This paper presents a novel reconfigurable data flow processing architecture that promises high performance by explicitly targeting both fine- and course-grained parallelism. This...
Charles L. Cathey, Jason D. Bakos, Duncan A. Buell
The deluge of available data for analysis demands the need to scale the performance of data mining implementations. With the current architectural trends, one of the major challen...
We describe the design and current status of our effort to implement the programming model of nested data parallelism into the Glasgow Haskell Compiler. We extended the original p...
Manuel M. T. Chakravarty, Roman Leshchinskiy, Simo...
This paper describes the design and implementation on MIMD parallel machines of P-AutoClass, a parallel version of the AutoClass system based upon the Bayesian method for determini...
Data replication is a key issue in a Data Grid and can be managed in different ways and at different levels of granularity: for example, at the file level or object level. In the ...