This work addresses the need for stateful dataflow programs that can rapidly sift through huge, evolving data sets. These data-intensive applications perform complex multi-step c...
Dionysios Logothetis, Christopher Olston, Benjamin...
The knowledge discovery process is interactive in nature and therefore minimizing query response time is imperative. The compute and memory intensive nature of data mining algorit...
Amol Ghoting, Gregory Buehrer, Matthew Goyder, Shi...
This paper presents a high-performance Distributed Shared Memory system called VODCA, which supports a novel View-Oriented Parallel Programming on cluster computers. One advantage...
Zhiyi Huang, Wenguang Chen, Martin K. Purvis, Weim...
We present a new result concerning the parallelisation of DBSCAN, a Data Mining algorithm for density-based spatial clustering. The overall structure of DBSCAN has been mapped to a...
As heterogeneous parallel systems become dominant, application developers are being forced to turn to an incompatible mix of low level programming models (e.g. OpenMP, MPI, CUDA, ...