The data parallel programming language construct of a "for-each" loop is proposed in the context of hierarchically nested arrays and unbalanced k-ary trees used in high performance applications. In order perform an initial evaluation, an implementation of an automatic parallelization system for C++ programs is introduced, which consists of a preprocessor and a matching library for distributed memory, shared memory and mixed model parallelism. For a full compile time dependence analysis and a tight distributed memory parallelization, some additional application knowledge about alignment of arrays or indirect data access can be put into the application's code data declarations. Results for a multigrid and a fast multipole benchmark code illustrate the concept. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Zumbusch, G. (2006). Data parallel iterators for hierarchical grid and tree algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4128 LNCS, pp. 625–634). Springer Verlag. https://doi.org/10.1007/11823285_65
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