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Thursday, May 30 • 9:45am - 10:30am
Discerning Industry Requirements for Graph Analytics

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Earlier this year, Gartner® lists graph processing among the top 10 data and analytics technology trends for 2019: “The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.” Almost ten years ago, Intel launched an academic research program to study parallel algorithms for non-numeric computation. This research gave rise to GraphBLAS, a graph analytics specification based on sparse linear algebra. This approach leverages decades of existing R&D on high-performance, parallel sparse linear algebra. In addition to GraphBLAS, Intel is evaluating several other approaches to graph analytics, including parallel frameworks and domain-specific languages.

The landscape of graph analysis is diverse and highly-fragmented. What are the critical graph algorithms? What graph sizes are typical for a given application? Are streaming, dynamic graphs required, or is static analysis enough? When is the graph topology sufficient, and when must vertex and edge attributes be considered? This talk covers Intel’s internal evaluation and benchmarking of various graph solutions in order to answer these questions. Our recent work on truly large graphs (i.e., roughly one trillion edges) will also be presented.

avatar for Henry A. Gabb

Henry A. Gabb

Senior Principal Engineer, Intel
Henry A. Gabb is a Senior Principal Engineer in Intel’s Compute Performance and Developer Products group. Much of his career has been spent promoting the value of parallel computing. He was the program manager for the Universal Parallel Computing Research Centers, a joint Intel/Microsoft... Read More →

Thursday May 30, 2019 9:45am - 10:30am CDT
(C) A2564 - A2566 Normandale Partnership Center, 9700 France Ave So, Bloomington, MN 55431