A neural network operation module, comprising a storage unit configured to store input data, a neural network instruction, and an operation result, wherein the input data includes input neurons and weights; a mapping unit configured to process the input data after receiving the input data to obtain processed input data, wherein the processed input data includes processed input neurons and processed weights; an instruction control unit configured to obtain the neural network instruction from an instruction caching unit and decode the neural network instruction into a microinstruction executed by an operation unit; the operation unit configured to obtain the processed input neurons and the processed weights and then perform an artificial neural network operation on the processed input neurons and the processed weights according to the microinstruction to obtain the operation result; and an output caching unit configured to cache the operation result; the neural network operation module being characterized in that the mapping unit is configured to determine the position of the input neurons whose absolute value is greater than a first threshold, and to obtain connection data of input neurons, which is a string configured to represent the position of the input neurons whose absolute values is greater than the first threshold; the mapping unit is configured to determine the position of the weights whose absolute value is greater than a second threshold, and to obtain connection data of weights, which is a string configured to represent whether an input neuron and an output neuron are connected; the mapping unit is configured to obtain new connection data according to the connection data of weights and the connection data of input neurons, in which the new connection data represent the relationship between an output neuron and the input neurons whose absolute value is greater than the first threshold; the mapping unit is configured to obtain the processed input neurons and the processed weights according to the new connection data, the input data of input neurons and weights; and the mapping unit is configured to store the processed input neurons and the processed weights into the storage unit in a one-to-one corresponding format; wherein the mapping unit, the storage unit, the instruction control unit, the instruction caching unit, the operation unit, the output caching unit are hardware circuits. a storage unit configured to store input data, a neural network instruction, and an operation result, wherein the input data includes input neurons and weights; a mapping unit configured to process the input data after receiving the input data to obtain processed input data, wherein the processed input data includes processed input neurons and processed weights; an instruction control unit configured to obtain the neural network instruction from an instruction caching unit and decode the neural network instruction into a microinstruction executed by an operation unit; the operation unit configured to obtain the processed input neurons and the processed weights and then perform an artificial neural network operation on the processed input neurons and the processed weights according to the microinstruction to obtain the operation result; and an output caching unit configured to cache the operation result; the neural network operation module being characterized in that the mapping unit is configured to determine the position of the input neurons whose absolute value is greater than a first threshold, and to obtain connection data of input neurons, which is a string configured to represent the position of the input neurons whose absolute values is greater than the first threshold; the mapping unit is configured to determine the position of the weights whose absolute value is greater than a second threshold, and to obtain connection data of weights, which is a string configured to represent whether an input neuron and an output neuron are connected; the mapping unit is configured to obtain new connection data according to the connection data of weights and the connection data of input neurons, in which the new connection data represent the relationship between an output neuron and the input neurons whose absolute value is greater than the first threshold; the mapping unit is configured to obtain the processed input neurons and the processed weights according to the new connection data, the input data of input neurons and weights; and the mapping unit is configured to store the processed input neurons and the processed weights into the storage unit in a one-to-one corresponding format; wherein the mapping unit, the storage unit, the instruction control unit, the instruction caching unit, the operation unit, the output caching unit are hardware circuits.