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Parallel Algorithms for Graph Optimization using Tree Decompositions

Conference ·
OSTI ID:1089227
Although many NP-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of required dynamic programming tables and excessive running times of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree-decomposition based approach to solve maximum weighted independent set. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.
Research Organization:
Oak Ridge National Laboratory (ORNL); Center for Computational Sciences
Sponsoring Organization:
SC USDOE - Office of Science (SC)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1089227
Country of Publication:
United States
Language:
English

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