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.

翻译：图表算法可以以线性代数表示。 GraphBLAS是这类算法针对算法开发者的低层构件库。 LAGraph在GreabBLAS的顶部,以图式算法的用户为对象,而图式算法在网络分析中是常见的高级算法。在本文中,我们描述了LAGraph图书馆的第一版,图书馆背后的设计决定,以及使用GAP基准套件的性能。LAGraph远远不止是一个图书馆。它也是一个记录和分析GrapBLAS所促成的全方位算法的项目。为此,我们为描述这些算法制定了一个缩略图和直观的符号。在本文中,我们用GAP基准套件中的例子来说明这一点。