Graphulo Implementation of Server-Side Sparse Matrix Multiply in the Accumulo Database

July 04, 2015 ยท Declared Dead ยท ๐Ÿ› IEEE Conference on High Performance Extreme Computing

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Authors Dylan Hutchison, Jeremy Kepner, Vijay Gadepally, Adam Fuchs arXiv ID 1507.01066 Category cs.DB: Databases Cross-listed cs.DC, cs.MS Citations 39 Venue IEEE Conference on High Performance Extreme Computing Last Checked 2 months ago
Abstract
The Apache Accumulo database excels at distributed storage and indexing and is ideally suited for storing graph data. Many big data analytics compute on graph data and persist their results back to the database. These graph calculations are often best performed inside the database server. The GraphBLAS standard provides a compact and efficient basis for a wide range of graph applications through a small number of sparse matrix operations. In this article, we implement GraphBLAS sparse matrix multiplication server-side by leveraging Accumulo's native, high-performance iterators. We compare the mathematics and performance of inner and outer product implementations, and show how an outer product implementation achieves optimal performance near Accumulo's peak write rate. We offer our work as a core component to the Graphulo library that will deliver matrix math primitives for graph analytics within Accumulo.
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