K-Means clustering is widely used in information retrieval and data mining. Distributed K-Means variants have already been proposed, but none of the past algorithms scales to large...
Odysseas Papapetrou, Wolf Siberski, Fabian Leitrit...
We study the problem of query optimization in federated relational database systems. The nature of federated databases explicitly decouples many aspects of the optimization proces...
We propose a distributed parallel support vector machine (DPSVM) training mechanism in a configurable network environment for distributed data mining. The basic idea is to exchange...
To achieve scalable parallel performance in Molecular Dynamics Simulation, we have modeled and implemented several dynamic spatial domain decomposition algorithms. The modeling is ...
Lars S. Nyland, Jan Prins, Ru Huai Yun, Jan Herman...
One of the promises of parallelized discrete-event simulation is that it might provide significant speedups over sequential simulation. In reality, high performance cannot be achi...