ORNL Researchers Survey Edge Computing Landscape – HPCwire

Feb. 21, 2020 — Oak Ridge National Laboratory (ORNL) researchers Ali Passian and Neena Imam surveyed the edge computing landscape and novel nanoscale technologies to better understand how to simultaneously advance both edge computing and nanoscience to benefit scientific progress. Their work was published in the journal Sensors.

Edge computing is both dependent on and greatly influencing a host of promising technologies including (clockwise from top left): quantum computing; high-performance computing; neuromorphic computing; and carbon nanotubes. Image courtesy of ORNL.

According to researchers, the answer lies in the development of next-generation materials at the nanoscale and beyond.

Researchers are manipulating materials at increasingly smaller scales to create unique behaviors, both quantum and classical, that could lead to interconnects, processors, and transistors that are exponentially more potent than those available today.

“All of the hype around edge computing presents an excellent opportunity for nanosystem R&D, which is necessary for a full, secure network of countless edge devices,” said Passian, a research scientist in ORNL’s Quantum Information Science group. “For edge computing to succeed, next-generation nanosystems will have to first be developed.”

The pursuit of low-power sensors, signal generating devices and arrays, energy-efficient and secure computing, storage, and fast communication processes could lead to technological progress. However, the explosion of sensors across society has presented edge computing with bandwidth, latency, and storage issues.

One solution to these challenges lies in the burgeoning field of artificial intelligence (AI). By incorporating a high-performance processor with built-in AI, edge computing can perform local decision-making and send only relevant data to the cloud, thus increasing the performance of various networks. AI in the cloud has the potential to also control the functions of edge devices.

High-performance computing will be instrumental in guiding the development of edge computing. For instance, the modeling and simulation of edge devices will be critical.

Energy-efficient microprocessors are critical to the evolution of HPC, as well as for future edge devices. And just as supercomputers are expected to be fast, secure, and use as little power as possible, edge computing devices are expected to do the same.

Both require significant advances in nanotechnology to realize their potential. “Edge computing and nanosystems may become one entity, where device and function come to interact dynamically,” Passian said.

Quantum effects also show promise in the fields of networking and sensing. For instance, Passian and Imam said quantum effects were demonstrated to carry information up to approximately 1,400 kilometers in free-space channels, a phenomenon that could greatly benefit edge computing and sensing.

Perhaps most importantly, edge devices must be secure, and one of quantum communication’s greatest strengths is its ability to securely and rapidly transmit information across great distances. However, new materials are needed to design the necessary processors, circuits, and transistors to apply quantum technologies to the edge’s challenges.  Due to their nanometer-size, carbon nanotubes (CNTs) are currently the most promising alternative to transistors, and CNT-based field-effect transistors are leading to faster, more efficient processors and sensors.

There’s also a massive research effort around photonic systems. It is now possible to integrate photonic components on a single chip, and photonic technology can be married with other systems to create innovative computing and networking platforms.

Plasmonic and optical interconnects show the potential for making these systems more efficient. For instance, “an information-carrying photon may be converted into an information-carrying plasmon that can propagate through a quantum plasmonic circuit in an optical computer or processor,” the authors write. However, the challenge of confining and controlling photons, which is necessary for the shrinking and integration of potential devices, still remains.

Finally, neuromorphic computing is also emerging as a potential edge platform.

In the end, the authors conclude that quantum and topological materials offer exciting and promising areas for the evolution of both nanotechnology and edge computing. But whatever the outcome, there is little doubt that edge computing will have a significant impact on numerous scientific fields as it matures.

This work was supported by the United States Department of Defense.

For more information on the project and read the full article, visit: https://www.ornl.gov/news/ornl-researchers-identify-most-promising-tech-advancing-edge-computing

About Oak Ridge National Laboratory 

UT-Battelle manages ORNL for DOE’s Office of Science. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Source: Oak Ridge National Laboratory 

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