Advanced memory devices emerge for AI
TORONTO — Resistive random access memory (ReRAM) and other emerging memory technologies have been getting a lot of attention in the past year as semiconductor companies look for ways to more efficiently deal with the requirements of artificial intelligence and neuromorphic computing.
At the International Electron Devices Meeting (IEDM) in San Francisco earlier this month, there were several papers presented that dealt with using emerging memory in neomorphic computing from companies the likes of IBM and various universities.
"The neuromorph crowd is excited about this type of thing," said Jim Handy, a veteran memory market watcher who is principal analyst at Objective Analysis. "I wouldn't say that any [the emerging memory technologies} stands out. They all have something. The question is who is going to get something meaningful to the market first."
Neuromorphic applications are designed to specifically mimic how the human brain learns and processes information, and ReRAM devices show promise for enabling high-density and ultimately scaled neuromorphic architectures because they are significantly smaller and more energy-efficient than current AI data centers. They also mimic the brain’s biological computation at the neuron and synaptic level.
"The real beauty is that it could dramatically reduce the price of an AI system and the power consumption," Handy said.
>> Continue reading this article on our sister site, EE Times: "Researchers Explore Emerging Memories for AI."