In order to calculate the number of shortest paths in each Neo4j database configuration a high performance computing cluster was used. The native Neo4j or NetworkX methods of calculating the number of shortest paths was found to either take too long or eventually fail due to RAM limitations. To address this each Neo4j database configuration was converted into a NetworkX DiGraph object and stored in gpickle format. All of the graphs were then loaded onto NCATS' HPC cluster to be processed by a Python script which would split the processing across all of the available cores.