I am trying to obtain the correlation histogram for a graph of mine following the example given in the manual. I run: g = gt.load_graph('graph.gt') gt.remove_parallel_edges(g) h=gt.corr_hist(g,'out','out') My graph is relatively large at 12,238,931 vertices and 24,884,365 edges. My problem is that as soon as I start the code it runs on 20 processes and happily chomps through 252 GB of RAM before starting to spill over into the swap making my machine incredibly slow. I presume the RAM usage is linked to the parallel processing so presumably could be tackled if I ran it using fewer processes. Is there any way of reducing the RAM usage? Or would I need to implement the routine manually to achieve this? Best wishes, Philipp -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/... Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.