Publications

Found 6 results
Filters: Autor is Torsten Hoefler  [Clear All Filters]
2021
M. Copik, Calotoiu, A., Grosser, T., Wicki, N., Wolf, F., und Hoefler, T., „Extracting Clean Performance Models from Tainted Programs“, in Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2021, S. 403-417.
D. Nikitenko, Wolf, F., Mohr, B., Hoefler, T., Stefanov, K., Voevodin, V. Vladimirov, Antonov, A. Sergeevich, und Calotoiu, A., „Influence of Noisy Environments on Behavior of HPC Applications“, Lobachevskii Journal of Mathematics, Bd. 42, S. 1560-1570, 2021.
M. Ritter, Geiß, A., Wehrstein, J., Calotoiu, A., Reimann, T., Hoefler, T., und Wolf, F., „Noise-Resilient Empirical Performance Modeling with Deep Neural Networks“, in Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2021, S. 23-34.
2020
A. Calotoiu, Geisenhofer, M., Kummer, F., Weber, J., Hoefler, T., Oberlack, M., und Wolf, F., „Empirical Modeling of Spatially Diverging Performance“, in Proceedings the 2020 IEEE/ACM International Workshop on HPC User Support Tools (HUST) and Workshop on Programming and Performance Visualization Tools (ProTools), 2020, S. 71-80.
A. Calotoiu, Copik, M., Hoefler, T., Ritter, M., Shudler, S., und Wolf, F., „ExtraPeak: Advanced Automatic Performance Modeling for HPC Applications“, Software for Exascale Computing - SPPEXA 2016-2019, LNCSE 136. Springer, S. 453-482, 2020.
M. Ritter, Calotoiu, A., Rinke, S., Reimann, T., Hoefler, T., und Wolf, F., „Learning Cost-Effective Sampling Strategies for Empirical Performance Modeling“, in Proceedings of the 34th IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020, S. 884-895.