Clustering is one of the most important tasks for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial c...
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
A metascalable (or “design once, scale on new architectures”) parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials...
Ken-ichi Nomura, Richard Seymour, Weiqiang Wang, H...
This paper presents a new approach towards parallel I/O for message-passing (MPI) applications on clusters built with commodity hardware and an SCI interconnect: instead of using t...