Predicting the Best Mapping for Efficient Exploitation of Task and Data Parallelism
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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 for the execution of message-passing applications on distributed systems. Using this environment, we evaluate the performance of an image processing application for the different parallelizing alternatives, and we propose the ways to improve its performance.
Is part ofLecture Notes in Computer Science, 2003, vol. 2790, p. 218-223
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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 ...
Yuan, X.; Roig Mateu, Concepció; Ripoll, A.; Senar, M.A.; Guirado Fernández, Fernando; Luque, Emilio (Springer Verlag, 2002)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 ...
Guirado Fernández, Fernando; Ripoll, A.; Roig Mateu, Concepció; Hernàndez, A.; Luque, Emilio (Springer Verlag, 2006)There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when executing them. In this ...