Abstract
Dataflow-based systems of parallel programming, such as LuNA fragmented programming system, often lack efficiency in high performance computations due to a high degree of non-determinism of a parallel program execution and execution overhead it causes. The authors concern defining control flow in LuNA programs in order to optimize their execution performance. The basic idea is to aggregate several fragments of a program and to execute them under control flow, thus reducing both surplus parallelism and system overhead. Tests presented show effectiveness of the proposed approach.
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This work was supported by Russian Foundation for Basic Research (grants 14-07-00381 a and 14-01-31328 mol_a).
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Malyshkin, V.E., Perepelkin, V.A., Tkacheva, A.A. (2015). Control Flow Usage to Improve Performance of Fragmented Programs Execution. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2015. Lecture Notes in Computer Science(), vol 9251. Springer, Cham. https://doi.org/10.1007/978-3-319-21909-7_9
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DOI: https://doi.org/10.1007/978-3-319-21909-7_9
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