A Python extension for the massively parallel framework waLBerla
Author(s): Bauer M, Schornbaum F, Godenschwager C, Markl M, Anderl D, Köstler H, Rüde U
Publication year: 2014
Conference Proceedings Title: online
Pages range: 1-8
Event: 4th Workshop on Python for High Performance and Scientific Computing
Event location: New Orleans
Start date of the event: 17/11/2014
End date of the event: 17/11/2014
We present a Python extension to the massively parallel HPC framework WALBERLA. WALBERLA is a framework for stencil based algorithms operating on block-structured grids, with the main application field being fluid simulations in complex geometries using the lattice Boltzmann method. Careful performance engineering results in good scalability to over 400,000 cores. To increase the usability and flexibility of the framework, a Python interface was developed. Python extensions are used at all stages of the simulation pipeline: They simplify and automate scenario setup, evaluation, and plotting. We show how our Python interface outperforms the existing a text-filebased configuration mechanism, providing features like automatic nondimensionalization of physical quantities and handling of complex parameter dependencies. Furthermore, Python is used to process and evaluate results while the simulation is running, leading to smaller output files and the possibility to adjust parameters dependent on the current simulation state. C++ data structures are exported such that a seamless interfacing to other numerical Python libraries is possible. The expressive power of Python and the performance of C++ make development of efficient code with low time effort possible.
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APA: Bauer, M., Schornbaum, F., Godenschwager, C., Markl, M., Anderl, D., Köstler, H., & Rüde, U. (2014). A Python extension for the massively parallel framework waLBerla. In online (pp. 1-8).
MLA: Bauer, Martin, et al. "A Python extension for the massively parallel framework waLBerla." Proceedings of the 4th Workshop on Python for High Performance and Scientific Computing, New Orleans 2014. 1-8.