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Abstract: Shared-memory and data-parallel programming models are two important paradigms for scientific applications. Both models provide high-level program abstractions, and simple and uniform views of network structures. The common features of the two models significantly simplify program coding and debugging for scientific applications. However, the underlining execution and overhead patterns are significantly different between the two models due to their programming constraints, and due to... (Update)
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BibTeX entry: (Update)
@misc{ patterns-comparative,
author = "Data-Parallel Execution Patterns",
title = "Comparative Evaluation and Case Studies of Shared-Memory and",
url = "citeseer.ist.psu.edu/765863.html" }
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