Cloud Research InfoCloud focuses on information management in very large infrastructures such as clusters, supercomputers, GPUs and the Cloud. Our research interests include: Extremely large databases; Cloud Computing; Scientific data; Graphs, including RDF; Very Long Strings; Parallel and Distributed systems; Data mining and Knowledge extraction; and Bioinformatics. Software MIZAN: A Pregel clone for large-scale graph processing SIGMOD programming contest InfoCloud, in collaboration with MIT CSAIL, is organizing the 2013 ACM-SIGMOD programming contest. Prize: $5,000 plus travel grant to New York. http:/
Collaborators Research We are investigating in developing a parallel graph data management. Graph data management. We have developed a strong string processing tool. We are developing a graph and string processing engine.
Research Research The KAUST InfoCloud Group focuses on Databases and Information management Specifically, we are working on: Database outsourcing and Cloud Computing Mobile Computing Parallel and Distributed systems Peer-to-Peer OLAP and Data Warehouses Graphs, RDF and String processing Spatial-Temporal and High-dimensional Databases Data Security - Privacy - Anonymity Bioinformatics & Machine learning
Software Research Disclaimer: The software on this page is provided on an as is basis for research purposes. There is no additional support offered, nor are the author(s) or their institutions liable under any circumstances Suffix Tree Contraction ERA_Software: Efficient Serial and Parallel Suffix Tree Construction We developed a disk-based suffix tree construction method, called Elastic Range (ERA), which works efficiently with very long strings that are much larger than the available memory. ERA partitions the tree construction process horizontally and vertically and minimizes I/Os by dynamically adjusting the
