Demystifying parallel and distributed deep learning: An in-depth concurrency analysis T Ben-Nun, T Hoefler ACM Computing Surveys (CSUR) 52 (4), 1-43, 2019 | 870 | 2019 |
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks T Hoefler, D Alistarh, T Ben-Nun, N Dryden, A Peste Journal of Machine Learning Research 22 (241), 1-124, 2021 | 810 | 2021 |
Augment your batch: Improving generalization through instance repetition E Hoffer, T Ben-Nun, I Hubara, N Giladi, T Hoefler, D Soudry Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 327* | 2020 |
Neural Code Comprehension: A Learnable Representation of Code Semantics T Ben-Nun, AS Jakobovits, T Hoefler Advances in Neural Information Processing Systems 31, 2018 | 308 | 2018 |
ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations C Cummins, ZV Fisches, T Ben-Nun, T Hoefler, MFP O’Boyle, H Leather International Conference on Machine Learning, 2244-2253, 2021 | 195* | 2021 |
Deep learning for post-processing ensemble weather forecasts P Grönquist, C Yao, T Ben-Nun, N Dryden, P Dueben, S Li, T Hoefler Philosophical Transactions of the Royal Society A 379 (2194), 1-18, 2021 | 185 | 2021 |
Groute: An asynchronous multi-GPU programming model for irregular computations T Ben-Nun, M Sutton, S Pai, K Pingali ACM SIGPLAN Notices 52 (8), 235-248, 2017 | 168 | 2017 |
Data Movement Is All You Need: A Case Study on Optimizing Transformers A Ivanov, N Dryden, T Ben-Nun, S Li, T Hoefler Fourth Conference on Machine Learning and Systems (MLSys), 2021 | 150 | 2021 |
A package for OpenCL based heterogeneous computing on clusters with many GPU devices A Barak, T Ben-Nun, E Levy, A Shiloh 2010 IEEE international conference on cluster computing workshops and …, 2010 | 148 | 2010 |
Stateful dataflow multigraphs: A data-centric model for performance portability on heterogeneous architectures T Ben-Nun, J de Fine Licht, AN Ziogas, T Schneider, T Hoefler Proceedings of the International Conference for High Performance Computing …, 2019 | 143 | 2019 |
A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning T Ben-Nun, M Besta, S Huber, AN Ziogas, D Peter, T Hoefler The 33rd IEEE International Parallel & Distributed Processing Symposium …, 2019 | 90 | 2019 |
X+: a comprehensive computationally accelerated structure analysis tool for solution X-ray scattering from supramolecular self-assemblies T Ben-Nun, A Ginsburg, P Székely, U Raviv Journal of Applied Crystallography 43 (6), 1522-1531, 2010 | 77 | 2010 |
Memory access patterns: The missing piece of the multi-GPU puzzle T Ben-Nun, E Levy, A Barak, E Rubin Proceedings of the International Conference for High Performance Computing …, 2015 | 76 | 2015 |
Solution X-ray scattering form factors of supramolecular self-assembled structures P Székely, A Ginsburg, T Ben-Nun, U Raviv Langmuir 26 (16), 13110-13129, 2010 | 74 | 2010 |
Graph processing on FPGAs: Taxonomy, survey, challenges M Besta, D Stanojevic, JDF Licht, T Ben-Nun, T Hoefler arXiv preprint arXiv:1903.06697, 2019 | 70 | 2019 |
Clairvoyant prefetching for distributed machine learning I/O N Dryden, R Böhringer, T Ben-Nun, T Hoefler Proceedings of the International Conference for High Performance Computing …, 2021 | 67 | 2021 |
Taming unbalanced training workloads in deep learning with partial collective operations S Li, T Ben-Nun, SD Girolamo, D Alistarh, T Hoefler Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of …, 2020 | 65 | 2020 |
Optimizing Parallel Graph Connectivity Computation via Subgraph Sampling M Sutton, T Ben-Nun, A Barak IEEE International Parallel and Distributed Processing Symposium, 2018 | 63 | 2018 |
A data-centric approach to extreme-scale ab initio dissipative quantum transport simulations AN Ziogas, T Ben-Nun, GI Fernández, T Schneider, M Luisier, T Hoefler Proceedings of the International Conference for High Performance Computing …, 2019 | 60 | 2019 |
Workflows are the New Applications: Challenges in Performance, Portability, and Productivity T Ben-Nun, T Gamblin, DS Hollman, H Krishnan, CJ Newburn IEEE/ACM International Workshop on Performance, Portability and Productivity …, 2020 | 44 | 2020 |