Fields ranging from autonomous driving to personalized medicine are generating huge amounts of data. But just as the flood of data is reaching massive proportions, the ability of computer chips to process it into useful information is stalling.
Computers today comprise different chips cobbled together. There is a chip for computing and a separate chip for data storage, and the connections between the two are limited. As applications analyze increasingly massive volumes of data, the limited rate at which data can be moved between different chips is creating a critical communication bottleneck. With limited area on a chip, there is not enough room to place them side-by-side, even as they have been miniaturized.
A new prototype chip uses multiple nanotechnologies, together with a new computer architecture. Instead of relying on silicon-based devices, the chip uses carbon nanotubes — sheets of 2D graphene formed into nanocylinders — and resistive random access memory (RRAM) cells, a type of nonvolatile memory that operates by changing the resistance of a solid dielectric material. More than 1 million RRAM cells and 2 million carbon nanotube field-effect transistors were integrated in this work, making a complex nanoelectronic system.
The RRAM and carbon nanotubes are built vertically over one another, making a dense 3D computer architecture with interleaving layers of logic and memory. By inserting ultra-dense wires between these layers, this 3D architecture promises to address the communication bottleneck. Such an architecture is not possible with existing silicon-based technology. Carbon nanotube circuits and RRAM memory, however, can be fabricated at much lower temperatures — below 200 °C — enabling them to be built up in layers without harming the circuits beneath. The chip can store massive amounts of data and perform on-chip processing to transform a data deluge into useful information.
To demonstrate the potential of the technology, more than 1 million carbon nanotube-based sensors were placed over the top layer of the chip, which was used to detect and classify ambient gases.
Due to the layering of sensing, data storage, and computing, the chip measured each of the sensors in parallel, and then wrote directly into its memory, generating huge bandwidth. So, for example, the devices could be used to detect signs of disease by sensing compounds in a patient’s breath.