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Supporting indirect data mapping in OpenM

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Code-passing abstractions based on lambdas and blocks are becoming increasingly popular to capture repetitive patterns that are amenable to parallelization. These abstractions improve code mantainability and simplify choosing from a range of mechanisms to implement parallelism. Several frameworks that use this model, including RAJA and Kokkos, employ OpenMP as one of their target parallel models. However, OpenMP inadequately supports the abstraction since it frequently requires information that is not available within the abstraction. Thus, OpenMP requires access to variables and parameters not directly supplied by the base language. This paper explores the issues with supporting these abstractions in OpenMP, with a particular focus on device constructs and the aggregation and passing of OpenMP state through base language abstractions. We propose mechanisms to improve support for these abstractions and also to reduce the burden of duplication in existing OpenMP applications.




Scogland, T. R. W., Keasler, J., Gyllenhaal, J., Hornung, R., de Supinski, B. R., & Finkel, H. (2015). Supporting indirect data mapping in OpenM. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9342, pp. 260–272). Springer Verlag.

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