A figure depicting the structure of stacked memristors with dimensions that could satisfy the Feynman Grand Challenge
In 1959 Richard Feynman, in his talk “Plenty of Room at the Bottom,” spoke of a future in which tiny machines could perform huge feats. Like many forward-looking concepts, his molecule and atom-sized world remained for years in the realm of science fiction. And then, scientists and other creative thinkers began to realize Feynman’s nanotechnological visions. In the spirit of Feynman’s insight engineers at UC Santa Barbara have developed a design for a functional nanoscale computing device. The concept involves a dense, 3D circuit operating on an unconventional type of logic that could, theoretically, be packed into a block no bigger than 50 nm on any side.
Key to this development is the use of a logic system called material implication logic combined with memristors—circuit elements whose resistance depends on the most recent charges and the directions of those currents that have flowed through them. Unlike the conventional computing logic and circuitry in current computers and other devices, in this form of computing, logic operation and information storage happen simultaneously and locally. This greatly reduces the need for components and space typically used to perform logic operations and to move data back and forth between operation and memory storage. The result of the computation is immediately stored in a memory element, which prevents data loss in the event of power outages—a critical function in autonomous systems such as robotics.
In addition, they reconfigured the traditionally 2D architecture of the memristor into a 3D block, which could then be stacked and packed into the space required to meet the Feynman Grand Prize Challenge. “Previous groups show that individual blocks can be scaled to very small dimensions, let’s say 10-by-10 nanometers,” said Strukov, who worked at technology company Hewlett-Packard’s labs when they ramped up development of memristors and material implication logic. By applying those results to his group’s developments, he said, the challenge could easily be met.
The tiny memristors are being heavily researched in academia and in industry for memory storage and neuromorphic computing. While implementations of material implication logic are rather exotic and not yet mainstream, uses for it could pop up any time, particularly in energy scarce systems such as robotics and medical implants. “Since this technology is still new, more research is needed to increase its reliability and lifetime and to demonstrate large scale three-dimensional circuits tightly packed in tens or hundreds of layers,” Adam said.
http://www.news.ucsb.edu/2016/017349/tiny-machine
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