Benchmarking Platforms for Large-Scale Graph Processing and RDF Data Management: The LDBC Approach

Tutorial at ICPE

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Speakers: Alexandru Iosup, Ana Lucia Varbanescu, Mihai Capota, Tim Hegeman Graphs model social networks, human knowledge, and other vital information for business, governance, and academic practice. Although both industry and academia are developing and tuning many graph-processing algorithms and platforms, the performance of graph-processing platforms has never been explored or compared in-depth. Moreover, graph processing exposes new bottlenecks in traditional HPC systems (see differences in Top500 and Graph500 rankings). Complementing Graph500, the Linked Data Benchmark Council (LDBC) consortium, which involves over 25 academic and industry partners, focuses on the development of benchmarks that will spur research and industry progress in large-scale graph and RDF data management. This tutorial introduces the SC audience to the latest LDBC benchmarks. Attendees will learn about and experiment with methods and tools for performance evaluation and optimization for graph processing platforms, and become able to explain the performance dependency Platform-Algorithm-Dataset. The attendees will understand in-depth three workloads, interactive social networking, semi-online business intelligence based on analytical queries, and batch full-graph analytics. The tutorial presents real-world experiences with commonly used systems, from graph databases such as Virtuoso and Neo4j, to parallel GPU-based systems such as Totem and Medusa, to distributed graph-processing platforms such as Giraph and GraphX. The tutorial also includes significant hands-on and Q&A components. URL: