Abstract: A system for providing efficient-hardware accelerated neural network convolution is disclosed. The system receives an input image for an artificial intelligence task for a deep learning accelerator. The system divides the image in to equally-sized partially overlapping image patches and applies a Fast Fourier Transform to the image patches. A size of an image filter is padded to match a size of the image patches and a Fast Fourier Transform to applied to the image filter. For each pixel in each patch, a matrix-vector product is computed between channels of each image patch and a matrix from a corresponding pixel location in the image filter. An inverse Fast Fourier Transform is applied to the matrix-vector product to convert each image to the spatial domain. A convolved version of the image is reconstructed by summing overlapping edges of the patches or by discarding overlapping regions of the patches.