The old promise of Moore’s Law is simple: Every two years, the future will arrive in the form of faster microchips. For decades, the semiconductor industry delivered that progress. But that era is fading. Today, performance gains are harder to achieve, energy demands are surging, and the idea of a single chip doing everything well is starting to break down.
That is the world Aman Arora is working in and pushing forward.
Arora is an assistant professor of computer science and engineering in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University. His research in reconfigurable computing sees the next wave of artificial intelligence, or AI, acceleration not in costly, hotter general-purpose processors, but in hardware that can be targeted to the task at hand.
Arora’s tool of choice is the field-programmable gate array, or FPGA, chip, which can be reshaped after it leaves the factory.
“Think of an FPGA as a giant breadboard, an electronics platform where you can wire components together, shrunk down into a tiny chip,” Arora says. “You can connect different components however you want, and it becomes whatever kind of circuit you need.”