Graphulo Implementation of Server-Side Sparse Matrix Multiply in the Accumulo Database
July 04, 2015 ยท Declared Dead ยท ๐ IEEE Conference on High Performance Extreme Computing
"No code URL or promise found in abstract"
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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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