Parallel programmers typically assume that all resources required for a program’s execution are dedicated to that purpose. However, in local and wide area networks, contention f...
Alain J. Roy, Ian T. Foster, William Gropp, Nichol...
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
DataScalar architectures improve memory system performance by running computation redundantly across multiple processors, which are each tightly coupled with an associated memory....
Map-Reduce is a programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. Through ...
Hung-chih Yang, Ali Dasdan, Ruey-Lung Hsiao, Dougl...
Output coding is a general framework for solving multiclass categorization problems. Previous research on output codes has focused on building multiclass machines given predefine...