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Analog Edge Inference with ReRAM


Abstract "As the demands of big data applications and deep learning continue to rise, the industry is increasingly looking to artificial intelligence (AI) accelerators. Analog in-memory computing (AiMC) with emerging nonvolatile devices enable good hardware solutions, due to its high energy efficiency in accelerating the multiply-and-accumulation (MAC) operation. Herein, an Applied Materials... » read more

Architecting Faster Computers


To create faster computers, the industry must take a major step back and re-examine choices that were made half a century ago. One of the most likely approaches involves dropping demands for determinism, and this is being attempted in several different forms. Since the establishment of the von Neumann architecture for computers, small, incremental improvements have been made to architectures... » read more

System Bits: April 8


Computers trained to design materials Researchers in the University of Missouri’s College of Engineering are applying deep learning technology to educate high-performance computers in the field of materials science, with the goal of having those computers design billions of potential materials. “You can train a computer to do what it would take many years for people to otherwise do,” ... » read more