Researchers Create Brain-Inspired Computing Architecture

Summary: Researchers have discovered a new molecule that could increase the ultra-fast decision-making capabilities of computers. The simple molecule provides a new electronic circuit element in which complex logic is encoded in nanoscale material properties.

Source: University of Limerick

An international team of scientists including researchers at University of Limerick in Ireland has discovered a new molecule that could further increase ultra-fast decision making in computers.

The energy-saving discovery, creating a new type of computing architecture, could have major implications in areas spanning from financial decision-making to bioinformatics.

The team at UL’s Bernal Institute discovered that a simple molecule made from just 77 atoms provides a new fundamental electronic circuit element in which complex logic is encoded in nanoscale material properties.

The new type of brain-inspired computing architecture was created by optimizing the electrical properties of soft crystals grown from the molecules.

The finding has just been reported in Nature.

Damien Thompson, Professor in Physics at UL who leads a research team in predictive materials design at the Bernal Institute, made the discovery using state-of-the-art computer simulations performed on the Irish Centre for High-End Computing supercomputer.

He showed that the molecule uses natural asymmetry in its metal-organic bonds to cleanly switch between different states, which allows it to perform ultra-fast decision-making.

“In the new device, everything is done in one place, so there is no need to keep reading or moving information around,” explained the Science Foundation Ireland-supported scientist.

“This removes the ‘von Neumann bottleneck’, a problem that has plagued computing from the very beginning and still hampers technology development. The new molecular circuitry means the computer-processing unit no longer has to fetch data for every operation it performs, and this saves enormously on time and energy costs.

“We are excited about the possibilities because the devices show all the hallmarks of brain computing. First, a huge number of tiny, identical molecular processors are networked together and work in parallel. More importantly, they show both redundancy and reconfigurability, which means the device can solve problems even if the individual components do not all work perfectly all the time or in the exact same way every time.

This is a drawing of a brain on a computer screen
The new type of brain-inspired computing architecture was created by optimising the electrical properties of soft crystals grown from the molecules. Image is in the public domain

“The new circuit elements could provide computers that are smaller, faster, and more energy-efficient, exactly what is needed for edge computing, internet of things and artificial intelligence applications,” Professor Thompson added.

The metal-organic molecules were synthesised by collaborators at the Indian Association for the Cultivation of Science (IACS) in Kolkata, made into films at National University of Singapore, and tested as circuit elements in Singapore, at Hewlett Packard’s AI Research Lab in Colorado, and at Texas A&M University.

Professor Luuk van der Wielen, Director of Bernal Institute and Bernal Professor of Biosystems Engineering and Design, expressed his delight at the major breakthrough involving the UL scientists.

“This high-impact research reinforces the ambition of the Bernal Institute at UL to impact the world on the basis of top science in an increasingly international context. This is a continuation of Bernal scientists’ world-leading contribution to the field of predictive materials modeling,” he explained.

Professor Seán Arkins, Dean of Science and Engineering at UL, said: “The researchers in UL’s Department of Physics continue to pioneer the exploitation of organic materials for electrical applications, and this work places them at the forefront of molecular nanotechnology.”

About this neurotech research news

Author: Alan Owens
Source: University of Limerick
Contact: Alan Owens – University of Limerick
Image: The image is in the public domain

Original Research: Closed access.
Decision trees within a molecular memristor” by Sreetosh Goswami, Rajib Pramanick, Abhijeet Patra, Santi Prasad Rath, Martin Foltin, A. Ariando, Damien Thompson, T. Venkatesan, Sreebrata Goswami & R. Stanley Williams. Nature


Decision trees within a molecular memristor

Profuse dendritic-synaptic interconnections among neurons in the neocortex embed intricate logic structures enabling sophisticated decision-making that vastly outperforms any artificial electronic analogues.

The physical complexity is far beyond existing circuit fabrication technologies: moreover, the network in a brain is dynamically reconfigurable, which provides flexibility and adaptability to changing environments.

In contrast, state-of-the-art semiconductor logic circuits are based on threshold switches that are hard-wired to perform predefined logic functions. To advance the performance of logic circuits, we are re-imagining fundamental electronic circuit elements by expressing complex logic in nanometre-scale material properties.

Here we use voltage-driven conditional logic interconnectivity among five distinct molecular redox states of a metal–organic complex to embed a ‘thicket’ of decision trees (composed of multiple if-then-else conditional statements) having 71 nodes within a single memristor.

The resultant current–voltage characteristic of this molecular memristor (a ‘memory resistor’, a globally passive resistive-switch circuit element that axiomatically complements the set of capacitor, inductor and resistor) exhibits eight recurrent and history-dependent non-volatile switching transitions between two conductance levels in a single sweep cycle. The identity of each molecular redox state was determined with in situ Raman spectroscopy and confirmed by quantum chemical calculations, revealing the electron transport mechanism.

Using simple circuits of only these elements, we experimentally demonstrate dynamically reconfigurable, commutative and non-commutative stateful logic in multivariable decision trees that execute in a single time step and can, for example, be applied as local intelligence in edge computing.

Join our Newsletter
I agree to have my personal information transferred to AWeber for Neuroscience Newsletter ( more information )
Sign up to receive our recent neuroscience headlines and summaries sent to your email once a day, totally free.
We hate spam and only use your email to contact you about newsletters. You can cancel your subscription any time.