AMEEDA: A general-purpose mapping tool for parallel applications on dedicated clusters
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The mapping of parallel applications constitutes a difficult problem for which very few practical tools are available. AMEEDA has been developed in order to overcome the lack of a general-purpose mapping tool. The automatic services provided in AMEEDA include instrumentation facilities, parameter extraction modules and mapping strategies. With all these services, and a novel graph formalism called TTIG, users can apply different mapping strategies to the corresponding application through an easy-to-use GUI, and run the application on a PVM cluster using the desired mapping.
Is part ofLecture Notes in Computer Science, 2002, vol. 2400, p. 248-252
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Roig Mateu, Concepció; Ripoll, A.; Senar, M.A.; Guirado Fernández, Fernando; Luque, Emilio (Springer Verlag, 2000)In the distributed processing area, mapping and scheduling are very important issues in order to exploit the gain from parallelization. The generation of efficient static mapping techniques implies a previous modelling ...
Guirado Fernández, Fernando; Ripoll, A.; Roig Mateu, Concepció; Yuan, X.; Luque, Emilio (Springer Verlag, 2003)The detection and exploitation of different kinds of parallelism, task parallelism and data parallelism often leads to efficient parallel programs. This paper presents a simulation environment to predict the best mapping ...
Guirado Fernández, Fernando; Roig Mateu, Concepció; Ripoll, A. (Elsevier, 2013)The exploitation of throughput in a parallel application that processes an input data stream is a difficult challenge. For typical coarse-grain applications, where the computation time of tasks is greater than their ...