Performance and Predictability of MPI and BSP Programs on the CRAY T3E

González, Jesús A.; Rodríguez, Casiano; Roda, José L.; González-Morales, Daniel; Sande, Francisco de; Almeida, Francisco; León, Coromoto

doi:10.1007/3-540-48158-3_4

Cited by 2 publications

(2 citation statements)

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“…Singles value of g and L, independent of the number of processors, were used. As can be deduced from this experiment and the study of the capacity predictions using the flat-BSP model with the Oxford BSP library [5], the introduction of groups in BSP does not necessarily implies a loss of accuracy [3]. …”

Section: Computational Resultsmentioning

confidence: 99%

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Groups in bulk synchronous parallel computing

González

León

Piccoli

et al.

Proceedings 8th Euromicro Workshop on Parallel and Distributed Processing

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An extension to the Bulk Synchronous Parallel Model (BSP) to allow the use of asynchronous BSP groups of processors is presented. In this model, called Nested BSP, processor groups can be divided and processors in a group synchronize through group dependent Collective operations generalizing the concept of barrier synchronization. A classification of Problems and Algorithms attending to their parallel Input-Output distribution is provided. For one of these problem classes, the called Common-Common class, we present a general strategy to derive efficient parallel algorithms. Algorithms belonging to this class allow the arbitrary division of the processor subsets, easing the opportunities of the underlying BSP software to divide the network in independent sub networks, minimizing the impact of the traffic in the rest of the network in the predicted cost. The expressiveness of the model is exemplified through three divide and conquer programs. The computational results for these programs in six high performance supercomputers show both the accuracy of the model and the optimality of the speedups for the class of problems considered.

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Section: Computational Resultsmentioning

confidence: 99%

“…After this step, the processor set Q becomes an inner node in the processor hierarchy and the new subsets Q i will be leaf sets. 3. Execute the parallel tasks T i (in i , out i ).…”

Section: The Nested Bsp Computing Modelmentioning

confidence: 99%