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On-the-fly memory compression for multibody algorithms

Eckhardt, W.; Glas, R.; Korzh, D.; Wallner, S.; Weinzierl, T.

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W. Eckhardt

R. Glas

D. Korzh

S. Wallner


G. R. Joubert

H. Leather

M. Parsons

F. Peters

M. Sawyer


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.


Eckhardt, W., Glas, R., Korzh, D., Wallner, S., & Weinzierl, T. (2016). On-the-fly memory compression for multibody algorithms. In G. R. Joubert, H. Leather, M. Parsons, F. Peters, & M. Sawyer (Eds.), Parallel computing : on the road to exascale (421-430).

Conference Name International Conference on Parallel Computing (ParCo) 2015
Conference Location Edinburgh, Scotland
Start Date Sep 1, 2015
End Date Sep 4, 2015
Acceptance Date Sep 29, 2015
Publication Date Apr 1, 2016
Deposit Date Oct 1, 2015
Publicly Available Date Nov 9, 2015
Pages 421-430
Series Title Advances in parallel computing
Series Number 27
Series ISSN 0927-5452
Book Title Parallel computing : on the road to exascale.
ISBN 9781614996200
Public URL
Publisher URL
Additional Information Conference dates: 1-4 September 2015


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