New 3D chip

As embedded intelligence is finding its way into ever more areas of our lives, 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.

Now, researchers at Stanford University and MIT have built a new chip to overcome this hurdle. The results are published today in the journal Nature, by lead author Max Shulaker, an assistant professor of electrical engineering and computer science at MIT. Shulaker began the work as a PhD student alongside H.-S. Philip Wong and his advisor Subhasish Mitra, professors of electrical engineering and computer science at Stanford. The team also included professors Roger Howe and Krishna Saraswat, also from Stanford. The new prototype chip is a radical change from today’s chips. It uses multiple nanotechnologies, together with a new computer architecture, to reverse both of these trends.

Instead of relying on silicon-based devices, the chip uses carbon nanotubes, which are 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. The researchers integrated over 1 million RRAM cells and 2 million carbon nanotube field-effect transistors, making the most complex nanoelectronic system ever made with emerging nanotechnologies. The RRAM and carbon nanotubes are built vertically over one another, making a new, dense 3D computer architecture with interleaving layers of logic and memory. By inserting ultradense wires between these layers, this 3D architecture promises to address the communication bottleneck.

To demonstrate the potential of the technology, the researchers took advantage of the ability of carbon nanotubes to also act as sensors. On the top layer of the chip they placed over 1 million carbon nanotube-based sensors, which they used to detect and classify ambient gases. Due to the layering of sensing, data storage, and computing, the chip was able to measure each of the sensors in parallel, and then write directly into its memory, generating huge bandwidth, Shulaker says. Three-dimensional integration is the most promising approach to continue the technology scaling path set forth by Moore’s laws, allowing an increasing number of devices to be integrated per unit volume, according to Jan Rabaey, a professor of electrical engineering and computer science at the University of California at Berkeley, who was not involved in the research.

The team is working to improve the underlying nanotechnologies, while exploring the new 3D computer architecture. For Shulaker, the next step is working with Massachusetts-based semiconductor company Analog Devices to develop new versions of the system that take advantage of its ability to carry out sensing and data processing on the same chip. So, for example, the devices could be used to detect signs of disease by sensing particular compounds in a patient’s breath, says Shulaker. This work was funded by the Defense Advanced Research Projects Agency, the National Science Foundation, Semiconductor Research Corporation, STARnet SONIC, and member companies of the Stanford SystemX Alliance.