News related to the GraphBLAS API and its community. GraphBLAS implementations, graph algorithms in linear algebra and graph processing on specialized hardware.
Joined July 2020
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GraphBLAS retweeted
And finally, here's John Gilbert's talk on graphs and sparse matrices @JuliaConOrg '23, on @GraphBLAS and many other things: youtu.be/X2JEWdCFf70?si=1mPI…
GraphBLAS retweeted
More work for @GraphBLAS !
@chrispatton, the Head of Product at @VirtuousAI, reveals how his company plans to use FalkorDB as a key element of its solution. VirtuousAI is an ethical AI platform that provides “whitebox” ML models.
falkordb.com/use-cases/virtu…
GraphBLAS retweeted
I learned so much from @eriknwelch's keynote at @pyconhk: How to accelerate NetworkX with GraphBLAS and cuGraph.
Amazing work @eriknwelch @nvidia @RAPIDSai @networkx_team 🙌🙌🙌
GraphBLAS retweeted
Here's a link to my JuliaCon 2023 keynote talk on @GraphBLAS and its impact on @JuliaLanguage,
@MATLAB, permion.ai (and thus
@LeidosInc), @falkordb (formerly RedisGraph) and more.
youtube.com/live/vG6ZLhe9Hns…
(reposted with link fixed)
GraphBLAS retweeted
We extended the deadline for the IPDPS 2023 Workshop on Graphs, Architectures, Programming, and Learning (GrAPL 2023) #hpc #graphs #GNN #algorithms #programming #MachineLearning
@GraphBLAS
Please submit your work by February 1st, 2023
GraphBLAS retweeted
Speeding up graph algorithms in python by up to 21,000x. 🔥
via a NetworkX+@anacondoninc+@GraphBLAS collaboration: NetworkX (@networkx_team) performance boost using the python interface to SuiteSparse:@GraphBLAS. @pydata talk by @eriknwelch & Jim Kitchen youtu.be/pd-Sbm8lHTc
The GraphBLAS BOF at @Supercomputing starts in 3 minutes in Room C146.
hpc.pnl.gov/BOF/
GraphBLAS retweeted
I'm at @Supercomputing 2022 in Dallas and would be happy to chat about @LDBCouncil benchmarks and @GraphBLAS applications. Send me a DM if you're interested. – at Dallas, TX
GraphBLAS retweeted
I'll be at the Graph Toolkit and @GraphBLAS BoF: sc22.supercomputing.org/pres…
GraphBLAS uses sparse linear algebra over semirings to create graph algorithms, and appears in @Redis, Anaconda, @MATLAB, and other places. Should be fun!
GraphBLAS retweeted
@GraphBLAS SIAM News article: graph algorithms via linear algebra over semirings, using sparse matrices. Already a part of @MATLAB, @Redis, @Anaconda conda-forge, Graphstax.com (AI on graphs), @JuliaLanguage, ... sinews.siam.org/Details-Page…
GraphBLAS retweeted
I have 2 PhDs who will finish this year: @aznaveh1 working on parallel sparse LU & @Jin_hao_Chen working on exact update/downdate of sparse LU and Cholesky. Both have worked with @GraphBLAS too. Great work! Both looking for positions (academic & non-academic) DM for details
GraphBLAS retweeted
@GraphBLAS speeds up sparse matrices in Julia by up to 1000x (for C[I,J]=A). C=A*B, C=A+B, C=A' etc are 2x to 30x faster (10x typical). @JuliaLanguage now has a full-featured interface to GraphBLAS, incl. semirings, masks, etc, for graph algo (@MATLAB uses GrB but only for C=A*B)
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GraphBLAS retweeted
New post: SuiteSparseGraphBLAS.jl: An Introduction - juliabloggers.com/suitespars… #julialang
GraphBLAS retweeted
Submit your work to the IPDPS 2022 Workshop on Graphs, Architectures, Programming, and Learning (GrAPL 2022) #hpc #graphs #GNN #algorithms #programming #MachineLearning
Deadline: Feb 14th 2022 -- hpc.pnl.gov/grapl/
The deadline of the GrAPL 2022 workshop has been extended to Feb 14: hpc.pnl.gov/grapl/cfp.html
SuiteSparse:GraphBLAS v6.1.4 is out with improved documentation and compile-time flags for cpu_features. It's the first version thoroughly tested on Apple Silicon (thanks to @szarnyasg).
github.com/DrTimothyAldenDav…
GraphBLAS retweeted
This paper presents a benchmark for the incremental evaluation of graph queries on the LDBC social network data sets. It includes tools from multiple domains (relational and graph DBMSs, model transformation tools, differential dataflow, GraphBLAS).
Our SoSyM paper based on the TTC 2018 live case on incremental graph queries is out! - dx.doi.org/10.1007/s10270-02…
GraphBLAS retweeted
In this paper, researchers presented 4 new algorithms for performing parallel masked SpGEMM which, in most cases scenarios, significantly outperform the state of the art for Masked SpGEMM implementations on a large number of real-world benchmarks. #HPC
arxiv.org/pdf/2111.09947.pdf
