The Revolution of Optical AI Processors

Computer Memory Matrix Circuit Art Illustration

Nathan Youngblood, an assistant professor at the University of Pittsburgh, has been awarded grants from the NSF and AFOSR to advance his research in optical computing and phase-change materials. His work aims to tackle the constraints of current computing hardware by developing more effective, dependable, and rapid optical computing systems. This research not only pledges to boost AI’s computational power but also to enhance the speed and efficiency of modern computing systems. Credit: SciTechDaily.com

Nathan Youngblood of the University of Pittsburgh is leading optical computing to enhance AI and computing efficiency, backed by substantial grants and concentrating on forming a varied tech workforce.

The skyrocketing demand for high computing power is far outstripping the capacities of current electronic systems; nevertheless, engineers at the University of Pittsburgh are spotlighting new solutions.

Nathan Youngblood, chief investigator and assistant professor of electrical and computer engineering at Pitt’s Swanson School of Engineering, secured a $552,166 Faculty Early Career Development Award from the National Science Foundation (NSF) and a $449,240 grant from the Air Force Office of Scientific Research (AFOSR) through its Young Investigator Program (YIP) to prolong his pioneering work in phase-change materials and optical computing.
“Dr. Youngblood is a rising star and one of the finest young researchers, scholars, and educators at Pitt Engineering,” said Alan George, Department Chair, R&H Mickle Endowed Chair, and Professor of Electrical and Computer Engineering and SHREC founder. “His two latest achievements – the CAREER Award and the AFOSR Young Investigator Award – are genuinely exceptional, and we are so proud of him and enthusiastic about his burgeoning research program and group of students.”

Photonic computing, also known as photonic computing, has presented potential over traditional hardware by employing light waves produced by lasers or other sources for data storage, data processing, or data communication for computing. However, current technology limits its practicality.

With these grants, Youngblood will be examining two different approaches to enhance the speed, reliability, and efficiency of optical computing. The first approach centers on utilizing the wave-like nature of light to boost the efficiency of optical computing, while the second concentrates on enhancing optical memories to heighten computational throughput.

Computing in the Realm of AI

For his CAREER Award, Youngblood will focus on shaping high-efficiency optical computing hardware to confront critical challenges of artificial intelligence (AI).

“As AI applications services continue to rise in prominence, we need the computing power to be able to support them,” Youngblood said. “There have been significant advancements in modern computers, but gains in traditional hardware efficiency are unable to keep pace with these data-hungry systems. Optical computing makes it possible.”

When current computing methods attempt to meet the demands of AI, unwanted heat is created due to the massive amounts of data moving at high speeds through the metal wires of the processor.

“Photons don’t have this heating issue, so you can process data much faster using light,” Youngblood explained. “Right now, however, optical processors aren’t powerful enough, accurate enough, or efficient enough to be genuinely beneficial for AI.”

Thanks to funding through Pitt’s Momentum Funds, Youngblood was able to secure an initial seeding grant and preliminary data for his CAREER Award.

“I’m incredibly grateful for Pitt’s help in jumpstarting this research,” Youngblood said.

An Upgrade in Modern Computing

It’s reasonably apparent modern computing systems have reached their limit.

Current computer hardware is hampered by the transfer of data between memory and processing cores, reducing computing speeds and generating undesirable heat in the machine.

Through the Young Investigator Program, Youngblood will produce photonic hardware that enables computation to occur in the optical memory array itself, considerably lessening the movement of data. His lab will undertake research in three primary thrusts: enhancing the efficiency, reliability, and repeatability of electrically programmable phase-change photonic memory; designing fully analog multilayer photonic networks for fast and efficient computing; and demonstrating a multi-layer, fully analog photonic in-memory accelerator on chip.

The outcomes of this work will advance the development of unique materials for reconfigurable photonic devices and integrate these components into optoelectronic computational systems.

“The resulting platform is expected to have a substantial impact for Air and Space Force applications requiring ultra-low latency computation, target discrimination, and autonomous navigation where there is an immediate need for extremely high-speed information processing,” Youngblood said.

The project, “Photonic in-memory accelerators for low-latency and efficient computing,” is part of the $21.5 million given to YIP recipients who receive three-year grants of up to $450,000. Individuals chosen must show extraordinary ability and promise for conducting basic research of the Department of the Air Force relevance.

In addition to the scientific contributions to the next step in optical and modern computing, Youngblood’s CAREER award will also assist him in cultivating a diverse high-tech workforce in the greater Pittsburgh area. Initiatives include creating affordable educational tools exposing students to nanotechnology applications in AI, conducting 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.

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