Carlos Reaño
Carlos Reaño
Lecturer (Queen's University Belfast, UK)
Verified email at gap.upv.es - Homepage
Title
Cited by
Cited by
Year
A complete and efficient CUDA-sharing solution for HPC clusters
AJ Peña, C Reaño, F Silla, R Mayo, ES Quintana-Ortí, J Duato
Parallel Computing 40 (10), 574-588, 2014
1072014
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
422015
A performance comparison of CUDA remote GPU virtualization frameworks
C Reaño, F Silla
2015 IEEE International Conference on Cluster Computing, 488-489, 2015
412015
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
392013
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
372012
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
282014
Remote GPU Virtualization: Is It Useful?
F Silla, J Prades, S Iserte, C Reaño
2016 2nd IEEE International Workshop on High-Performance Interconnection …, 2016
252016
Improving the user experience of the rCUDA remote GPU virtualization framework
C Reaño, F Silla, A Castelló, AJ Peña, R Mayo, ES Quintana‐Ortí, J Duato
Concurrency and Computation: Practice and Experience 27 (14), 3746-3770, 2015
192015
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
182016
On the benefits of the remote GPU virtualization mechanism: The rCUDA case
F Silla, S Iserte, C Reano, J Prades
Concurrency and Computation: Practice and Experience 29 (13), e4072, 2017
142017
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
142016
Acceleration-as-a-service: Exploiting virtualised GPUs for a financial application
B Varghese, J Prades, C Reaño, F Silla
2015 IEEE 11th International Conference on e-Science, 47-56, 2015
132015
Providing CUDA acceleration to KVM virtual machines in infiniband clusters with rCUDA
F Pérez, C Reaño, F Silla
IFIP International Conference on Distributed Applications and Interoperable …, 2016
102016
CUDA acceleration for Xen virtual machines in infiniband clusters with rCUDA
J Prades, C Reaño, F Silla
Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of …, 2016
102016
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
72017
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
72017
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
62018
Multi-tenant virtual GPUs for optimising performance of a financial risk application
J Prades, B Varghese, C Reaño, F Silla
Journal of Parallel and Distributed Computing 108, 28-44, 2017
62017
Tuning remote GPU virtualization for InfiniBand networks
C Reaño, F Silla
The Journal of Supercomputing 72 (12), 4520-4545, 2016
62016
Extending rCUDA with support for P2P memory copies between remote GPUs
C Reaño, F Silla
2016 IEEE 18th International Conference on High Performance Computing and …, 2016
52016
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Articles 1–20