Researchers at the University of California, Davis, have developed a new computing and signal processing platform based on nanophotonics and nanoelectronics to decrease power consumption and improve overall computing speed with all-optical inputs and outputs.
Conventional computing, telecom, and signal processing systems utilize technologies that are susceptible to typical electronic pitfalls such as high power consumption and limited operation speed. Although other technologies, like machine learning systems and neuromorphic computing systems, are effective, they are susceptible to these same issues, which continue to reduce overall efficiency.
Researchers at the University of California, Davis have developed a novel computing and signal processing platform to significantly reduce power consumption and overall computing speed. This new method employs nanophotonics integrated with nanoelectronics to allow for all-optical inputs and outputs. By using all optical connections, the platform eliminates the impedance problems caused by electronic circuits. Additionally, the speed of processors and memory is improved while power consumption is reduced by 1000x compared to other electronic approaches.
neuromorphic, signal processing, nanoelectronics, nanophotonics, power consumption, machine learning, computing systems