Abstract
In the early phases of an automotive industry development, design time can be substantially improved by using automated tools that assist engineers to perform repetitive and time consuming tasks, speeding up automotive products development and providing quality guarantees over otherwise error-prone processes. MERGE is such a tool from industry that prepares CAD models for electrophoretic deposition simulation. In this paper we describe the parallelization and optimization of MERGE for distributed memory parallel architectures. For this purpose we create a dynamic tree of tasks at runtime, analyze its load behavior and execute it through a master-worker compute paradigm based on different scheduling policies. Our implementation is based on a hybrid MPI-OpenMP version which results in a considerable improvement of both resource utilization and performance. Empirical performance results are presented for our new approach which achieve a speedup of up to 18 on an SMP cluster architecture.
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References
Strodthoff, B., Schifko, M., Jttler, B.: Horizontal decomposition of triangulated solids for the simulation of dip-coating processes. CAD Comput. Aided Des. 43(12), 1891–1901 (2011)
Engineering Software Steyr GmbHd: Merge software (2015). http://www.essteyr.com/en/products/merge.html
Frostig, E.: A Stochastic Scheduling Problem with Intree Precedence Constraints on JSTOR (1988)
Kulkarni, V.G., Chimento, P.F.: Optimal scheduling of exponential tasks with in-tree precedence constraints on two parallel processors subject to failure and repair. Oper. Res. 40(3–supplement–2), S263–S271 (1992)
Diakité, S., Nicod, J.M., Philippe, L., Toch, L.: Assessing new approaches to schedule a batch of identical intree-shaped workflows on a heterogeneous platform. Int. J. Parallel Emergent Distrib. Syst. 27(1), 79–107 (2012)
Drosinos, N., Koziris, N.: Performance comparison of pure MPI vs hybrid MPI-OpenMP parallelization models on SMP clusters. In: 18th International Parallel and Distributed Processing Symposium, 2004, Proceedings, pp. 15–24. IEEE (2004)
Xuan, H., Tong, W., Gong, Z., Lan, Y.: Implementation and performance analysis of hybrid MPI+OpenMP programming for parallel MLFMA on SMP cluster. In: 2012 Third International Conference on Intelligent Control and Information Processing, pp. 744–748. IEEE, July 2012
Schifko, M., Jüttler, B., Kornberger, B.: Industrial application of exact boolean operations for meshes. In: Proceedings of the 26th Spring Conference on Computer Graphics, SCCG 2010, pp. 165–172. ACM, New York (2010)
Cgal, Computational Geometry Algorithms Library. http://www.cgal.org
Ayuso, L., Jordan, H., Fahringer, T., Kornberger, B., Schifko, M., Höckner, B., Moosbrugger, S., Verma, K.: Parallelizing a CAD model processing tool from the automotive industry. In: Lopes, L., et al. (eds.) Euro-Par 2014, Part I. LNCS, vol. 8805, pp. 24–35. Springer, Heidelberg (2014)
Pinedo, M.L.: Scheduling: Theory, Algorithms, and Systems. Springer Science & Business Media, New York (2012)
Dong, S., Karniadakis, G.E.: Dual-level parallelism for deterministic and stochastic CFD problems. Supercomputing, ACM/IEEE, pp. 1–17 (2002)
Dean, J., Ghemawat, S.: Mapreduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)
Mercier, G., Clet-Ortega, J.: Towards an efficient process placement policy for MPI applications in multicore environments. In: Ropo, M., Westerholm, J., Dongarra, J. (eds.) PVM/MPI. LNCS, vol. 5759, pp. 104–115. Springer, Heidelberg (2009)
Gates, A.F., Natkovich, O., Chopra, S., Kamath, P., Narayanamurthy, S.M., Olston, C., Benjaminn, R., Srinavasan, S., Srivastava, U.: Building a high-level dataflow system on top of map-reduce: the pig experience. In: VLDB 2009, pp. 1–12 (2009)
Acknowledgments
This research has been funded by the Austrian Research Promotion Agency under contract 834307 (AutoCore), and supported by the Austrian Ministry of Science BMWF as part of the UniInfrastrukturprogramm of the Focal Point Scientific Computing at the University of Innsbruck.
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Ayuso, L., Durillo, J.J., Kornberger, B., Schifko, M., Fahringer, T. (2016). Parallelization and Optimization of a CAD Model Processing Tool from the Automotive Industry to Distributed Memory Parallel Computers. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2015. Lecture Notes in Computer Science(), vol 9573. Springer, Cham. https://doi.org/10.1007/978-3-319-32149-3_36
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DOI: https://doi.org/10.1007/978-3-319-32149-3_36
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