Consider a workload in which massively parallel tasks that require large resource pools are interleaved with short tasks that require fast response but consume fewer resources. We...
Mark Silberstein, Dan Geiger, Assaf Schuster, Miro...
—Modern large-scale grid computing for processing advanced science and engineering applications relies on geographically distributed clusters. In such highly distributed environm...
Daniel M. Batista, Luciano Chaves, Nelson L. S. da...
Efficient loop scheduling on parallel and distributed systems depends mostly on load balancing, especially on heterogeneous PC-based cluster and grid computing environments. In thi...
This paper studies five real-world data intensive workflow applications in the fields of natural language processing, astronomy image analysis, and web data analysis. Data intensiv...
The mainstream adoption of cluster, grid, and most recently cloud computing models have broadened the applicability of parallel programming from scientific communities to
the bus...