Abstract
PEPC (Pretty Efficient Parallel Coulomb-solver) is a complex HPC application developed at the Jülich Supercomputing Centre, scaling to thousands of processors. This is a case study of challenges faced when applying the Scalasca parallel performance analysis toolset to this intricate example at relatively high processor counts. The Scalasca version used in this study has been extended to distinguish iteration/timestep phases to provide a better view of the underlying mechanisms of the application execution. The added value of the additional analyses and presentations is then assessed to determine requirements for possible future integration within Scalasca.
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Wolf, F., Wylie, B.J.N., Ábrahám, E., Becker, D., Frings, W., Fürlinger, K., Geimer, M., Hermanns, M.-A., Mohr, B., Moore, S., Pfeifer, M., Szebenyi, Z.: Usage of the Scalasca toolset for scalable performance analysis of large-scale parallel applications, in Tools for High Performance Computing. In: Proc. 2nd Int’l Workshop on Tools for High Performance Computing, Stuttgart, Germany, pp. 167–181. Springer, Heidelberg (2008)
Jülich Supercomputing Centre, Scalasca toolset for scalable performance analysis of large-scale parallel applications, http://www.scalasca.org/
Wylie, B.J.N., Wolf, F., Mohr, B., Geimer, M.: Integrated runtime measurement summarization and selective event tracing for scalable parallel execution performance diagnosis. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds.) PARA 2006. LNCS, vol. 4699, pp. 460–469. Springer, Heidelberg (2007)
Malony, A.D., Shende, S.S., Morris, A.: Phase-based parallel performance profiling, In: Parallel Computing: Architectures, Algorithms and Applications. Proc. 11th ParCo Conf., Málaga, Spain, October 2006. NIC Series, vol. 33, pp. 203–210. John von Neumann Institute for Computing, Jülich (2006)
Fürlinger, K., Gerndt, M., Dongarra, J.: On using incremental profiling for the performance analysis of shared-memory parallel applications. In: Kermarrec, A.-M., Bougé, L., Priol, T. (eds.) Euro-Par 2007. LNCS, vol. 4641, pp. 62–71. Springer, Heidelberg (2007)
Szebenyi, Z., Wylie, B.J.N., Wolf, F.: Scalasca parallel performance analyses of SPEC MPI2007 applications. In: Kounev, S., Gorton, I., Sachs, K. (eds.) SIPEW 2008. LNCS, vol. 5119, pp. 99–123. Springer, Heidelberg (2008)
Gibbon, P., Frings, W., Dominiczak, S., Mohr, B.: Performance Analysis and Visualization of the N-Body Tree Code PEPC on Massively Parallel Computers. In: Proc. 11th ParCo Conf., Málaga, Spain, October 2006. NIC Series, vol. 33, pp. 367–374. John von Neumann Institute for Computing, Jülich (2006)
Labarta, J., Giménez, J., Martinez, E., González, P., Servat, H., Llort, G., Aguilar, X.: Scalability of Visualization and Tracing Tools. In: Proc. 11th ParCo Conf., Málaga, Spain, October 2006. NIC Series, vol. 33, pp. 869–876. John von Neumann Institute for Computing, Jülich (2006)
Brunst, H., Nagel, W.E.: Scalable Performance Analysis of Parallel Systems: Concepts and Experiences. In: Proc. 10th ParCo Conf., Dresden, Germany, September 2003, pp. 737–744 (2003)
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Szebenyi, Z., Wylie, B.J.N., Wolf, F. (2009). Scalasca Parallel Performance Analyses of PEPC. In: César, E., et al. Euro-Par 2008 Workshops - Parallel Processing. Euro-Par 2008. Lecture Notes in Computer Science, vol 5415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00955-6_35
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DOI: https://doi.org/10.1007/978-3-642-00955-6_35
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