arXiv subjects
Publications and source records attributed to Nick New.
Modern hardware designs for AI and cryptography treat data transit and processing separately. At Optalysys we have demonstrated programmable Photonic hardware that computes mathematical functions on data that is in transit, enabling tens of GFLOPs of operations on data links.
The Convolutional Neural Network (CNN) is a state-of-the-art architecture for a wide range of deep learning problems, the quintessential example of which is computer vision. CNNs principally employ the convolution operation, which can be accelerated using the Fourier transform. In this paper, we present an optical hardware accelerator that combines silicon photonics and free-space optics, leveraging the use of the optical Fourier transform within several CNN architectures. The hardware presented is a proof of concept, demonstrating that this technology can be applied to artificial intelligence problems with a large efficiency boost with respect to canonical methods.