Comments (11)
If you give me some sample dataset I can try to perform runtime analysis and try to improve running time by parallelized or not.
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There is potential for speedup by multithreading parts of GFAffix, especially if the bottle neck is the graph traversal. I'd be interested in knowing which step in the algorithm affects the running time on these deep graphs. The graph traversal can be parallelized, but it's not embarrassingly parallelizable, as the graph editing (which is intertwined in the graph traversal) can only be done safely in a single thread.
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@ekg do you have such a "deep graph" handy?
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Or just smaller but similar graph.
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Do these deep graphs have a particular high node degree, or is the number of nodes exceptionally high?
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GFAffix should scale linearly with path depth, overall this shouldn't dominate the runtime. But node degree is certainly a bottle neck.
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@ekg Could you give me advise how to build a similar graph, type of data, pipeline, tools, etc…
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@natir sorry to take a while here. I may need to share this somehow, but the graph is rather large and will take 4 days to build if you do so from scratch. I'll see if I can get a simpler test case together.
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@ekg Just so you know that your issue is not forgotten: I have a solution for parallelizing GFAffix and will work on this sometime soonish.
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Related Issues (13)
- GFAffix breaks path HOT 1
- Gfaffix removes one edge needed by paths, leaving graph invalid HOT 5
- gfaffix invalidates graph by removing self-looping edge HOT 5
- update Bioconda recipe HOT 2
- memory allocation error in 0.1.5b HOT 6
- --dont_collapse regex behaves weirdly HOT 3
- --dont_collapse braids a deep nested snarl HOT 3
- gfaffix crashes with "length of walk X does not sum up to that of its replacing node of Y HOT 1
- Reference path de-collapse sometimes results in nodes+edges not covered by any path.
- GFAffix strips header information HOT 1
- --dont_collapse doesn't work on W-lines?
- how to cite? HOT 4
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