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The rate of convergence of net output error is very low when training feedforward neural networks for multiclass problems using the backpropagation algorithm. While backpropagation will reduce the Euclidean distance between the actual and desired output vectors, the differences between some of the components of these vectors increase in the first iteration.(More)
This paper describes the design of the Fortran90D/HPF compiler, a source-to-source parallel compiler for distributed memory systems being developed at Syracuse University. Fortran 90D/HPF is a data parallel language with special directives to specify data alignment and distributions. A systematic methodology to process distribution directives of Fortran(More)
Efficient discover of association rules in large databases is a we 1 studied problem and several ap1y proaches have been proposed. However, it is non trivial to maintain the association rules current when the database is updated since, such updates could invalidate existing rules or introduce new rules. In this paper, we propose an incremental updating(More)
In [5], we have proposed a compilcXime optimization approach, the bottom–up top-down duplication heuristic (BTDH), for static scheduling of directed-cyclic graphs @AGs) on distributed memory multiprocessors (DMMs). In this paper, we discuss the applications of BTDH for list scheduling algorithms (LSAS). There are two ways to useBTDH forLSAs. (1) BTDH can be(More)
Multicore architectures, especially chip multi-processors, have been widely acknowledged as a successful design paradigm. Existing approaches primarily target application-driven partitioning of the shared cache to alleviate inter-core cache interference so that both performance and energy efficiency are improved. Dynamic cache reconfiguration is a promising(More)
When anomaly detection software is used as a data analysis tool, finding the hardest-to-detect anomalies is not the most critical task. Rather, it is often more important to make sure that those anomalies that are reported to the user are in fact interesting. If too many unremarkable data points are returned to the user labeled as candidate anomalies, the(More)
Summary form only given. We discuss a novel framework for policy based scheduling in resource allocation of grid computing. The framework has several features. First, the scheduling strategy can control the request assignment to grid resources by adjusting usage accounts or request priorities. Second, Efficient resource management is achieved by assigning(More)