Graphs are a ubiquitous and versatile data structure, which allow representation of problems and systems across a vast array of domains, from infrastructure networks and molecules to language and social interactions. SuiteSparseGraphBLAS.jl casts graph computations as generalized linear algebra on sparse matrices. Support for ChainRules AD frameworks, and the wider ecosystem is a core feature of v1.0, releasing around JuliaCon.
This talk will give an overview of progress on a JSOC 2021 project. Most work will be complete by this point, and the talk will give a brief overview of GraphBLAS, an example algorithm using GraphBLAS in Julia, and a graph neural network layer written using the project.
One of the goals of the project is interoperability with the Julia ecosystem, integrating with interfaces from SparseArrays, LightGraphs, and GeometricFlux. These integrations will be highlighted as well.