Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Recently, the high-performance computing community has realized that power is a performance-limiting factor. One reason for this is that supercomputing centers have limited power ...
Robert Springer, David K. Lowenthal, Barry Rountre...
Parallel dataflow programming frameworks such as Map-Reduce are increasingly being used for large scale data analysis on computing clouds. It is therefore becoming important to a...
This paper proposes a simple and efficient implementation method for a hierarchical coarse grain task parallel processing scheme on a SMP machine. OSCAR multigrain parallelizing c...
Predictable network computing still involves a number of open questions. One such question is providing a controlled amount of CPU time to distributed processes. Mechanisms to cont...