From the branching pattern of leaf veins to the variety of interconnected pathways that spread the coronavirus, nature thrives on networks — grids that link the different components of complex systems. Networks underlie such real-life problems as determining the most efficient route for a trucking company to deliver life-saving drugs and calculating the smallest number of mutations required to transform one string of DNA into another.
Instead of relying on software to tackle these computationally intensive puzzles, researchers at the National Institute of Standards and Technology (NIST) took an unconventional approach. They created a design for an electronic hardware system that directly replicates the architecture of many types of networks.
The researchers demonstrated that their proposed hardware system, using a computational technique known as race logic, can solve a variety of complex puzzles both rapidly and with a minimum expenditure of energy. Race logic requires less power and solves network problems more rapidly than competing general- purposed computers.
The scientists, who include Advait Madhavan of NIST and the University of Maryland in College Park and Matthew Daniels and Mark Stiles of NIST, describe their work in Volume 17, Issue 3, May 2021 of the ACM Journal on Emerging Technologies in Computing Systems.
A key feature of race logic is that it encodes information differently from a standard computer. Digital information is typically encoded and processed using values of computer bits — a “1” if a logic statement is true and a “0” if it’s false. When a bit flips its value, say from 0 to 1, it means that a particular logic operation has been performed in order to solve a mathematical problem.
In contrast, race logic encodes and processes information by representing it as time signals — the time at which a particular group of computer bits transitions, or fl ..
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