HPGDMP'16: First International Workshop on High Performance Graph Data Management and Processing
Organizers
Event Type
Workshop
Algorithms
SIGHPC Workshop
TimeSunday, November 13th9am - 12:30pm
Location251-C
DescriptionApplications that need to manage and process large scale graph data have become prominent in recent times. Social network analysis, semantic web, bioinformatics, and cheminformatics are some examples of application domains that deal with large graphs containing billions of vertices and edges. Graph processing has attracted significant attention from the high performance computing community due to the complexities involved with the processing and storage of large graphs. Data management systems such as in-memory, distributed graph databases have been introduced for storing and managing large graphs. Graph processing frameworks and libraries have been developed to simplify high performance large scale graph processing. Furthermore, large scale distributed-memory compute clusters, single shared-memory high performance computers, and heterogeneous hardware containing GPUs and FPGAs have been used for carrying out large scale graph data processing tasks. These efforts have been bolstered by graph related benchmarking initiatives such as the Graph 500 and Green Graph 500 benchmarks. Despite these significant research efforts, there still exist significant issues and technical gaps which need to be solved in the area of high performance graph data management and processing. The High Performance Graph Data Management and Processing 2016 (HPGDMP16) workshop aims to provide a unified platform for discussing the latest state-of-the-art efforts conducted to address research issues related to high performance large graph management and processing.
This workshop will produce a refereed proceedings that will be available through the ACM Digital Library and IEEE Xplore (free of charge during and immediately after SC, and free after that to SIGHPC members).
This workshop will produce a refereed proceedings that will be available through the ACM Digital Library and IEEE Xplore (free of charge during and immediately after SC, and free after that to SIGHPC members).
Links
Proceedings
