Samsung Electronics Co., Ltd.

Minje Kim

Soonwan Kwon

Sang Joon Kim

Sangjoon Kim

Soon-Wan Kwon

A neural network apparatus includes: a first processing circuit and a second processing circuit each configured to perform a vector-by-matrix multiplication (VMM) operation on a weight and an input activation; a first register configured to store an output of the first processing circuit; an adder configured to add an output of the first register and an output of the second processing circuit; a second register configured to store an output of the adder; and an input circuit configured to input a same input activation to the first processing circuit and the second processing circuit and control the first processing circuit and the second processing circuit.

Apparatus and method with neural network operations

A neural network apparatus performs multiply-accumulate (MAC) operations with respect to fractions of weights and input activations in a block floating-point format by using an analog crossbar array, performs addition operations with respect to shared exponents of weights and input activations in a block floating-point format by using a digital computing circuit, and outputs a partial sum of floating-point output activations by combining the result of the MAC operations and the result of the addition operations.

Neural network apparatus performing floating-point operation and operating method of the same

A neural network device includes a shift register circuit, a control circuit, and a processing circuit. The shift register circuit includes registers configured to, in each cycle of cycles, transfer stored data to a next register and store new data received from a previous register to a current register. The control circuit is configured to sequentially input data of input activations included in an input feature map into the shift register circuit in a preset order. The processing circuit, includes crossbar array groups that receive input activations from at least one of the registers and perform a multiply-accumulate (MAC) operation with respect to the received input activation and weights, is configured to accumulate and add at least some operation results output from the crossbar array groups in a preset number of cycles to obtain an output activation in an output feature map.

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Hwaseong-si, South Korea

Minje Kim