Publications

Found 28 results
Filters: Autor is Felix Wolf  [Clear All Filters]
2022
H. Nöttgen, Czappa, F., und Wolf, F., „Accelerating Brain Simulations with the Fast Multipole Method“, in Proceedings of the 28th International Conference on Parallel and Distributed Computing (Euro-Par), 2022, S. 22-26.
S. Prasad, Ghafoor, S., Barnas, M., Wolf, F., Saule, E., und Sakellariou, N. Rodriguez, „Editorial of Special Issue: Keeping up with technology: Teaching parallel, distributed, and highperformance computing“, Journal of Parallel and Distributed Computing, Bd. 160. Elsevier, S. 36-38, 2022.
T. Özden, Beringer, T., Mazaheri, A., Fard, H. Mohammadi, und Wolf, F., „ElastiSim: A Batch-System Simulator for Malleable Workloads“, Proceedings of the 51st International Conference on Parallel Processing (ICPP). ACM (to appear, Link), 2022.
A. Horn, Fard, H. Mohammadi, und Wolf, F., „Multi-objective Hybrid Autoscaling of Microservices in Kubernetes Clusters“, in Proceedings of the 28th International Conference on Parallel and Distributed Computing (Euro-Par), 2022, S. 233-250.
2021
F. Wolf und Gao, W., „Benchmarking, Measuring, and Optimizing“, Proceedings of the 3rd BenchCouncil International Symposium (Bench). Springer, S. 1-268, 2021.
F. Czappa, Calotoiu, A., Höhl, T., Mantel, H., Nguyen, T., und Wolf, F., „Design-Time Performance Modeling of Compositional Parallel Programs“, Parallel Computing, Bd. 108, S. 1-12, 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.
R. Mammadli, Selakovic, M., Wolf, F., und Pradel, M., „Learning to Make Compiler Optimizations More Effective“, in Proceedings of the 5th ACM SIGPLAN International Symposium on Machine Programming (MAPS), 2021, S. 9-20.
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.
J. - P. Lehr, Bischof, C., Dewald, F., Mantel, H., Norouzi, M., und Wolf, F., „Tool-Supported Mini-App Extraction to Facilitate Program Analysis and Parallelization“, in Proceedings of the 50th International Conference on Parallel Processing (ICPP), 2021, S. 1-10.
2020
A. Mazaheri, Beringer, T., Moskewicz, M., Wolf, F., und Jannesari, A., „Accelerating winograd convolutions using symbolic computation and meta-programming“, in Proceedings of the 15th European Conference on Computer Systems (EuroSys), 2020, S. 1-14.
H. Mohammadi Fard, Prodan, R., und Wolf, F., „Dynamic Multi-objective Scheduling of Microservices in the Cloud“, in Proceedings of the 13th International Conference on Utility and Cloud Computing (UCC), 2020, S. 386-393.
F. Schrammel, Renk, F., Mazaheri, A., und Wolf, F., „Efficient Ephemeris Models for Spacecraft Trajectory Simulations on GPUs“, in Proceedings of the 26th European Conference on Parallel and Distributed Computing (Euro-Par), 2020, S. 561-577.
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.
R. Hähnle, Tabar, A. Heydari, Mazaheri, A., Norouzi, M., Steinhöfel, D., und Wolf, F., „Safer Parallelization“, in Proceedings of the 9th International Symposium on Leveraging Applications of Formal Methods (ISoLA), 2020, S. 117-137.
N. Morew, Norouzi, M., Jannesari, A., und Wolf, F., „Skipping Non-essential Instructions Makes Data-Dependence Profiling Faster“, in Proceedings of the 26th International Conference on Parallel and Distributed Computing (Euro-Par), 2020, S. 3-17.
R. Mammadli, Jannesari, A., und Wolf, F., „Static Neural Compiler Optimization via Deep Reinforcement Learning“, in Proceedings of the 6th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), 2020, S. 1-11.
2019
M. Norouzi, Ilias, Q., Jannesari, A., und Wolf, F., „Accelerating Data-Dependence Profiling with Static Hints“, in Proceedings of the 25th International Conference on Parallel and Distributed Computing (Euro-Par), 2019, S. 17-28.
M. Norouzi, Wolf, F., und Jannesari, A., „Automatic Construct Selection and Variable Classification in OpenMP“, in Proceedings of the 33rd International Conference on Supercomputing (ICS), 2019, S. 330-341.
J. - P. Lehr, Calotoiu, A., Bischof, C., und Wolf, F., „Automatic Instrumentation Refinement for Empirical Performance Modeling“, in Proceedings of the 2019 IEEE/ACM International Workshop on Programming and Performance Visualization Tools (ProTools), 2019, S. 40-47.
A. Calotoiu, Höhl, T., Mantel, H., Nguyen, T., und Wolf, F., „Designing Efficient Parallel Software via Compositional Performance Modeling“, in Proceedings of the Workshop on Programming and Performance Visualization Tools (ProTools), 2019, S. 17-24.
A. Mazaheri, Schulte, J., Moskewicz, M., Wolf, F., und Jannesari, A., „Enhancing the Programmability and Performance Portability of GPU Tensor Operations“, in Proceedings of the 25th European Conference on Parallel and Distributed Computing (Euro-Par), 2019, S. 213-226.
R. Mammadli, Wolf, F., und Jannesari, A., „The Art of Getting Deep Neural Networks in Shape“, ACM Transactions on Architecture and Code Optimization, Bd. 15, Nr. 4, S. 62:1-62:21, 2019.
2018
A. Shah, Müller, M. S., und Wolf, F., „Estimating the Impact of External Interference on Application Performance“, in Proceedings of the 24th European Conference on Parallel and Distributed Computing (Euro-Par), 2018, S. 46-58.
A. Mazaheri, Wolf, F., und Jannesari, A., „Unveiling Thread Communication Bottlenecks Using Hardware-Independent Metrics“, in Proceedings of the 47th International Conference on Parallel Processing (ICPP), 2018, S. 1-10.