| High-performance computing using FPGAs W Vanderbauwhede, K Benkrid Springer 3, 33-38, 2013 | 164 | 2013 |
| Resource-efficient neural networks for embedded systems W Roth, G Schindler, B Klein, R Peharz, S Tschiatschek, H Fröning, ... arXiv preprint arXiv:2001.03048, 2020 | 60* | 2020 |
| GGAS: Global GPU address spaces for efficient communication in heterogeneous clusters L Oden, H Fröning 2013 IEEE International Conference on Cluster Computing (CLUSTER), 1-8, 2013 | 57 | 2013 |
| An overview of MPI characteristics of exascale proxy applications B Klenk, H Fröning High Performance Computing: 32nd International Conference, ISC High …, 2017 | 55 | 2017 |
| The HTX-board: a rapid prototyping station H Fröning, M Nüssle, D Slogsnat, H Litz, U Brüning 3rd annual FPGAworld Conference, 2006 | 48 | 2006 |
| VELO: A novel communication engine for ultra-low latency message transfers H Litz, H Froening, M Nuessle, U Bruening 2008 37th International Conference on Parallel Processing, 238-245, 2008 | 45 | 2008 |
| InfiniBand Verbs on GPU: a case study of controlling an InfiniBand network device from the GPU L Oden, H Fröning The International Journal of High Performance Computing Applications 31 (4 …, 2017 | 44 | 2017 |
| Efficient hardware support for the partitioned global address space H Fröning, H Litz 2010 IEEE International Symposium on Parallel & Distributed Processing …, 2010 | 41 | 2010 |
| A simple model for portable and fast prediction of execution time and power consumption of GPU kernels L Braun, S Nikas, C Song, V Heuveline, H Fröning ACM Transactions on Architecture and Code Optimization (TACO) 18 (1), 1-25, 2020 | 40 | 2020 |
| Optimizing the data-collection time of a large-scale data-acquisition system through a simulation framework T Colombo, H Fröning, PJ Garcìa, W Vandelli The Journal of Supercomputing 72, 4546-4572, 2016 | 40 | 2016 |
| On achieving high message rates H Fröning, M Nüssle, H Litz, C Leber, U Brüning 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid …, 2013 | 35 | 2013 |
| Cuda flux: A lightweight instruction profiler for cuda applications L Braun, H Fröning 2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High …, 2019 | 29 | 2019 |
| Energy-efficient collective reduce and allreduce operations on distributed GPUs L Oden, B Klenk, H Fröning 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2014 | 29 | 2014 |
| An FPGA-based custom high performance interconnection network M Nüssle, B Geib, H Fröning, U Brüning 2009 International Conference on Reconfigurable Computing and FPGAs, 113-118, 2009 | 29 | 2009 |
| Relaxations for high-performance message passing on massively parallel SIMT processors B Klenk, H Fröening, H Eberle, L Dennison 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2017 | 28 | 2017 |
| Exploring time and energy for complex accesses to a hybrid memory cube J Schmidt, H Fröning, U Brüning Proceedings of the Second International Symposium on Memory Systems, 142-150, 2016 | 22 | 2016 |
| cCUDA: Effective co-scheduling of concurrent kernels on GPUs SK Shekofteh, H Noori, M Naghibzadeh, H Fröning, HS Yazdi IEEE Transactions on Parallel and Distributed Systems 31 (4), 766-778, 2019 | 20 | 2019 |
| Training discrete-valued neural networks with sign activations using weight distributions W Roth, G Schindler, H Fröning, F Pernkopf Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 19 | 2020 |
| Early experiences with saving energy in direct interconnection networks F Zahn, S Lammel, H Fröning 2017 IEEE 3rd International Workshop on High-Performance Interconnection …, 2017 | 18 | 2017 |
| Analyzing the energy (dis-) proportionality of scalable interconnection networks F Zahn, P Yebenes, S Lammel, PJ Garcia, H Fröning 2016 2nd IEEE International Workshop on High-Performance Interconnection …, 2016 | 18 | 2016 |
Heiner LitzUniversity of California Santa CruzVerified email at ucsc.edu
