A system for data processing in a neural network, the system comprising: at least one processor; and at least one memory in communication with the at least one processor, the at least one memory having computer-readable instructions stored thereupon, which, when executed by the at least one processor, cause the at least one processor to: retrieve a first weight value associated with a first kernel of a plurality of kernels of the neural network; retrieve a second weight value associated with a second kernel of the plurality of kernels of the neural network; wherein each of the first kernel and the second kernel include a plurality of weight value holding positions each holding a weight value, the first weight value associated with a first holding position of the first kernel and the second weight value associated with a first holding position of the second kernel, wherein the first holding position of the first kernel is spatially equivalent to the first holding position of the second kernel; determine that the first weight value and the second weight value are equal, store the first kernel and the second kernel in one or more storage devices such that the second kernel is processed consecutively to the first kernel to reduce bit flipping associated with the neural network during execution of an operation on at least one input data value; perform the operation on the at least one input data value. at least one processor; and at least one memory in communication with the at least one processor, the at least one memory having computer-readable instructions stored thereupon, which, when executed by the at least one processor, cause the at least one processor to: retrieve a first weight value associated with a first kernel of a plurality of kernels of the neural network; retrieve a second weight value associated with a second kernel of the plurality of kernels of the neural network; wherein each of the first kernel and the second kernel include a plurality of weight value holding positions each holding a weight value, the first weight value associated with a first holding position of the first kernel and the second weight value associated with a first holding position of the second kernel, wherein the first holding position of the first kernel is spatially equivalent to the first holding position of the second kernel; determine that the first weight value and the second weight value are equal, store the first kernel and the second kernel in one or more storage devices such that the second kernel is processed consecutively to the first kernel to reduce bit flipping associated with the neural network during execution of an operation on at least one input data value; perform the operation on the at least one input data value. retrieve a first weight value associated with a first kernel of a plurality of kernels of the neural network; retrieve a second weight value associated with a second kernel of the plurality of kernels of the neural network; wherein each of the first kernel and the second kernel include a plurality of weight value holding positions each holding a weight value, the first weight value associated with a first holding position of the first kernel and the second weight value associated with a first holding position of the second kernel, wherein the first holding position of the first kernel is spatially equivalent to the first holding position of the second kernel; determine that the first weight value and the second weight value are equal, store the first kernel and the second kernel in one or more storage devices such that the second kernel is processed consecutively to the first kernel to reduce bit flipping associated with the neural network during execution of an operation on at least one input data value; perform the operation on the at least one input data value.