| 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 | 577 | 2019 |
| MPI: A Message-Passing Interface Standard MPI Forum Technical Report, 2012 | 427* | 2012 |
| The convergence of sparsified gradient methods D Alistarh, T Hoefler, M Johansson, N Konstantinov, S Khirirat, C Renggli Advances in Neural Information Processing Systems 31, 2018 | 368 | 2018 |
| Characterizing the influence of system noise on large-scale applications by simulation T Hoefler, T Schneider, A Lumsdaine SC'10: Proceedings of the 2010 ACM/IEEE International Conference for High …, 2010 | 302 | 2010 |
| Slim fly: A cost effective low-diameter network topology M Besta, T Hoefler SC'14: proceedings of the international conference for high performance …, 2014 | 291 | 2014 |
| Generic topology mapping strategies for large-scale parallel architectures T Hoefler, M Snir Proceedings of the international conference on Supercomputing, 75-84, 2011 | 284 | 2011 |
| The PERCS high-performance interconnect B Arimilli, R Arimilli, V Chung, S Clark, W Denzel, B Drerup, T Hoefler, ... 2010 18th IEEE Symposium on High Performance Interconnects, 75-82, 2010 | 284 | 2010 |
| Implementation and performance analysis of non-blocking collective operations for MPI T Hoefler, A Lumsdaine, W Rehm Proceedings of the 2007 ACM/IEEE conference on Supercomputing, 1-10, 2007 | 264 | 2007 |
| Scientific benchmarking of parallel computing systems: twelve ways to tell the masses when reporting performance results T Hoefler, R Belli Proceedings of the international conference for high performance computing …, 2015 | 247 | 2015 |
| 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 The Journal of Machine Learning Research 22 (1), 10882-11005, 2021 | 216 | 2021 |
| LogGOPSim: simulating large-scale applications in the LogGOPS model T Hoefler, T Schneider, A Lumsdaine Proceedings of the 19th ACM International Symposium on High Performance …, 2010 | 213 | 2010 |
| Neural code comprehension: A learnable representation of code semantics T Ben-Nun, AS Jakobovits, T Hoefler Advances in Neural Information Processing Systems 31, 2018 | 180 | 2018 |
| Using automated performance modeling to find scalability bugs in complex codes A Calotoiu, T Hoefler, M Poke, F Wolf Proceedings of the International Conference on High Performance Computing …, 2013 | 162 | 2013 |
| Using advanced MPI: Modern features of the message-passing interface W Gropp, T Hoefler, R Thakur, E Lusk MIT Press, 2014 | 160 | 2014 |
| Dare: High-performance state machine replication on rdma networks M Poke, T Hoefler Proceedings of the 24th International Symposium on High-Performance Parallel …, 2015 | 157 | 2015 |
| Multistage switches are not crossbars: Effects of static routing in high-performance networks T Hoefler, T Schneider, A Lumsdaine 2008 IEEE International Conference on Cluster Computing, 116-125, 2008 | 155 | 2008 |
| Enabling highly-scalable remote memory access programming with MPI-3 one sided R Gerstenberger, M Besta, T Hoefler Proceedings of the International Conference on High Performance Computing …, 2013 | 151 | 2013 |
| Message progression in parallel computing-to thread or not to thread? T Hoefler, A Lumsdaine 2008 IEEE International Conference on Cluster Computing, 213-222, 2008 | 143 | 2008 |
| To push or to pull: On reducing communication and synchronization in graph computations M Besta, M Podstawski, L Groner, E Solomonik, T Hoefler Proceedings of the 26th International Symposium on High-Performance Parallel …, 2017 | 138 | 2017 |
| MPI+ MPI: a new hybrid approach to parallel programming with MPI plus shared memory T Hoefler, J Dinan, D Buntinas, P Balaji, B Barrett, R Brightwell, W Gropp, ... Computing 95, 1121-1136, 2013 | 129 | 2013 |
Andrew LumsdaineUniversity of Washington; Pacific Northwest National LaboratoryVerified email at uw.edu
