A device for performing a forward propagation process of an artificial neural network, the device comprising a floating point data statistics module, a data conversion unit and a fixed point data operation module, wherein the floating point data statistics module is used to perform a statistical analysis on various types of data required for the forward propagation process of the artificial neural network to obtain a decimal point location; wherein the floating point data statistics module includes a data extraction unit, a statistical unit, and an analysis unit, wherein the data extracting unit is configured to extract the various types of data in the forward propagation process based on a long-bit floating point data, the statistical unit is configured to count a data range for a same type of data and a data distribution of each data segment, wherein the same type of data is concentrated in the data range, and the analysis unit is configured to obtain the decimal point location that should be set for each type of data with a fixed bit fixed point according to the results counted by the statistics unit; the data conversion unit is used to convert a long-bit floating-point data type to a short-bit fixed-point data type according to the decimal point location obtained by the floating point data statistics module; the fixed point data operation module is used to perform an artificial neural network forward propagation process on the short-bit fixed point data after the data conversion unit using the short-bit fixed point data type to represent all the input, weight, and/or biased data required in the forward propagation process of artificial neural network; wherein the long-bit floating point data is original floating point data, the short-bit fixed point data means that the short-bit fixed point data is represented by fewer bits than the original floating point data; wherein a short-bit fixed point data structure for storing the short-bit fixed point data comprises: one bit for storing a sign of the short-bit fixed point data, M bits for storing an integer part of the short-bit fixed point data, and N bits for storing a fractional part of the short-bit fixed point data; wherein a representation form of the short-bit fixed point data sets a symbol bit Point location to record the decimal point location for data of a same layer, a same type in the artificial neural network, for adjusting an accuracy and a representable data range of a data representation according to the data distribution. the floating point data statistics module is used to perform a statistical analysis on various types of data required for the forward propagation process of the artificial neural network to obtain a decimal point location; wherein the floating point data statistics module includes a data extraction unit, a statistical unit, and an analysis unit, wherein the data extracting unit is configured to extract the various types of data in the forward propagation process based on a long-bit floating point data, the statistical unit is configured to count a data range for a same type of data and a data distribution of each data segment, wherein the same type of data is concentrated in the data range, and the analysis unit is configured to obtain the decimal point location that should be set for each type of data with a fixed bit fixed point according to the results counted by the statistics unit; the data conversion unit is used to convert a long-bit floating-point data type to a short-bit fixed-point data type according to the decimal point location obtained by the floating point data statistics module; the fixed point data operation module is used to perform an artificial neural network forward propagation process on the short-bit fixed point data after the data conversion unit using the short-bit fixed point data type to represent all the input, weight, and/or biased data required in the forward propagation process of artificial neural network; wherein the long-bit floating point data is original floating point data, the short-bit fixed point data means that the short-bit fixed point data is represented by fewer bits than the original floating point data; wherein a short-bit fixed point data structure for storing the short-bit fixed point data comprises: one bit for storing a sign of the short-bit fixed point data, M bits for storing an integer part of the short-bit fixed point data, and N bits for storing a fractional part of the short-bit fixed point data; wherein a representation form of the short-bit fixed point data sets a symbol bit Point location to record the decimal point location for data of a same layer, a same type in the artificial neural network, for adjusting an accuracy and a representable data range of a data representation according to the data distribution. one bit for storing a sign of the short-bit fixed point data, M bits for storing an integer part of the short-bit fixed point data, and N bits for storing a fractional part of the short-bit fixed point data; wherein a representation form of the short-bit fixed point data sets a symbol bit Point location to record the decimal point location for data of a same layer, a same type in the artificial neural network, for adjusting an accuracy and a representable data range of a data representation according to the data distribution.