Biclustering refers to simultaneous clustering of objects and their features. Use of biclustering is gaining momentum in areas such as text mining, gene expression analysis and co...
Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-...
Irregular and iterative I/O-intensive jobs need a different approach from parallel job schedulers. The focus in this case is not only the processing requirements anymore: memory, ...
The current trend in HPC hardware is towards clusters of shared-memory (SMP) compute nodes. For applications developers the major question is how best to program these SMP cluster...
Abstract--Determinant Quantum Monte Carlo (DQMC) simulation has been widely used to reveal macroscopic properties of strong correlated materials. However, parallelization of the DQ...
We present SNAP (Small-world Network Analysis and Partitioning), an open-source graph framework for exploratory study and partitioning of large-scale networks. To illustrate the c...