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Durham Research Online
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On-the-fly memory compression for multibody algorithms.

Eckhardt, W. and Glas, R. and Korzh, D. and Wallner, S. and Weinzierl, T. (2016) 'On-the-fly memory compression for multibody algorithms.', in Parallel computing : on the road to exascale. Amsterdam: IOS Press, pp. 421-430. Advances in parallel computing. (27).

Abstract

Memory and bandwidth demands challenge developers of particle-based codes that have to scale on new architectures, as the growth of concurrency outperforms improvements in memory access facilities, as the memory per core tends to stagnate, and as communication networks cannot increase bandwidth arbitrary. We propose to analyse each particle of such a code to find out whether a hierarchical data representation storing data with reduced precision caps the memory demands without exceeding given error bounds. For admissible candidates, we perform this compression and thus reduce the pressure on the memory subsystem, lower the total memory footprint and reduce the data to be exchanged via MPI. Notably, our analysis and transformation changes the data compression dynamically, i.e. the choice of data format follows the solution characteristics, and it does not require us to alter the core simulation code.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:http://ebooks.iospress.nl/volumearticle/42680
Publisher statement:The final publication is available at IOS Press through http://dx.doi.org/10.3233/978-1-61499-621-7-421
Date accepted:29 September 2015
Date deposited:09 November 2015
Date of first online publication:April 2016
Date first made open access:No date available

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