Thrill is a C++ framework for distributed Big Data computations on a cluster. It is currently in development and aims to be more versatile and performant than Java-based alternatives.
We have designed and implemented the Google File System, a scalable distributed file system for large distributed data-intensive applications. It provides fault tolerance while running on inexpensive commodity hardware, and it delivers high aggregate performance to a large number of clients.
DDM algorithms for mining large distributed data sources,DDM algorithms for monitoring data streams, Privacy preserving distributed multi-party data mining;Sensor networks, Grid mining, mobile/wireless;applications, privacy preserving security-related
Parallel or distributed mining,Cluster-based data mining algorithms and systems,Grid-based data mining,lgorithms and systems;Peer-to-Peer based data mining algorithms and systems;Data mining algorithms and systems based on parallel hardware platforms
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