Wissenschaftliche Artikel

Träff, J. L., Hunold, S., Mercier, G., & Holmes, D. J. (2021). MPI collective communication through a single set of interfaces: A case for orthogonality. Parallel Computing: Systems & Applications, 107(102826), 102826. https://doi.org/10.1016/j.parco.2021.102826 ( reposiTUm)
Kirchbach, K. V., Schulz, C., & Träff, J. L. (2020). Better Process Mapping and Sparse Quadratic Assignment. ACM Journal on Experimental Algorithmics, 25, 1–19. https://doi.org/10.1145/3409667 ( reposiTUm)

Beiträge in Tagungsbänden

Vardas, I., Hunold, S., SWARTVAGHER, P., & Träff, J. L. (2024). Improved Parallel Application Performance and Makespan by Colocation and Topology-aware Process Mapping. In 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (pp. 119–124). IEEE. https://doi.org/10.1109/CCGrid59990.2024.00023 ( reposiTUm)
Swartvagher, P., Hunold, S., Träff, J. L., & Vardas, I. (2023). Using Mixed-Radix Decomposition to Enumerate Computational Resources of Deeply Hierarchical Architectures. In Proceedings of 2023 SC23 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis (SC 2023 Workshops) (pp. 405–415). ACM. https://doi.org/10.1145/3624062.3624109 ( reposiTUm)
Träff, J. L., & Vardas, I. (2023). Library Development with MPI: Attributes, Request Objects, Group Communicator Creation, Local Reductions, and Datatypes. In Proceedings of the 30th European MPI Users’ Group Meeting (EUROMPI 23). 30th European MPI Users’ Group Meeting (EuroMPI 2023), Bristol, United Kingdom of Great Britain and Northern Ireland (the). ACM. https://doi.org/10.1145/3615318.3615323 ( reposiTUm)
Swartvagher, P., Vardas, I., Hunold, S., & Träff, J. L. (2023). Rank Reordering within MPI Communicators to Exploit Deep Hierarchal Architectures of Supercomputers. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2023 - ASHPC23 (pp. 61–61). EuroCC Austria. https://doi.org/10.34726/5368 ( reposiTUm)
Vardas, I., Hunold, S., Swartvagher, P., & Träff, J. L. (2023). Effects of Mapping Strategies on Average Duration and Throughput of Colocated HPC Applications. In E. Reiter (Ed.), Austrian-Slovenian HPC Meeting 2023 - ASHPC23 (pp. 10–10). EuroCC Austria. https://doi.org/10.34726/5330 ( reposiTUm)
Vardas, I., Hunold, S., Ajanohoun, J. I., & Traff, J. L. (2022). mpisee: MPI Profiling for Communication and Communicator Structure. In 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops (IPDPSW 2022) (pp. 520–529). IEEE. https://doi.org/10.1109/IPDPSW55747.2022.00092 ( reposiTUm)
Hunold, S., Ajanohoun, J. I., Vardas, I., & Träff, J. L. (2022). An Overhead Analysis of MPI Profiling and Tracing Tools. In C. Scully-Allison, R. Liem, & A. V. Solorzano (Eds.), PERMAVOST 2022: Proceedings of the 2nd Workshop on Performance Engineering, Modelling, Analysis, and Visualization Strategy (pp. 5–13). Association for Computing Machinery (ACM). https://doi.org/10.1145/3526063.3535353 ( reposiTUm)
Faraj, M. F., van der Grinten, A., Meyerhenke, H., Träff, J. L., & Schulz, C. (2020). High-Quality Hierarchical Process Mapping. In S. Faro & D. Cantone (Eds.), 18th International Symposium on Experimental Algorithms, SEA 2020 (pp. 4:1-4:15). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SEA.2020.4 ( reposiTUm)
von Kirchbach, K., Lehr, M., Hunold, S., Schulz, C., & Träff, J. L. (2020). Efficient Process-to-Node Mapping Algorithms for Stencil Computations. In 2020 IEEE International Conference on Cluster Computing (CLUSTER). IEEE International Conference on Cluster Computing (IEEE Cluster 2020) - Online Conference, Kobe, Japan. IEEE. https://doi.org/10.1109/cluster49012.2020.00011 ( reposiTUm)

Preprints

Hunold, S., von Kirchbach, K., Lehr, M., Schulz, C., & Träff, J. L. (2020). Efficient Process-to-Node Mapping Algorithms for Stencil Computations. arXiv. https://doi.org/10.48550/arXiv.2005.09521 ( reposiTUm)