I'm not understanding the docs on parallelization. I'd like to parallelize
a betweenness centrality calculation:
for s in nodes
state = dijkstra_shortest_paths(g, s; allpaths=true)
if endpoints
_accumulate_endpoints!(betweenness, state, g, s)
else
_accumulate_basic!(betweenness, state, g, s)
end
end
nodes is a vector of ints over which the calculation should be run (by
default, this is every vertex in the graph). Because both state() and
_accumulate_* are independent calculations, it seems to me that I could
take advantage of multiple cores / processors to speed things up. However,
I don't know where to start. Any advice would be greatly appreciated.
State has arrays of ints called "dists" and "parents" - each run through
this loop alters these arrays, but there's no dependence between loop
iterations.
