We are developing a full software system for accelerating semantic graph databases on commodity cluster that scales to hundreds of nodes while maintaining constant query throughput. Our framework comprises a SPARQL to C++ compiler, a library of parallel graph methods and a custom multithreaded runtime layer, which provides a Partitioned Global Address Space (PGAS) programming model with fork/join parallelism and automatic load balancing over a commodity clusters. We present preliminary results for the compiler and for the runtime.
Revised: March 11, 2014 |
Published: October 6, 2013
Citation
Morari A., V.G. Castellana, D.J. Haglin, J.T. Feo, J.R. Weaver, A. Tumeo, and O. Villa. 2013.Accelerating semantic graph databases on commodity clusters. In IEEE International Conference on Big Data (Big Data 2013), October 6-9, 2013, Silicon Valley, California, 768-772. Piscataway, New Jersey:Institute of Electrical and Electronics Engineers.PNNL-SA-98187.doi:10.1109/BigData.2013.6691650