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From: | Thomas F. Brantle |
Subject: | [igraph] Average Path Length / Diameter |
Date: | Mon, 11 Feb 2008 20:43:10 -0500 |
Gabor and Others: I know that those computations involving “shortest path”
analyses will be fairly “costly and time consuming” from a
computational point of view (i.e., m*n). Please let me give you a general
idea of my network data and other potential computer resource constraints. The primary network data that I want to analyze includes a few datasets
of approximately 2 – 3 million nodes and 10 – 30 million links,
each. For these shortest path (e.g., average shortest path length) computations
I assume that my network is “undirected” and I also expect the
largest or giant component to include 90-99% of the nodes. For these analyses I’m using an 8GB/2800MHz Linux (Ubuntu)
server. Given these computing constraints, I would greatly appreciate your
suggestions on a computing (and computational) strategy for my network dataset
analyses. I’ve estimated that the computation could take a month or more.
Given this issue, is there a convergence strategy, computational
sampling, numerical approximation or other alternative that may be
incorporated? I’ve searched the literature and haven’t seen this
issue directly addressed, unless I just missed it. If you have any ideas or a suggested computational strategy I’d
greatly appreciate it. Thanks, --Tom |
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