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.

中文翻译：

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LAGraph：线性代数，网络分析库和图算法的研究

图算法可以用线性代数表示。GraphBLAS是针对此类算法的，针对算法开发人员的低级构建块库。LAGraph建立在GraphBLAS的基础上，以网络分析中常见的高级算法为图形算法的用户定位。在本文中，我们描述了LAGraph库的第一个版本，库背后的设计决策以及使用GAP基准套件的性能。但是，LAGraph不仅仅是一个库。这也是一个记录和分析GraphBLAS支持的所有算法的项目。为此，我们开发了一种简洁直观的表示法来描述这些算法。在本文中，我们通过GAP基准测试套件中的示例展示了这种表示法。