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A Study on the Performance of Reproducible Computations

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 11887)


Parallel computations are intrinsically non-reproducible, due to a combined effect of non-deterministic parallel reductions and non-associative floating point operations. Different strategies have been proposed in literature to alleviate this issue or eliminate it altogether, however at present there is no study on the performance impact of associative floating point operations on large scale applications. In this work, we implement associative operations using binned doubles in MiniFE, and perform various performance tests on Cirrus and Fulhame, two state-of-the-art HPC systems.


  • Reproducibility
  • Binned doubles
  • Performance

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  • DOI: 10.1007/978-3-030-34356-9_33
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This research is supported by Rolls-Royce plc through the EPSRC ASiMoV Prosperity Partnership Project. The authors would like to thank Rolls-Royce plc for granting permission to publish this work. The experiments were undertaken on two different systems: the Cirrus UK National Tier-2 HPC Service at EPCC, funded by the University of Edinburgh and EPSRC (EP/P020267/1); and the Fulhame system, which is supplied to EPCC as part of the Catalyst UK program, a collaboration with Hewlett Packard Enterprise, Arm and SUSE to accelerate the adoption of Arm based supercomputer applications in the UK.

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Correspondence to Nico Bombace .

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Bombace, N., Weiland, M. (2019). A Study on the Performance of Reproducible Computations. In: Weiland, M., Juckeland, G., Alam, S., Jagode, H. (eds) High Performance Computing. ISC High Performance 2019. Lecture Notes in Computer Science(), vol 11887. Springer, Cham.

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