Architecture of a computer for calculating a convolution layer in a convolutional neural network

A computer (CONV) for computing a convolutional layer of an artificial neural network, comprising at least one set (PE_BLOC) of at least two partial sum computing modules (PE_POOL1,PE_POOL2,PE_POOL3) connected in series, a storage member (W_MEM) for storing the coefficients of at least one convolution filter, each partial sum computing module (PE_POOL2) comprising at least one computing unit (PE0,PE1) configured so as to carry out a multiplication of an item of input data of the computer and a coefficient of a convolution filter, followed by an addition of the output of the preceding partial sum computing module (PE_POOL1) in the series or of a predefined value for the first partial sum computing module (PE_POOL1) in the series, each set (PE_BLOC) furthermore comprising, for each partial sum computing module except the first in the series, a shift register connected at input for storing the item of input data for the processing duration of the preceding partial sum computing modules in the series, the computer (CONV) furthermore comprising at least one accumulator connected at output of each set (PE_BLOC) and a memory (RAM), the input data of the computer coming from at least two input matrices, each partial sum computing module (PE_POOL) being configured so as to receive, at input, the input data belonging to different input matrices and having the same coordinates in each input matrix.