New York: Cambridge University Press 2002. High-order methods for incompressible fluid flows. IEEE, pp 94–95ĭeville MO, Fischer PF, Mund EH. In: 2018 IEEE 8th Symposium on Large Data Analysis and Visualization (LDAV). In: Proceedings of the First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, pp 25–29īernardoni B, Ferrier N, Insley J, Papka M.E, Patel S, Rizzi S (2018) In situ visualization and analysis to design large scale experiments in computational fluid dynamics. In: SC ’16: l, pp 921–932Īyachit U, Bauer A, Geveci B, O’Leary P, Moreland K, Fabian N, Mauldin J (2015) ParaView catalyst: enabling in situ data analysis and visualization. 2005 836:717–732.Īyachit U, Bauer A, Duque EPN, Eisenhauer G, Ferrier N, Gu J, Jansen KE, Loring B, Lukic Z, Menon S, Morozov D, O’Leary P, Ranjan R, Rasquin M, Stone CP, Vishwanath V, Weber GH, Whitlock B, Wolf M, Wu KJ, Bethel EW (2016) Performance analysis, design considerations, and applications of extreme-scale in situ infrastructures. The first Helios release that used ParaView Catalyst for in situ capabilities was version 3, which only included streamlines, slices, and contours and. ParaView: an end-user tool for large data visualization. In general, the result of this study highlights the technical challenges posed by the integration of high-performance simulation codes and data-analysis libraries and their practical use in complex cases, even when efficient algorithms already exist for a certain application scenario.Ĭomputational fluid dynamics High-performance computing In situ visualization.Īhrens J, Geveci B, Law C. In our case, better scaling and load-balancing in the parallel image composition would considerably improve the performance of Nek5000 with in situ capabilities. We also identified an imbalance of in situ processing time between rank 0 and all other ranks. Through profiling with Arm MAP, we identified a bottleneck in the image composition step (that uses the Radix-kr algorithm) where a majority of the time is spent on MPI communication. In our study case, a high-fidelity simulation of turbulent flow, we observe that in situ operations significantly limit the strong scalability of the code, reducing the relative parallel efficiency to only ≈ 21 % on 2048 cores (the relative efficiency of Nek5000 without in situ operations is ≈ 99 % ). We perform a strong scalability test up to 2048 cores on KTH's Beskow Cray XC40 supercomputer and assess in situ visualization's impact on the Nek5000 performance. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time.
0 Comments
Leave a Reply. |