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## Re: [igraph] Computing SCC on large graph

 From: Santiago Videla Subject: Re: [igraph] Computing SCC on large graph Date: Mon, 11 May 2015 16:15:36 -0300

Hi,

FYI, I came back to this using both igraph for R and graph-tool [1], over the same graph and they took ~2s to compute SCC. So, I guess something is not working as expected in the python interface :) Please, let me know if I can help somehow to debug this.

Regards,

On Tue, Apr 28, 2015 at 3:15 PM, Santiago Videla wrote:
Hi,

Thanks for the reply. Just to let you know, it ended a few hours after I sent my email, so I guess it was just hard to compute :)

Regards,

On Mon, Apr 27, 2015 at 9:31 PM, Gábor Csárdi wrote:
Hi, SCC is linear, so it should not take too long. I would try a smaller graph first, then a bit bigger one, etc. to see how it scales.

But it is suspicious that something went wrong.

G.

On Mon, Apr 27, 2015 at 4:12 PM, Santiago Videla wrote:
Hi all,

I recently started to use igraph (from python) and after playing a bit with it I loaded a directed graph with ~1.5 millions nodes and ~100 millions edges. I know there are cycles and I'd like to identify them all (I believe that most of them are of the form A <-> B). I'm trying to compute the SCC of the graph. I guess there are plenty of things that in practice could have an impact on how the algorithm performs. But, does anyone have experience computing SCC on a graph of similar scale? How long (aprox) could it take? I ask because it has been running for 75 hours by now, and the memory seems quite stable around 3.5GB (Intel Core i5 2.67GHz - 16GB RAM).

Do you think this is normal/expected? Should I just keep waiting?

Regards,

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Santiago Videla