Each of the M cross switches performs switching between a straight state and a reverse state. In each of the M coefficient circuits, the first constant current source is connected between a positive output terminal of the corresponding coefficient circuit and a reference potential, and the second constant current source is connected between a negative output terminal of the corresponding coefficient circuit and the reference potential.

Abstract: Embodiments for implementing a fused multiply-multiply-accumulate (“FMMA”) unit by one or more processors in a computing system. Mantissas for two products, an exponent difference of the two products serving as an alignment shift amount for a product of the two products having a smallest exponent, and an alignment shift amount for an addend relative to an alternative product of the two product having a larger exponent may be determined in parallel. The addend may be aligned relative to the alternative product having the larger exponent. The product having the smallest exponent may be aligned relative to the alternative product having the larger exponent according to the alignment shift amount.