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Abstract:
We consider the problem of preprocessing an $n$-vertex digraph with
real edge weights so that subsequent queries for the shortest path or distance
between any two vertices can be efficiently answered.
We give parallel algorithms for the EREW PRAM model of computation
that depend on the {\em treewidth} of
the input graph. When the treewidth is a constant, our algorithms
can answer distance queries in $O(\alpha(n))$ time using a single
processor, after a preprocessing of $O(\log^2n)$ time and $O(n)$ work,
where $\alpha(n)$ is the inverse of Ackermann's function.
The class of constant treewidth graphs
contains outerplanar graphs and series-parallel graphs, among
others. To the best of our knowledge, these
are the first parallel algorithms which achieve these bounds
for any class of graphs except trees.
We also give a dynamic algorithm which, after a change in
an edge weight, updates our data structures in $O(\log n)$ time
using $O(n^\beta)$ work, for any constant $0 < \beta < 1$.
Moreover, we give an algorithm of independent interest:
computing a shortest path tree, or finding a negative cycle in
$O(\log^2 n)$ time using $O(n)$ work.
