LAGraph: Linear Algebra, Network Analysis Libraries, and the Study of Graph Algorithms

TL;DR

LAGraph is a high-level library built on GraphBLAS that simplifies network analysis by providing common graph algorithms, and it also serves as a platform for documenting and analyzing graph algorithms expressed in linear algebra.

Contribution

This paper introduces the first release of LAGraph, a library that offers high-level graph algorithms and a notation for describing algorithms enabled by GraphBLAS.

Findings

LAGraph demonstrates competitive performance on the GAP benchmark suite.

The library provides a user-friendly interface for network analysis tasks.

A new notation effectively describes a broad range of graph algorithms.

Abstract

Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level building blocks for such algorithms that targets algorithm developers. LAGraph builds on top of the GraphBLAS to target users of graph algorithms with high-level algorithms common in network analysis. In this paper, we describe the first release of the LAGraph library, the design decisions behind the library, and performance using the GAP benchmark suite. LAGraph, however, is much more than a library. It is also a project to document and analyze the full range of algorithms enabled by the GraphBLAS. To that end, we have developed a compact and intuitive notation for describing these algorithms. In this paper, we present that notation with examples from the GAP benchmark suite.