An integrated circuit including a data architecture including N adders and N multipliers configured to receive operands. The data architecture receives instructions for selecting a data flow between the N multipliers and the N adders of the data architecture. The selected data flow includes the options: (1) a first data flow using the N multipliers and the N adders to provide a multiply-accumulate mode and (2) a second data flow to provide a multiply-reduce mode.

This disclosure relates to an adder circuit. The adder circuit comprises an operand input and a second operand input to an XNOR cell. The XNOR cell may be configured to provide the operand input and the second operand input to both a NAND gate and a first OAI cell. A second OAI cell may transform the output of the XNOR cell into a carry out signal.

In some example embodiments a logical block comprising twelve inputs and two six-input lookup tables (LUTs) is provided, wherein four of the twelve inputs are provided as inputs to both of the six-input lookup tables. This configuration supports efficient field programmable gate array (FPGA) implementation of multipliers. Each six-input LUT comprises two five-input lookup tables (LUT5s) that are used to form Booth encoding multiplier building blocks. The five inputs to each LUT5 are two bits from a multiplier and three Booth-encoded bits from a multiplicand. By assembling building blocks, multipliers of arbitrary size may be formed.

In some example embodiments a logical block comprising twelve inputs and two six-input lookup tables (LUTs) is provided, wherein four of the twelve inputs are provided as inputs to both of the six-input lookup tables. This configuration supports efficient field programmable gate array (FPGA) implementation of multipliers. Each six-input LUT comprises two five-input lookup tables (LUT5s) that are used to form Booth encoding multiplier building blocks. The five inputs to each LUT5 are two bits from a multiplier and three Booth-encoded bits from a multiplicand. By assembling building blocks, multipliers of arbitrary size may be formed.

An ALU is capable of generating a multiply accumulation by compressing like-magnitude partial products. Given N pairs of multiplier and multiplicand, Booth encoding is used to encode the multipliers into M digits, and M partial products are produced for each pair of with each partial product in a smaller precision than a final product. The partial products resulting from the same encoded multiplier digit position, are summed across all the multiplies to produce a summed partial product. In this manner, the partial product summation operations can be advantageously performed in the smaller precision. The M summed partial products are then summed together with an aggregated fixup vector for sign extension. If the N multipliers equal to a constant, a preliminary fixup vector can be generated based on a predetermined value with adjustment on particular bits, where the predetermined value is determined by the signs of the encoded multiplier digits.

In an example, an apparatus comprises a plurality of execution units and logic, at least partially including hardware logic, to gate at least one of a multiply unit or an accumulate unit in response to an input of value zero. Other embodiments are also disclosed and claimed.

The present disclosure discloses a processing element and a neural processing device including the processing element. The processing element includes a weight register configured to store a weight, an input activation register configured to store input activation, a flexible multiplier configured to generate result data by performing a multiplication operation of the weight and the input activation by using a first multiplier of a first precision or using both the first multiplier and a second multiplier of the first precision in response to a calculation mode signal and a saturating adder configured to generate a partial sum by using the result data.

The present disclosure discloses a processing element and a neural processing device including the processing element. The processing element includes a weight register configured to store a weight, an input activation register configured to store input activation, a flexible multiplier configured to generate result data by performing a multiplication operation of the weight and the input activation by using a first multiplier of a first precision or using both the first multiplier and a second multiplier of the first precision in response to a calculation mode signal and a saturating adder configured to generate a partial sum by using the result data.

An apparatus and method for efficiently performing a multiply add or multiply accumulate operation. For example, one embodiment of a processor comprises: a decoder to decode an instruction specifying an operation, the instruction comprising a first operand identifying a multiplier and a second operand identifying a multiplicand; and fused multiply-add (FMA) execution circuitry comprising first multiplication circuitry to perform a multiplication using the multiplicand and multiplier to generate a result for multipliers and multiplicands falling within a first precision range, and second multiplication circuitry to be used instead of the first multiplication circuitry for multipliers and multiplicands falling within a second precision range.

In an example, an apparatus comprises a plurality of execution units and logic, at least partially including hardware logic, to gate at least one of a multiply unit or an accumulate unit in response to an input of value zero. Other embodiments are also disclosed and claimed.