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Carlos Reaño
Carlos Reaño
Assistant Professor in Computer Architecture at Universitat de València, Spain
Dirección de correo verificada de uv.es - Página principal
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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
1342014
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
712015
A performance comparison of CUDA remote GPU virtualization frameworks
C Reaño, F Silla
2015 IEEE International Conference on Cluster Computing, 488-489, 2015
602015
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
502012
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
492013
Remote GPU Virtualization: Is It Useful?
F Silla, J Prades, S Iserte, C Reaño
2016 2nd IEEE International Workshop on High-Performance Interconnection …, 2016
422016
SLURM support for remote GPU virtualization: Implementation and performance study
S Iserte, A Castelló, R Mayo, ES Quintana-Ortí, F Silla, J Duato, C Reaño, ...
2014 IEEE 26th International Symposium on Computer Architecture and High …, 2014
342014
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
322018
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
302017
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
302016
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
242015
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
202017
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
172016
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
172015
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
152017
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
132016
A comparative performance analysis of remote GPU virtualization over three generations of GPUs
C Reano, F Silla
2017 46th International Conference on Parallel Processing Workshops (ICPPW …, 2017
112017
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
102021
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
102017
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
102016
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