  Contraction Hierarchies is a successful speedup-technique to Dijkstra's
seminal shortest path algorithm that has a convenient trade-off between
preprocessing and query times. We investigate a shared-memory parallel
implementation that uses $O(n+m)$ space for storing the graph and O(1) space
for each core during preprocessing. The presented data structures and
algorithms consequently exploits cache locality and thus exhibit competitive
preprocessing times. The presented implementation is especially suitable for
preprocessing graphs of planet-wide scale in practice. Also, our experiments
show that optimal data structures in the PRAM model can be beaten in practice
by exploiting memory cache hierarchies.
