Abstract
The message passing model is now widely used for parallel computing, but is still difficult to use with some applications. The explicit data distribution or the explicit dynamic creation of parallel tasks can require a complex algorithm. In this paper, in order to avoid explicit data distribution, we propose a programming approach based on a data load balancing service for MPI-C. Using a parallel version of the merge sort algorithm, we show how our service avoids explicit data distribution completely, easing parallel programming. Some performance results are presented which compare our approach to a version of merge sort with explicit data distribution.
This work is supported by the CONACyT Project 34230-A: Infraestructura para la construcción de aplicaciones fuertemente distribuidas.
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Román-Alonso, G., Castro-García, M.A., Buenabad-Chávez, J. (2004). Easing Message-Passing Parallel Programming Through a Data Balancing Service. In: Kranzlmüller, D., Kacsuk, P., Dongarra, J. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2004. Lecture Notes in Computer Science, vol 3241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30218-6_42
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DOI: https://doi.org/10.1007/978-3-540-30218-6_42
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