A device for performing a forward propagation process of an artificial neural network comprising a floating point data statistics module, a data conversion unit and a floating 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 artificial neural network, to obtain an offset of an exponent bit, offset, and a length of the exponent bit, EL; wherein the floating point data statistics module comprises a data extraction unit, a statistical unit, and an analysis unit, wherein the data extracting unit is used to extract the various types of data for the forward propagation process based on long-bit floating point data, the statistical unit is used to count the data range of a same type of data and the data distribution of each data segment, and the analysis unit is used to, based on the data range of a same type of data and the data distribution of each data segment counted by the statistical unit, obtain the offset of the exponent bit, offset, and the length of the exponent bit, EL, that should be set for each of the various types of data represented as the short-bit floating point data; wherein the long-bit floating point data is original floating point data, the short-bit floating point data means that the original floating point data is represented by fewer bits than the original floating point data; wherein the length of the exponent bit, EL, for each of the various types of data is set such that a representable data range comprises as much data as possible for this type of data; the data conversion unit is used to convert a long-bit floating-point data type to a short-bit floating-point data type, based on the offset of the exponent bit, offset, and the length of the exponent bit, EL, obtained by the floating point data statistics module; after inputs, weights, and/or biased data required for the forward propagation process of artificial neural network are represented as short-bit floating point data in the short-bit floating point data type, by the data conversion unit, the floating point data operation module is used to perform the forward propagation process of artificial neural network on the short-bit floating point data. 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 artificial neural network, to obtain an offset of an exponent bit, offset, and a length of the exponent bit, EL; wherein the floating point data statistics module comprises a data extraction unit, a statistical unit, and an analysis unit, wherein the data extracting unit is used to extract the various types of data for the forward propagation process based on long-bit floating point data, the statistical unit is used to count the data range of a same type of data and the data distribution of each data segment, and the analysis unit is used to, based on the data range of a same type of data and the data distribution of each data segment counted by the statistical unit, obtain the offset of the exponent bit, offset, and the length of the exponent bit, EL, that should be set for each of the various types of data represented as the short-bit floating point data; wherein the long-bit floating point data is original floating point data, the short-bit floating point data means that the original floating point data is represented by fewer bits than the original floating point data; wherein the data extracting unit is used to extract the various types of data for the forward propagation process based on long-bit floating point data, the statistical unit is used to count the data range of a same type of data and the data distribution of each data segment, and the analysis unit is used to, based on the data range of a same type of data and the data distribution of each data segment counted by the statistical unit, obtain the offset of the exponent bit, offset, and the length of the exponent bit, EL, that should be set for each of the various types of data represented as the short-bit floating point data; wherein the long-bit floating point data is original floating point data, the short-bit floating point data means that the original floating point data is represented by fewer bits than the original floating point data; wherein the length of the exponent bit, EL, for each of the various types of data is set such that a representable data range comprises as much data as possible for this type of data; the data conversion unit is used to convert a long-bit floating-point data type to a short-bit floating-point data type, based on the offset of the exponent bit, offset, and the length of the exponent bit, EL, obtained by the floating point data statistics module; after inputs, weights, and/or biased data required for the forward propagation process of artificial neural network are represented as short-bit floating point data in the short-bit floating point data type, by the data conversion unit, the floating point data operation module is used to perform the forward propagation process of artificial neural network on the short-bit floating point data.