P33: Massively Parallel Evolutionary Computation for
Empowering Electoral Reform: Quantifying Gerrymandering
via Multi-objective Optimization and Statistical Analysis
SessionPoster Reception
Authors
Event Type
ACM Student Research Competition
Poster
Reception
TimeTuesday, November 14th5:15pm -
7pm
LocationFour Seasons Ballroom
DescriptionImportant insights into redistricting can be gained by
formulating and analyzing the problem within a
large-scale optimization framework. Redistricting is an
application of the set-partitioning problem that is
NP-hard. We design a hybrid metaheuristic as the base
search algorithm. With our grant on the Blue Waters
supercomputer, we extend our algorithm to the
high-performance-computing realm by using MPI to
implement an asynchronous processor communication
framework. We experimentally demonstrate the
effectiveness of our algorithm to utilize multiple
processors and to scale to 131,072 processors. The
massive computing power allows us to extract new
substantive insights that closely mesh with the
framework that the Supreme Court has elucidated for
electoral reform.
