CAREER: Multi-Dimensional Photonic Accelerators for Scalable and Efficient Computing

University Of Pittsburgh, Pittsburgh PA

Investigators

Abstract

Despite advances in parallel computing platforms such as graphics processing units (GPUs), the growing demand for high computing power in emerging artificial intelligence (AI) applications far exceeds hardware efficiency improvements in current electronic systems. Optical computing promises improved efficiency and speed over conventional computing hardware, but is currently limited by power consumption, precision, and scalability issues. This project aims to revolutionize the field of AI by addressing these outstanding issues in current photonic computing architectures, thus unleashing the advantages of photonic computing for AI. In this CAREER proposal, the PI plans to advance optical computing through: (1) integrating photonic circuits and image sensors, (2) demonstrating multi-dimensional photonic computing, and (3) developing a simulation framework for large-scale photonic neural networks. Beyond technical advancements, the project’s educational goals include cultivating a diverse high-tech workforce in Pittsburgh through affordable educational tools, annual STEM workshops, and mentoring undergraduate researchers. Voluntary assessments in collaboration with Pitt's Engineering Education Research Center will measure educational outcomes, providing quantifiable metrics for long-term impact. This project aims to address three major limitations of current photonic computing platforms—power hungry electrical readout, limited analog precision, and poor scalability—to enable a fast and efficient computing architecture which could transform the field of artificial intelligence (AI). Despite notable advances in parallel computing, gains in hardware efficiency are unable to keep pace with the growing demand for extremely high computing power required by emerging AI applications and services. This is primarily due to the fundamental trade-off between clock speed and computational efficiency in the electronic domain stemming from the capacitance and Joule heating of metal interconnects. The PI will address this fundamental issue by performing computation in the optical domain using multiple photonic degrees of freedom for improved compute efficiency and speed. In this CAREER proposal, the PI will create new knowledge and extend the boundaries of optical computing through three unified tasks which: (1) integrate photonics and image sensors for robust and scalable matrix operations; (2) demonstrate multi-dimensional photonic computing for complex-valued matrix operations; and (3) develop a simulation framework to model the compute efficiency and latency of the proposed hardware for large-scale deep neural networks. Beyond technical advancements, the PI aims to cultivate a diverse high-tech workforce in the greater Pittsburgh area. Initiatives include creating affordable educational tools exposing students to nanotechnology applications in AI, conducting annual STEM workshops in collaboration with Pitt's outreach program (LEAD), and mentoring undergraduate researchers through Pitt's EXCEL summer research program. Voluntary assessments will measure educational outcomes, providing quantifiable metrics for the project's broader impact on workforce diversity and innovation in AI. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.