Novel High-Performance Hybrid System for Semantic Factoring of Graph Databases
Pacific Northwest National Laboratory (09/21/11) Kathryn Lang; Christine Novak
Researchers at the Pacific Northwest National Laboratory, Sandia National Laboratories, and Cray have developed an application that can analyze gigabyte-sized data sets. The application uses semantic factoring to organize data, revealing hidden connections and threads. The researchers used the application to analyze the massive datasets for the Billion Triple Challenge, an international competition aimed at demonstrating capability and innovation for dealing with very large semantic graph databases. The researchers utilized the Cray XMT architecture, which allowed all 624 gigabytes of input data to be held in RAM. The researchers are now developing a prototype that can be adapted to a variety of application domains and datasets, including working with the bio2rdf.org and future billion-triple-challenge datasets in prototype testing and evaluation.
Pacific Northwest National Laboratory (09/21/11) Kathryn Lang; Christine Novak
Researchers at the Pacific Northwest National Laboratory, Sandia National Laboratories, and Cray have developed an application that can analyze gigabyte-sized data sets. The application uses semantic factoring to organize data, revealing hidden connections and threads. The researchers used the application to analyze the massive datasets for the Billion Triple Challenge, an international competition aimed at demonstrating capability and innovation for dealing with very large semantic graph databases. The researchers utilized the Cray XMT architecture, which allowed all 624 gigabytes of input data to be held in RAM. The researchers are now developing a prototype that can be adapted to a variety of application domains and datasets, including working with the bio2rdf.org and future billion-triple-challenge datasets in prototype testing and evaluation.
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