With this program, the National Science Foundation has challenged the scientific community to help solve the problem of energy efficient computing. Data centers around the world spend almost equal amount of overhead power in cooling and power conversion for every Watt of computation. As society's appetite for information continues to grow, data centers will eventually consume a significant portion of the world's electricity. Today, the entire information technology industry relies on digital electronics, i.e. electrons carrying digital bits, which impose a barrier for how efficient a computational task can be, regardless of how brilliantly software routines can be engineered. This project will explore the physics of lightwaves to craft a "photonic" processor that breaks that efficiency barrier. This interdisciplinary endeavor will attempt to generate foundational science which will support future innovation in the tech industry. To the end of help building the workforce for the future, the investigators will continue their commitments in mentoring graduate and undergraduate students, and support broadening participation of women, minorities and underrepresented groups through STEM outreach, and NSF REU sites.
The approach unites neuromorphic (neural network-inspired) architectures, nanophotonic devices, and emerging fabrication platforms. The technical challenge requires vertical integration of new optical devices, logic units, and control software. It utilizes diverse expertise of faculty members in nanophotonic devices, photonic systems and computer engineering. Specifically, the key points of innovation will include: 1) ultra-efficient electro-optic modulators that will act as neurons at the nanoscale; 2) reconfigurable hardware interconnection fabric on-chip that uses light as information carrier; and 3) creation of control software and benchmarks that are required to orient the project within the broader field of efficient computing. A strong experimental thrust to design, build, and demonstrate these proposed systems will serve to reduce the risk of development of this technology and pave the way for other researchers to join the emerging field of nanophotonic neuromorphic computing.
