SPP 1648:  Software for Exascale Computing

• Subject Area: Computer Science, Systems and Electrical Engineering ; Biology ; Geosciences ; Mechanical and Industrial Engineering ; Mathematics ; Physics ; Thermal Engineering/Process Engineering
• Term: from 2012 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 214420555

• Final Report Year: 2020

Final Report Abstract

No abstract available

Publications

• Using automated performance modeling to find scalability bugs in complex codes. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, p. 45. IEEE, Piscataway (2013)
  Calotoiu, A., Hoefler, T., Poke, M., Wolf, F.
  (See online at https://doi.org/10.1145/2503210.2503277)
• DASH: data structures and algorithms with support for hierarchical locality. In: European Conference on Parallel Processing, pp. 542–552. Springer, Berlin (2014)
  Fürlinger, K., Glass, C., Gracia, J., Knüpfer, A., Tao, J., Hünichnich, D., Idrees, K., Maiterth, M., Mhedheb, Y., Zhou, H.
  (See online at https://doi.org/10.1007/978-3-319-14313-2_46)
• EXA-DUNE: flexible PDE solvers, numerical methods and applications. In: European Conference on Parallel Processing, pp. 530–541. Springer, Berlin (2014)
  Bastian, P., Engwer, C., Göddeke, D., Iliev, O., Ippisch, O., Ohlberger, M., Turek, S., Fahlke, J., Kaulmann, S., Steffen Müthing, S., et al.
  (See online at https://doi.org/10.1007/978-3-319-14313-2_45)
• Increasing the performance of the Jacobi–Davidson method by blocking. SIAM J. Sci. Comput. 37(6), C697–C722 (2015)
  Röhrig-Zöllner, M., Thies, J., Kreutzer, M., Alvermann, A., Pieper, A., Basermann, A., Hager, G., Wellein, G., Fehske, H.
  (See online at https://doi.org/10.1137/140976017)
• Portable node-level performance optimization for the fast multipole method. In: Recent Trends in Computational Engineering-CE2014, pp. 29–46. Springer, Berlin (2015)
  Beckmann, A., Kabadshow, I.
  (See online at https://doi.org/10.1007/978-3-319-22997-3_2)
• Time-parallel gravitational collapse simulation. Commun. Appl. Math. Comput. Sci. 12(1), 109–128 (2015)
  Kreienbuehl, A., Benedusi, P., Ruprecht, D., Krause, R.
  (See online at https://doi.org/10.2140/camcos.2017.12.109)
• Global communication schemes for the numerical solution of high-dimensional PDEs. Parallel Comput. 52, 78–105 (2016)
  Hupp, P., Heene, M., Jacob, R., Pflüger, D.
  (See online at https://doi.org/10.1016/j.parco.2015.12.006)
• High-performance implementation of Chebyshev filter diagonalization for interior eigenvalue computations. J. Comput. Phys. 325, 226– 243 (2016)
  Pieper, A., Kreutzer, M., Alvermann, A., Galgon, M., Fehske, H., Hager, G., Lang, B., Wellein, G.
  (See online at https://doi.org/10.1016/j.jcp.2016.08.027)
• Parallel coupling numerics for partitioned fluid–structure interaction simulations. Comput. Math. Appl. 71(4), 869–891 (2016)
  Mehl, M., Uekermann, B., Bijl, H., Blom, D., Gatzhammer, B., Van Zuijlen, A.
  (See online at https://doi.org/10.1016/j.camwa.2015.12.025)
• Resilience for massively parallel multigrid solvers. SIAM J. Sci. Comput. 38(5), S217–S239 (2016)
  Huber, M., Gmeiner, B., Rüde, U., Wohlmuth, B.
  (See online at https://doi.org/10.1137/15M1026122)
• A highly scalable, algorithm-based fault-tolerant solver for gyrokinetic plasma simulations. In: Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, pp. 1–8 (2017)
  Obersteiner, M., Hinojosa, A.P., Heene, M., Bungartz, H.J., Pflüger, D.
  (See online at https://doi.org/10.1145/3148226.3148229)
• A scala prototype to generate multigrid solver implementations for different problems and target multi-core platforms. Int. J. Comput. Sci. Eng. 14(2), 150–163 (2017)
  Köstler, H., Schmitt, C., Kuckuk, S., Kronawitter, S., Hannig, F., Teich, J., Rüde, U., Lengauer, C.
  (See online at https://doi.org/10.1504/IJCSE.2017.082879)
• Isoefficiency in practice: configuring and understanding the performance of task-based applications. In: ACM SIGPLAN Notices, vol. 52, pp. 131–143. ACM, New York (2017)
  Shudler, S., Calotoiu, A., Hoefler, T., Wolf, F.
  (See online at https://doi.org/10.1145/3155284.3018770)
• Toward decoupling the selection of compression algorithms from quality constraints. In: International Conference on High Performance Computing, pp. 3–14. Springer, Berlin (2017)
  Kunkel, J., Novikova, A., Betke, E., Schaare, A.
  (See online at https://doi.org/10.1007/978-3-319-67630-2_1)
• A high-level C++ approach to manage local errors, asynchrony and faults in an MPI application. In: 2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), pp. 714–721. IEEE, Piscataway (2018)
  Engwer, C., Altenbernd, M., Dreier, N.A., Göddeke, D.
  (See online at https://doi.org/10.1109/PDP2018.2018.00117)
• Automating the development of high-performance multigrid solvers. Proc. IEEE 106(11), 1969– 1984 (2018)
  Schmitt, C., Kronawitter, S., Hannig, F., Teich, J., Lengauer, C.
  (See online at https://doi.org/10.1109/JPROC.2018.2854229)
• Efficiency of high-performance discontinuous Galerkin spectral element methods for under-resolved turbulent incompressible flows. Int. J. Numer. Methods Fluids 88(1), 32–54 (2018)
  Fehn, N., Wall, W.A., Kronbichler, M.
  (See online at https://doi.org/10.1002/fld.4511)
• GekkoFS—a temporary distributed file system for HPC applications. In: 2018 IEEE International Conference on Cluster Computing (CLUS- TER), pp. 319–324. IEEE, Piscataway (2018)
  Vef, M.A., Moti, N., Süß, T., Tocci, T., Nou, R., Miranda, A., Cortes, T., Brinkmann, A.
  (See online at https://doi.org/10.1109/CLUSTER.2018.00049)
• Performance portability of earth system models with user-controlled GGDML code translation. In: International Conference on High Performance Computing, pp. 693–710. Springer, Berlin (2018)
  Jum’ah, N., Kunkel, J.
  (See online at https://doi.org/10.1007/978-3-030-02465-9_50)
• Space-time FE-DG Discretization of the anisotropic diffusion equation in any dimension: the spectral symbol. SIAM J. Matrix Anal. Appl. 39(3), 1383–1420 (2018)
  Benedusi, P., Garoni, C., Krause, R., Li, X., Serra-Capizzano, S.
  (See online at https://doi.org/10.1137/17M113527X)
• Thread-local concurrency: a technique to handle data race detection at programming model abstraction. In: Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing, pp. 144–155 (2018)
  Protze, J., Schulz, M., Ahn, D.H., Müller, M.S.
  (See online at https://doi.org/10.1145/3208040.3208056)
• A new load balancing approach for coupled multi-physics simulations. In: 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 676–682. IEEE, Piscataway (2019)
  Totounferoush, A., Pour, N.E., Schröder, J., Roller, S., Mehl, M.
  (See online at https://doi.org/10.1109/IPDPSW.2019.00115)
• Engineering a distributed histogram sort. In: 2019 IEEE International Conference on Cluster Computing (CLUSTER), pp. 1–11. IEEE, Piscataway (2019)
  Kowalewski, R., Jungblut, P., Fürlinger, K.
  (See online at https://doi.org/10.1109/CLUSTER.2019.8891005)
• Fast matrix-free evaluation of discontinuous Galerkin finite element operators. ACM Trans. Math. Softw. 45(3), 1–40 (2019)
  Kronbichler, M., Kormann, K.
  (See online at https://doi.org/10.1145/3325864)
• FFMK: an HPC OS based on the L4Re microkernel. In: Operating Systems for Supercomputers and High Performance Computing, pp. 335–357. Springer, Berlin (2019)
  Weinhold, C., Lackorzynski, A., Härtig, H.
  (See online at https://doi.org/10.1007/978-981-13-6624-6_19)
• Large-scale simulation of mantle convection based on a new matrix-free approach. J. Comput. Sci. 31, 60–76 (2019)
  Bauer, S., Huber, M., Ghelichkhan, S., Mohr, M., Rüde, U., Wohlmuth, B.
  (See online at https://doi.org/10.1016/j.jocs.2018.12.006)
• More bang for your buck: Improved use of GPU nodes for GROMACS 2018. J. comput. chem. 40(27), 2418–2431 (2019)
  Kutzner, C., Páll, S., Fechner, M., Esztermann, A., de Groot, B.L., Grubmüller, H.
  (See online at https://doi.org/10.1002/jcc.26011)
• Multilevel checkpoint/restart for large computational jobs on distributed computing resources. In: IEEE 38th Symposium on Reliable Distributed System (SRDS) (2019)
  Gholami, M., Schintke, F.
  (See online at https://doi.org/10.1109/SRDS47363.2019.00025)
• On the quality of wall time estimates for resource allocation prediction. In: Proceedings of the 48th International Conference on Parallel Processing: Workshops, pp. 1–8. ACM, New York (2019)
  Soysal, M., Berghoff, M., Klusáček, D., Streit, A.
  (See online at https://doi.org/10.1145/3339186.3339204)
• Myx—runtime correctness analysis for multi-level parallel programming paradigms. In: Software for Exascale Computing: SPPEXA 2016– 2019. Lecture Notes in Computational Science and Engineering. Springer, Berlin (2020)
  Protze, J., Tsuji, M., Terboven, C., Dufaud, T., Murai, H., Petiton, S., Emad, N., Müller, M., Boku, T.
  (See online at https://doi.org/10.1007/978-3-030-47956-5_18)