Predicting the energy-consumption of mpi applications at scale using only a single node FC Heinrich, T Cornebize, A Degomme, A Legrand, A Carpen-Amarie, ... 2017 IEEE international conference on cluster computing (CLUSTER), 92-102, 2017 | 55 | 2017 |
Reproducible MPI benchmarking is still not as easy as you think S Hunold, A Carpen-Amarie IEEE Transactions on Parallel and Distributed Systems 27 (12), 3617-3630, 2016 | 47 | 2016 |
Scheduling independent moldable tasks on multi-cores with GPUs R Bleuse, S Hunold, S Kedad-Sidhoum, F Monna, G Mounié, D Trystram IEEE Transactions on Parallel and Distributed Systems 28 (9), 2689-2702, 2017 | 39 | 2017 |
Implementing a classic: Zero-copy all-to-all communication with MPI datatypes JL Träff, A Rougier, S Hunold Proceedings of the 28th ACM international conference on Supercomputing, 135-144, 2014 | 37 | 2014 |
Daggen: A synthetic task graph generator F Suter, S Hunold Github, 2013 | 29 | 2013 |
Multilevel hierarchical matrix multiplication on clusters S Hunold, T Rauber, G Rünger Proceedings of the 18th annual international conference on Supercomputing …, 2004 | 26 | 2004 |
Decomposing MPI collectives for exploiting multi-lane communication JL Träff, S Hunold 2020 IEEE International Conference on Cluster Computing (CLUSTER), 270-280, 2020 | 25 | 2020 |
Jedule: A tool for visualizing schedules of parallel applications S Hunold, R Hoffmann, F Suter 2010 39th International Conference on Parallel Processing Workshops, 169-178, 2010 | 25 | 2010 |
On the state and importance of reproducible experimental research in parallel computing S Hunold, JL Träff arXiv preprint arXiv:1308.3648, 2013 | 24 | 2013 |
Transformation of legacy software into client/server applications through pattern-based rearchitecturing S Hunold, M Korch, B Krellner, T Rauber, T Reichel, G Rünger 2008 32nd Annual IEEE International Computer Software and Applications …, 2008 | 24 | 2008 |
Autotuning MPI collectives using performance guidelines S Hunold, A Carpen-Amarie Proceedings of the International Conference on High Performance Computing in …, 2018 | 22 | 2018 |
One step toward bridging the gap between theory and practice in moldable task scheduling with precedence constraints S Hunold Concurrency and Computation: Practice and Experience 27 (4), 1010-1026, 2015 | 22 | 2015 |
Automatic tuning of PDGEMM towards optimal performance S Hunold, T Rauber Euro-Par 2005 Parallel Processing: 11th International Euro-Par Conference …, 2005 | 22 | 2005 |
Isomorphic, sparse MPI-like collective communication operations for parallel stencil computations JL Träff, FD Lübbe, A Rougier, S Hunold Proceedings of the 22nd European MPI Users' Group Meeting, 1-10, 2015 | 21 | 2015 |
Reproducible MPI micro-benchmarking isn't as easy as you think S Hunold, A Carpen-Amarie, JL Träff Proceedings of the 21st European MPI Users' Group Meeting, 69-76, 2014 | 21 | 2014 |
Redistribution aware two-step scheduling for mixed-parallel applications S Hunold, T Rauber, F Suter 2008 IEEE International Conference on Cluster Computing, 50-58, 2008 | 21 | 2008 |
Combining building blocks for parallel multi-level matrix multiplication S Hunold, T Rauber, G Rünger Parallel Computing 34 (6-8), 411-426, 2008 | 21 | 2008 |
Predicting MPI collective communication performance using machine learning S Hunold, A Bhatele, G Bosilca, P Knees 2020 IEEE International Conference on Cluster Computing (CLUSTER), 259-269, 2020 | 20 | 2020 |
Scheduling dynamic workflows onto clusters of clusters using postponing S Hunold, T Rauber, F Suter 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid …, 2008 | 20 | 2008 |
On the expected and observed communication performance with MPI derived datatypes A Carpen-Amarie, S Hunold, JL Träff Proceedings of the 23rd European MPI Users' Group Meeting, 108-120, 2016 | 19 | 2016 |