Fault detectable and tolerant neural network

Abstract

A hardware neural network engine which uses checksums of the matrices used to perform the neural network computations. For fault correction, expected checksums are compared with checksums computed from the matrix developed from the matrix operation. The expected checksums are developed from the prior stage of the matrix operations or from the prior stage of the matrix operations combined with the input matrices to a matrix operation. This use of checksums allows reading of the matrices from memory, the dot product of the matrices and the accumulation of the matrices to be fault corrected without triplication of the matrix operation hardware and extensive use of error correcting codes. The nonlinear stage of the neural network computation is done using triplicated nonlinear computational logic. Fault detection is done in a similar manner, with fewer checksums needed and correction logic removed as compared to the fault correction operation.