Skeletons are reusable, parameterized components with well-defined semantics and pre-packaged efficient parallel implementation. This paper develops a new, provably cost-optimal implementation of the DS (double-scan) skeleton for the divide-and-conquer paradigm. Our implementation is based on a novel data structure called plist (pointed list); implementation's performance is estimated using an analytical model. We demonstrate the use of the DS skeleton for parallelizing a tridiagonal system solver and report experimental results for its MPI implementation on a Cray T3E and a Linux cluster: they confirm the performance improvement achieved by the cost-optimal implementation and demonstrate its good predictability by our performance model. © Springer-Verlag 2003.
CITATION STYLE
Bischof, H., Gorlatch, S., & Kitzelmann, E. (2004). Cost Optimality and Predictability of Parallel Programming with Skeletons. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2790, 682–693. https://doi.org/10.1007/978-3-540-45209-6_97
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