High Performance Graph Data Management and Mining with X10

Abstract

Graph data management and mining in HPC environments has been a widely discussed issue in recent times. In this talk I will describe the use of Partitioned Global Address Space languages for graph data mining and management. I will first discuss the rationale behind X10 based graph libraries and graph database benchmarks using ScaleGraph and XGDBench as examples. Next, I will take Acacia which is completely developed with X10 language as an example system and describe our experience with implementing such high performance system with X10. In this talk I will describe how RDF processing and Streaming extensions have been implemented in Acacia. Finally, I will highlight some of the notable areas which need further attention in future.