Javier Prades

According to our database, Javier Prades authored at least 27 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

NGS: A network GPGPU system for orchestrating remote and virtual accelerators.

Javier Prades, Carlos Reaño, Federico Silla

J. Syst. Archit., 2024

2023

Using remote GPU virtualization techniques to enhance edge computing devices.

José M. Cecilia, Juan Morales-García, Baldomero Imbernón, Javier Prades, Juan-Carlos Cano, Federico Silla

Future Gener. Comput. Syst., May, 2023

On the Acceleration of FaaS Using Remote GPU Virtualization.

Diana M. Naranjo Delgado, Manuel Contreras, Germán Moltó, Sebastián Risco, Ignacio Blanquer, Javier Prades, Federico Silla

Proceedings of the Companion of the 2023 ACM/SPEC International Conference on Performance Engineering, 2023

BODOQUE: An Energy-Efficient Flow Monitoring System for Ephemeral Streams.

Benjamín Arratia, Javier Prades, Salvador Peña-Haro, José Maria Cecilia, Pietro Manzoni

Proceedings of the Twenty-fourth International Symposium on Theory, 2023

2021

Improving the management efficiency of GPU workloads in data centers through GPU virtualization.

Sergio Iserte, Javier Prades, Carlos Reaño, Federico Silla

Concurr. Comput. Pract. Exp., 2021

2020

Improving the performance of physics applications in atom-based clusters with rCUDA.

Federico Silla, Javier Prades, Elvira Baydal, Carlos Reaño

J. Parallel Distributed Comput., 2020

Maximizing resource usage in multifold molecular dynamics with rCUDA.

Javier Prades, Baldomero Imbernón, Carlos Reaño, Jorge Peña-García, José Pedro Cerón-Carrasco, Federico Silla, Horacio Pérez Sánchez

Int. J. High Perform. Comput. Appl., 2020

2019

GPU-Job Migration: The rCUDA Case.

Javier Prades, Federico Silla

IEEE Trans. Parallel Distributed Syst., 2019

Analyzing the performance/power tradeoff of the rCUDA middleware for future exascale systems.

Carlos Reaño, Javier Prades, Federico Silla

J. Parallel Distributed Comput., 2019

On the effect of using rCUDA to provide CUDA acceleration to Xen virtual machines.

Javier Prades, Carlos Reaño, Federico Silla

Clust. Comput., 2019

2018

Enhancing large-scale docking simulation on heterogeneous systems: An MPI vs rCUDA study.

Baldomero Imbernón, Javier Prades, Domingo Giménez, José M. Cecilia, Federico Silla

Future Gener. Comput. Syst., 2018

Leveraging rCUDA for Enhancing Low-Power Deployments in the Physics Domain.

Federico Silla, Javier Prades, Carlos Reaño

Proceedings of the 47th International Conference on Parallel Processing, 2018

Exploring the Use of Remote GPU Virtualization in Low-Power Systems for Bioinformatics Applications.

Carlos Reaño, Javier Prades, Federico Silla

Proceedings of the 47th International Conference on Parallel Processing, 2018

Made-to-Measure GPUs on Virtual Machines with rCUDA.

Javier Prades, Federico Silla

Proceedings of the 47th International Conference on Parallel Processing, 2018

Increasing Molecular Dynamics Simulations Throughput by Virtualizing Remote GPUs with rCUDA.

Javier Prades, Carlos Reaño, Federico Silla, Baldomero Imbernón, Horacio Pérez Sánchez, José M. Cecilia

Proceedings of the 47th International Conference on Parallel Processing, 2018

Improving the Efficiency of Future Exascale Systems with rCUDA.

Carlos Reaño, Javier Prades, Federico Silla

Proceedings of the 4th IEEE International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era, 2018

2017

Multi-tenant virtual GPUs for optimising performance of a financial risk application.

Javier Prades, Blesson Varghese, Carlos Reaño, Federico Silla

J. Parallel Distributed Comput., 2017

On the benefits of the remote GPU virtualization mechanism: The rCUDA case.

Federico Silla, Sergio Iserte, Carlos Reaño, Javier Prades

Concurr. Comput. Pract. Exp., 2017

Turning GPUs into Floating Devices over the Cluster: The Beauty of GPU Migration.

Javier Prades, Federico Silla

Proceedings of the 46th International Conference on Parallel Processing Workshops, 2017

A Live Demo for Showing the Benefits of Applying the Remote GPU Virtualization Technique to Cloud Computing.

Javier Prades, Federico Silla

Proceedings of the 17th IEEE/ACM International Symposium on Cluster, 2017

2016

CUDA acceleration for Xen virtual machines in infiniband clusters with rCUDA.

Javier Prades, Carlos Reaño, Federico Silla

Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2016

Remote GPU Virtualization: Is It Useful?

Federico Silla, Javier Prades, Sergio Iserte, Carlos Reaño

Proceedings of the 2nd IEEE International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era HiPINEB@HPCA 2016, 2016

Increasing the Performance of Data Centers by Combining Remote GPU Virtualization with Slurm.

Sergio Iserte, Javier Prades, Carlos Reaño, Federico Silla

Proceedings of the IEEE/ACM 16th International Symposium on Cluster, 2016

2015

On the design of a new dynamic credit-based end-to-end flow control mechanism for HPC clusters.

Javier Prades, Federico Silla, Holger Fröning, Mondrian Nüssle, José Duato

Parallel Comput., 2015

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application.

Blesson Varghese, Javier Prades, Carlos Reaño, Federico Silla

Proceedings of the 11th IEEE International Conference on e-Science, 2015

2014

SLURM Support for Remote GPU Virtualization: Implementation and Performance Study.

Sergio Iserte, Adrián Castelló, Rafael Mayo, Enrique S. Quintana-Ortí, Federico Silla, José Duato, Carlos Reaño, Javier Prades

Proceedings of the 26th IEEE International Symposium on Computer Architecture and High Performance Computing, 2014

2012

A New End-to-End Flow-Control Mechanism for High Performance Computing Clusters.

Javier Prades, Federico Silla, José Duato, Holger Fröning, Mondrian Nüssle

Proceedings of the 2012 IEEE International Conference on Cluster Computing, 2012