The application provides a neural network-oriented accelerator, which comprises a main
processing core, an input buffer, a controller, a main
systolic array and an output buffer, the input buffer is used for storing feature maps and weight parameters of a neural network, the controller is used for generating operation signals to read the feature maps and the weight parameters from the input buffer, the main
systolic array is used for receiving the feature maps and the weight parameters and performing calculation to obtain an output sequence; a sorter is used for reordering each element in the output sequence to select a to-be-detected sequence, a
lockstep processing core is used for recalculating the value of each element in the to-be-detected sequence through a
lockstep systolic array to obtain a check sequence; a check
logic module is used for comparing whether the values of the same elements in the to-be-detected sequence and the check sequence are the same; and an error
recovery module is used for recalculating the values of all elements in the to-be-detected sequence that do not pass the check according to a preset recalculation mechanism.