LAGraph

This is a library plus a test harness for collecting algorithms that use the GraphBLAS. For test coverage reports, see https://graphblas.org/LAGraph/ . Documentation: https://lagraph.readthedocs.org

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What it is

This is a library plus a test harness for collecting algorithms that use the GraphBLAS. For test coverage reports, see https://graphblas.org/LAGraph/ . Documentation: https://lagraph.readthedocs.org

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HN mentions by year4 dated mentions

Observed mentions: 2019-04-09 12:40:21 UTC to 2024-03-04 22:50:45 UTC.

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Comments
2019	2019-01-01 00:00:00 UTC	2020-01-01 00:00:00 UTC	1	1
2020	2020-01-01 00:00:00 UTC	2021-01-01 00:00:00 UTC	1	1
2021	2021-01-01 00:00:00 UTC	2022-01-01 00:00:00 UTC	0	0
2022	2022-01-01 00:00:00 UTC	2023-01-01 00:00:00 UTC	0	0
2023	2023-01-01 00:00:00 UTC	2024-01-01 00:00:00 UTC	0	0
2024	2024-01-01 00:00:00 UTC	2025-01-01 00:00:00 UTC	2	2

What Hacker News says

4 sources

michelpp·Mar 4, 2024

> you probably want more specialised tools like BLAS/LAPACK The GraphBLAS and LAGraph are sparse matrix optimized libraries for this exact purpose: https://github.com/DrTimothyAldenDavis/GraphBLAS https://github.com/GraphBLAS/LAGraph/

In The hunt for the missing data type

michelpp·Mar 4, 2024

A similar and more recent example of graph decomposition is the fast graphlet transform: https://github.com/fcdimitr/fglt This algorithm has a nice Algebraic formulation recently implemented with the GraphBLAS in LAGraph: https://github.com/GraphBLAS/LAGraph/blob/stable/experimenta...

In A windowed graph Fourier transform (2012)

DocSparse·May 23, 2020

Give us time; we're still in the beginning stages of writing algorithms that use it. If you dig through LAGraph, you'll find lots of messy prototypes, as we experiment on various methods. Those are drafts, not polished results. Our most recent methods are polished, extremely simple, yet very fast: https://github.com/GraphBLAS/LAGraph/blob/master/Source/Algo... https://github.com/GraphBLAS/LAGraph/blob/master/Source/Algo... https://github.com/GraphBLAS/LAGraph/blob/master/Source/Algo... (that one has 6 algorithms inside) https://github.com/GraphBLAS/LAGraph/blob/master/Source/Algo... We're working on the GPU version, and all the built-in semirings very work nicely on the GPU. For user-defined semirings, we will need the user operators defined as strings containing C code. Then they can all be done on the GPU too.

In GraphBLAS – Graph algorithms in the language of linear algebra

DocSparse·Apr 9, 2019

GraphBLAS uses sparse matrices internally, and the API assumes a sparse format. The data structure is opaque, however, so if I want, I could use dense matrices if it's faster (and there are times when that's faster; see for example the vector v in the push/pull BFS in LAGraph, at https://github.com/GraphBLAS/LAGraph/blob/master/Source/Algo... ). However, I don't switch to dense matrices automatically yet. SuiteSparse:GraphBLAS does have a fast incremental update mechanism, but it's not (yet) as flexible as other approaches. But the beauty of GraphBLAS is that the data structure is entirely opaque to the user, so if a library implementor such as myself wants to plunk in an entire new one, then the user code that relies on GraphBLAS doesn't change. It would be possible, even, to use lua-graph internally (or anything else, license permit

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ting), and then to select the fastest format for the problem at hand. Or, lua-graph (or any graph library) could be augmented to support a GraphBLAS API to its functionality. Currently, SuiteSparse:GraphBLAS has four matrix formats: CSR, CSC, hypersparse CSR, and hypersparse CSC. The CSR and CSC formats take O(|V|+|E|) space, and the hypersparse formats take O(|E|) space. Hypersparse matrices arise in some problems, and subgraphs are often hypersparse. In the future, I would like to add a CSB format as well. I select between standard and hypersparse formats automatically. The default is CSR and I don't pick CSC automatically. In some cases, it would make sense to hold the matrix in both CSR and CSC formats, simultaneously, thus allowing fast access to both the in- and out-adjacency lists at the same time (at the cost of double the memory). I don't do that yet, however.

In What is GraphBLAS?