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Broadening horizons of cutting-edge computing

Providing computational prowess to propel ambitious high-tech pursuits

by | Apr 14, 2022 | Faculty, Features

Ira A. Fulton Schools of Engineering Assistant Professor Deliang Fan has earned National Science Foundation support for his electrical and computer engineering research to advance the emerging field of hybrid in-memory computing systems. Those systems promise more robust performance in many areas of technology, including robotics, autonomous automobiles and computer vision. Photographer: Erika Gronek/ASU
The National Science Foundation grants the Faculty Early Career Development Program (CAREER) Award to early-career faculty members who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.

Eleven faculty members in the Ira A. Fulton Schools of Engineering at Arizona State University have received NSF CAREER Awards in 2022.

Deliang Fan has nothing less than bold expectations for his endeavors to expand the capabilities of computing systems and technologies. His far-reaching aspirations involve designing advanced computational hardware to help innovate in some of the most technologically complex areas of engineering and science.

He especially wants to make significant advances in high-performance, energy-efficient computing for big data processing and make big steps in developing more vigorous artificial intelligence, or AI, computing.

Fan, an electrical and computer engineer and assistant professor in the Ira A. Fulton Schools of Engineering  at Arizona State University, says his ultimate goal is to “design, implement and conduct the experimentation to validate the performance of a new hybrid in-memory computing system.”

In-memory computing is a way of running computer calculations entirely in computer memory. For example, random-access memory, or RAM, is short-term memory where data is stored as needed by a computer’s processor.

“The key concept is to leverage the memory device or circuit properties to implement logic functions within a memory array to directly process stored data,” Fan says, “and to do this without moving data to a separate central logic unit, thus minimizing energy-dominating data communication.”

The idea, he says, is to “optimize energy efficiency, inference accuracy, spatiotemporal dynamics, robustness and on-device learning, which will greatly advance AI-based big data processing fields such as computer vision, autonomous driving and robotics.”

Based on his progress so far, the National Science Foundation, or NSF, is convinced Fan is prepared to take on these formidable challenges. He was recently given a 2022 National Science Foundation NSF CAREER Award that will provide $500,000 over five years to fund his research.

The CAREER Award program supports university faculty members early in their careers who are deemed to have the potential to excel in both research and education, to serve as role models in their academic departments and to lead advances in fields in which progress will serve national interests and priorities.

Fan’s Efficient, Secure and Intelligent Computing Laboratory team is attempting to build “a revolutionary and ultra-efficient ‘AI-in-memory’ computing system that could execute AI computation directly within the memory where the data is stored, without the massive data movement,” says Fan, who teaches in the School of Electrical, Computer and Energy Engineering, one of the seven Fulton Schools.

If the project is successful, it will provide a new kind of in-memory computing architecture that will operate faster and be a hundred times more energy efficient than current state-of-the-art central processing units or graphics processing units.

“This tiny but powerful computing system will bring computing solutions to the existing smart Internet of Things technologies, robots, self-driving cars, smart connected health technologies, on-device learning capability and many others things,” Fans says. “It will provide a much cheaper, faster and low-power AI computing platform.”

The project will include extensive educational components. Fan plans to recruit both undergraduate and graduate students to participate in conducting research for the project.

More educational efforts will be made through multiple K-12 STEM outreach programs designed to help younger students learn the basics about computer engineering and AI fields.

In addition, a new course in the growing area of in-memory computing is being developed, with plans to offer the course in the School of Electrical, Computer and Energy Engineering.

About The Author

Joe Kullman

Joe Kullman is a science writer for the Ira A. Fulton Schools of Engineering. Before joining Arizona State University in 2006, Joe worked as a reporter, writer and editor for newspapers and magazines dating back to the dawn of the age of the personal computer. He began his career while earning degrees in journalism and philosophy from Kent State University in Ohio. Media Contact: [email protected] | 480-965-8122 | Ira A. Fulton Schools of Engineering Communications

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