Study examines photonics for AI and neuromorphic computing
Engineering360 News Desk | February 04, 2021A team of scientists from the University of Exeter, Queen’s University (Canada), Princeton University and University of Münster have investigated the future potential for computer systems to use photonics in lieu of conventional electronics.
The research examines some of the potential solutions for determining how to develop computing technologies to process data in a fast and energy efficient way.
Modern-day computers are based on the von Neumann architecture wherein the fast central processing unit (CPU) is physically separated from the much slower program and data memory. This means computing speed is limited and power is wasted by the need to continuously transfer data to and from the memory and processor over bandwidth-limited and energy-inefficient electrical interconnects — known as the von Neumann bottleneck.
Consequently, it has been estimated that more than 50% of the power of modern computing systems is wasted simply in this moving around of data.
Professor C David Wright, from the University of Exeter’s Department of Engineering and one of the co-authors of the study, explained: “Clearly, a new approach is needed — one that can fuse together the core information processing tasks of computing and memory, one that can incorporate directly in hardware the ability to learn, adapt and evolve, and one that does away with energy-sapping and speed-limiting electrical interconnects.”
Photonic neuromorphic computing is one such approach. Here, signals are communicated and processed using light rather than electrons, giving access to much higher bandwidths (processor speeds) and vastly reducing energy losses.
Further, the researchers attempted to make the computing hardware itself isomorphic with biological processing systems (brains), by developing devices to directly mimic the basic functions of brain neurons and synapses, then connecting these together in networks that can offer fast, parallelized, adaptive processing for artificial intelligence (AI) and machine learning applications.
The state-of-the-art of such photonic ‘brain-like’ computing, and its likely future development, is the focus of a paper titled: “Photonics for artificial intelligence and neuromorphic computing,” which appears in the journal Nature Photonics.