We present a parallel version of BIRCH with the objective of enhancing the scalability without compromising on the quality of clustering. The incoming data is distributed in a cyc...
This work identifies practical compiling techniques for scalable shared memory machines. For this, we have focused on experimental studies using a real machine and representative ...
Yunheung Paek, Angeles G. Navarro, Emilio L. Zapat...
Tiling exploits temporal reuse carried by an outer loop of a loop nest to enhance cache locality. Loop skewing is typically required to make tiling legal. This restricts parallelis...
A distributed memory parallel version of the group average Hierarchical Agglomerative Clustering algorithm is proposed to enable scaling the document clustering problem to large c...
Rebecca Cathey, Eric C. Jensen, Steven M. Beitzel,...
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...