Parallel I/O plays an increasingly important role in today’s data intensive computing applications. While much attention has been paid to parallel read performance, most of this...
In this paper, we propose a new image clustering algorithm, referred to as Clustering using Local Discriminant Models and Global Integration (LDMGI). To deal with the data points s...
Yi Yang, Dong Xu, Feiping Nie, Shuicheng Yan, Yuet...
We describe and evaluate a new, pipelined algorithm for large, irregular all-gather problems. In the irregular all-gather problem each process in a set of processes contributes in...
Clusters of workstations have emerged as a popular platform for parallel and distributed computing. Commodity high speed networks which are used to connect workstation clusters pr...
Vijay Moorthy, Matthew G. Jacunski, Manoj Pillai, ...
Unsupervised clustering is a powerful technique for understanding multispectral and hyperspectral images, being k-means one of the most used iterative approaches. It is a simple th...