System Bits: April 22

A neuromorphic computing roadmap envisions an analog path to simulating the human brain, according to electrical engineering researchers at Georgia Tech; Stanford scientists help create a novel way to do time-lapse studies of crystallization they expect will lead to more flexible and effective electronic displays, circuits and pharmaceutical drugs.

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To mimic human cognition
In the field of neuromorphic engineering, researchers study computing techniques that could someday mimic human cognition and to this end, electrical engineers at the Georgia Institute of Technology recently published a “roadmap” that details innovative analog-based techniques that could make it possible to build a practical neuromorphic computer.

Georgia Tech professor Jennifer Hasler displays a field programmable analog array (FPAA) board that includes an integrated circuit with biological-based neuron structures for power-efficient calculation. Hasler’s research indicates that this type of board, which is programmable but has low power requirements, could play an important role in advancing neuromorphic computing. (Source: Georgia Tech)

Georgia Tech professor Jennifer Hasler displays a field programmable analog array (FPAA) board that includes an integrated circuit with biological-based neuron structures for power-efficient calculation. Hasler’s research indicates that this type of board, which is programmable but has low power requirements, could play an important role in advancing neuromorphic computing. (Source: Georgia Tech)

A core technological hurdle in this field involves the electrical power requirements of computing hardware. Although a human brain functions on a mere 20 watts of electrical energy, a digital computer that could approximate human cognitive abilities would require tens of thousands of integrated circuits (chips) and a hundred thousand watts of electricity or more – levels that exceed practical limits.

The Georgia Tech roadmap proposes a solution based on analog computing techniques, which require far less electrical power than traditional digital computing. The more efficient analog approach would help solve the daunting cooling and cost problems that presently make digital neuromorphic hardware systems impractical.

“To simulate the human brain, the eventual goal would be large-scale neuromorphic systems that could offer a great deal of computational power, robustness and performance,” said Jennifer Hasler, a professor in the Georgia Tech School of Electrical and Computer Engineering (ECE), who is a pioneer in using analog techniques for neuromorphic computing. “A configurable analog-digital system can be expected to have a power efficiency improvement of up to 10,000 times compared to an all-digital system.”

Ways to study,control crystallization
Sometimes engineers invent something before they fully comprehend why it works. To understand the “why,” they must often create new tools and techniques in a virtuous cycle that improves the original invention while also advancing basic scientific knowledge. This was the case about two years ago when Stanford engineers discovered how to make a more efficient type of “strained organic semiconductors” that carry currents faster, a big step toward producing flexible electronic devices that couldn’t be built using rigid silicon chips.

Researchers dissolved organic molecules into a solution and deposited this liquid onto a flat surface. Their innovation was how they controlled the process through which those organic molecules assembled and crystallized as the liquid evaporated. The team wanted to understand why their process created such an electronically useful crystal lattice so they launched a new experiment with help from an organic thin film characterization expert from King Abdullah University of Science and Technology (KAUST) in Saudi Arabia.

The process of crystallization normally occurs in the blink of an eye, and the researchers needed to understand it at the nanoscale. To do this they had to create a way to record and visualize molecules as they formed crystals in slow motion.

To do this they combined a tiny, bright X-ray beam produced by the Cornell High Energy Synchrotron Source, or CHESS, in Ithaca, N.Y., with high-speed X-ray cameras to shoot a movie showing how organic molecules form different types of ordered structures or crystals.

This produced an ideal lattice – quick-evaporation of the solution coupled with the thinness of the liquid were part of the trick, as well as some surprises. The researchers showed that once the liquid film becomes thin enough, also known as the confinement regime, the type of crystal can be selected with unprecedented control.

In a more far-reaching sense, the experiments reveal new ways to study and control crystallization, both of which will benefit other fields, such as pharmaceutical manufacturing, where the potency of pills can depend on precisely controlling the crystal structure of active ingredients.

The research may help create strained organic semiconductors for use in electronic devices. It could also yield benefits beyond electronics and in other fields that require precise control over crystal polymorphism. Many drugs, for instance, are made from small molecules that must crystallize in just the right way to have the proper effect.