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Feature Article

Feature Article

Non-Silicon, Non-von-Neumann Computing – Part II

Access the overview by Sankar Basu, Randal Bryant, Giovanni de Micheli, Thomas Theis, and Lloyd Whitman in Proceedings of the IEEE, August 2020

The editors of the special issue are from the US National Science Foundation, Carnegie Mellon University, Swiss Federal Institute of Technology Lausanne (EPFL), and IBM.

This special issue is a continuation of new research articles on novel computer architectures and devices that was first introduced in a January 2019 special issue.

This is a very broad field, as reflected in the selection of articles included.

This includes articles on error correction in systems of unreliable devices, field programmable analog arrays, spintronic memories, spin-based stochastic logic, deep learning with photonic devices, and quantum computing in noisy systems.

While most of these systems are still in the research stage, and indeed, some may never prove to be practical, they illustrate some of the wide range of technologies that may be applied to non-silicon, non-von-Neumann processors in the next several decades.

Technology Spotlight

Technology Spotlight

Brain-Inspired Computing
Catherine Schuman, Oak Ridge National Laboratory

At the MIT Technology Review Symposium on Future Compute, held in Dec. 2019 in Cambridge, Massachusetts, Dr. Schuman provided an overview of Brain-Inspired Computing, also known as Neuromorphic Computing.

Biological brains consist of arrays of neurons connected by synapses, with massive parallelism and distributed logic and memory. Early inspiration by the structure of the brain gave rise to the now established field of artificial neural networks (ANNs), which are being widely applied to artificial intelligence and machine learning. Dr, Schuman contrasted these ANNs with networks that emulate brains somewhat more closely, by including spiking neurons that are extremely low in power. These newer systems may have application to AI in mobile edge systems, where power limitation is more critical. Similar systems may also be applied to simulation of biological brains.

Access the video of Dr. Schuman's talk at the MIT Future Compute website.

This Symposium also included many other talks covering the field of future computing, from AI to quantum computing. Access the agenda and the videos for most of these talks at the MIT Future Compute website.