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Alexandru Calotoiu, Marcin Copik, Fabian Czappa, Alexander Geiß, Gustavo Morais, Marcus Ritter, Sergei Shudler, Torsten Hoefler, Felix Wolf: Extra-P – Empirical Performance Modeling Made Easy. Frontiers in High Performance Computing, 3–2025, 2026.
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Branden Butler, Sixing Yu, Arya Mazaheri, Ali Jannesari: PipeInfer: Accelerating LLM Inference using Asynchronous Pipelined Speculation. In Proc. of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), Atlanta, GA, USA, pages 1–19, IEEE, November 2024.
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Gregor Corbin, Nour Daoud, Bernd Mohr, Gustavo de Morais, Felix Wolf: Are Noise-Resilient Logical Timers useful for Performance Analysis?. In Proc. of the Workshop on Programming and Performance Visualization Tools (ProTools), held in conjunction with the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24), Atlanta, GA, USA, pages 1519-1530, IEEE, November 2024.
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Lukas Rothenberger, Gustavo de Morais, Alexander Geiß, Felix Wolf: Practical empirical performance modeling for CFD applications using Extra-P. In Proc. of the 35th International Conference on Parallel Computational Fluid Dynamics (ParCFD2024), Bonn, Germany, pages 176–179, Forschungszentrum Jülich GmbH Zentralbibliothek, September 2024.
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Tim Beringer, Jakob Stock, Arya Mazaheri, Felix Wolf: Dissecting Convolutional Neural Networks for Runtime and Scalability Prediction. In Proc. of the 53st International Conference on Parallel Processing (ICPP), Gotland, Sweden, pages 168–178, ACM, August 2024.
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Seyed Ali Mohammadi, Lukas Rothenberger, Gustavo de Morais, Bertin Nico Görlich, Erik Lille, Hendrik Rüthers, Felix Wolf: Filtering and Ranking of Code Regions for Parallelization via Hotspot Detection and OpenMP Overhead Analysis. In Proc. of the Workshop on Programming and Performance Visualization Tools (ProTools), held in conjunction with the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC23), Denver, CO, USA, pages 1368–1379, November 2023.
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Sixing Yu, Arya Mazaheri, Ali Jannesari: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning. In Proc. of the 39th International Conference on Machine Learning (ICML), Baltimore, Maryland, USA, volume 162 of Proceedings of Machine Learning Research, pages 25656–25667, PMLR, July 2022.
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Rahim Mammadli, Ali Jannesari, Felix Wolf: Static Neural Compiler Optimization via Deep Reinforcement Learning. In Proc. of the 6th Workshop on the LLVM Compiler Infrastructure in HPC, held in conjunction with the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC20), pages 1–11, IEEE, November 2020.
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Arya Mazaheri, Tim Beringer, Matthew Moskewicz, Felix Wolf, Ali Jannesari: Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming. In Proc. of the 15th EuroSys Conference, Heraklion, Crete, Greece, pages 1–14, ACM, April 2020.
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Arya Mazaheri, Johannes Schulte, Matthew Moskewicz, Felix Wolf, Ali Jannesari: Enhancing the Programmability and Performance Portability of GPU Tensor Operations. In Proc. of the 25th Euro-Par Conference, Göttingen, Germany, volume 11725 of Lecture Notes in Computer Science, pages 213–226, Springer, August 2019.
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Rahim Mammadli, Felix Wolf, Ali Jannesari: The Art of Getting Deep Neural Networks in Shape. ACM Transactions on Architecture and Code Optimization (TACO), 15(4): 62:1–62:21, January 2019.
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