A complete and efficient CUDA-sharing solution for HPC clusters AJ Pena, C Reaño, F Silla, R Mayo, ES Quintana-Ortí, J Duato Parallel Computing 40 (10), 574-588, 2014 | 135 | 2014 |
Local and remote GPUs perform similar with EDR 100G InfiniBand C Reaño, F Silla, G Shainer, S Schultz Proceedings of the Industrial Track of the 16th International Middleware …, 2015 | 74 | 2015 |
A performance comparison of CUDA remote GPU virtualization frameworks C Reaño, F Silla 2015 IEEE International Conference on Cluster Computing, 488-489, 2015 | 62 | 2015 |
CU2rCU: Towards the complete rCUDA remote GPU virtualization and sharing solution C Reaño, AJ Peña, F Silla, J Duato, R Mayo, ES Quintana-Ortí 2012 19th International Conference on High Performance Computing, 1-10, 2012 | 52 | 2012 |
Influence of InfiniBand FDR on the performance of remote GPU virtualization C Reaño, R Mayo, ES Quintana-Ortí, F Silla, J Duato, AJ Peña 2013 IEEE International Conference on Cluster Computing (CLUSTER), 1-8, 2013 | 48 | 2013 |
Remote GPU Virtualization: Is It Useful? F Silla, J Prades, S Iserte, C Reaño 2016 2nd IEEE International Workshop on High-Performance Interconnection …, 2016 | 43 | 2016 |
SLURM support for remote GPU virtualization: Implementation and performance study S Iserte, A Castelló, R Mayo, ES Quintana-Ortí, F Silla, J Duato, C Reano, ... 2014 IEEE 26th International Symposium on Computer Architecture and High …, 2014 | 34 | 2014 |
Accelerator virtualization in fog computing: Moving from the cloud to the edge B Varghese, C Reano, F Silla IEEE Cloud Computing 5 (6), 28-37, 2018 | 33 | 2018 |
On the benefits of the remote GPU virtualization mechanism: The rCUDA case F Silla, S Iserte, C Reaño, J Prades Concurrency and Computation: Practice and Experience 29 (13), e4072, 2017 | 31 | 2017 |
Increasing the performance of data centers by combining remote GPU virtualization with Slurm S Iserte, J Prades, C Reaño, F Silla 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2016 | 30 | 2016 |
Improving the user experience of the rCUDA remote GPU virtualization framework C Reano, F Silla, A Castelló, AJ Pena, R Mayo, ES Quintana‐Ortí, J Duato Concurrency and Computation: Practice and Experience 27 (14), 3746-3770, 2015 | 24 | 2015 |
Intra-node memory safe gpu co-scheduling C Reano, F Silla, DS Nikolopoulos, B Varghese IEEE Transactions on Parallel and Distributed Systems 29 (5), 1089-1102, 2017 | 21 | 2017 |
Acceleration-as-a-service: Exploiting virtualised GPUs for a financial application B Varghese, J Prades, C Reano, F Silla 2015 IEEE 11th International Conference on e-Science, 47-56, 2015 | 18 | 2015 |
Reducing the performance gap of remote GPU virtualization with InfiniBand Connect-IB C Reaño, F Silla 2016 IEEE symposium on computers and communication (ISCC), 920-925, 2016 | 17 | 2016 |
Enhancing the rCUDA remote GPU virtualization framework: From a prototype to a production solution C Reaño, F Silla, J Duato 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2017 | 15 | 2017 |
Providing CUDA acceleration to KVM virtual machines in InfiniBand clusters with rCUDA F Pérez, C Reaño, F Silla Distributed Applications and Interoperable Systems: 16th IFIP WG 6.1 …, 2016 | 13 | 2016 |
Improving the management efficiency of GPU workloads in data centers through GPU virtualization S Iserte, J Prades, C Reaño, F Silla Concurrency and Computation: Practice and Experience 33 (2), e5275, 2021 | 12 | 2021 |
Multi-tenant virtual GPUs for optimising performance of a financial risk application J Prades, B Varghese, C Reano, F Silla Journal of Parallel and Distributed Computing 108, 28-44, 2017 | 11 | 2017 |
A comparative performance analysis of remote GPU virtualization over three generations of GPUs C Reaño, F Silla 2017 46th International Conference on Parallel Processing Workshops (ICPPW …, 2017 | 11 | 2017 |
Performance evaluation of the NVIDIA pascal GPU architecture: Early experiences C Reaño, F Silla 2016 IEEE 18th International Conference on High Performance Computing and …, 2016 | 10 | 2016 |