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Can a Supercomputing Algorithm Kill Gerrymandering?


A map of Wisconsin's Congressional districts.

Researchers at the University of Illinois at Urbana-Champaign have developed a supercomputing algorithm that can determine whether state legislative districts have been drawn fairly.

Credit: top500.org

Researchers at the University of Illinois at Urbana-Champaign have developed a supercomputing algorithm that can determine whether state legislative districts have been unfairly drawn, with the potential of reshaping U.S. electoral politics.

The application, when run on the university's Blue Waters supercomputer, can produce 1 billion possible maps using only the criteria required by state law and traditional districting principals. The maps are inherently nonpartisan because no political demographics are used to create them.

Algorithm co-developer Wendy Tam Cho says the vast volume of produced maps would provide the court with a statistically relevant dataset from which to infer partisan intent. "If a billion different maps are very different from the map the court is evaluating, then the Supreme Court has some evidence that partisanship was part of the motivation behind the alleged partisan gerrymandering," Cho notes.

The algorithm could end up effectively outlawing gerrymandering across the U.S.

From TOP500.org
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Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA


 

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