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Listar por autor "Prades Gasulla, Javier"

Mostrando ítems 1-19 de 19

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

Reaño González, Carlos; Prades, Javier; Silla Jiménez, Federico (Elsevier, 2019-10)

[EN] The computing power of supercomputers and data centers has noticeably grown during the last decades at the cost of an ever increasing energy demand. The need for energy (and power) of these facilities has finally ...
Análisis de las prestaciones del entorno de deep learning TensorFlow

Rodríguez Alepuz, Sergio (Universitat Politècnica de València, 2018-09-11)

[ES] Los sistemas de aprendizaje automático —y, en concreto, los modelos de aprendizaje profundo (del inglés, deep learning) o redes neuronales— se han popularizado recientemente debido a que han supuesto un salto ...
BODOQUE: An Energy-Efficient Flow Monitoring System for Ephemeral Streams

Arratia-Uribe, Benjamín Andrés; Prades, Javier; Peña-Haro, Salvador; Cecilia-Canales, José María; Manzoni, Pietro (Association for Computing Machinery (ACM), 2023-10-26)

[EN] Effective environmental monitoring is crucial for managing global environmental challenges and providing the necessary data for Environmental Intelligence (EI). This discipline involves the integration of data from ...
Enhancing large-scale docking simulation on heterogeneous systems: An MPI vs rCUDA study

Imbernón, Baldomero; Prades Gasulla, Javier; Gimenez Canovas, Domingo; Cecilia, J. M.; Silla Jiménez, Federico (Elsevier, 2018-02)

[EN] Virtual Screening (VS) methods can considerably aid clinical research by predicting how ligands interact with pharmacological targets, thus accelerating the slow and critical process of finding new drugs. VS methods ...
Estudio analítico de las prestaciones de una aplicación paralela distribuida

Díaz Román, Antonio (Universitat Politècnica de València, 2016-10-06)

[ES] La ejecución de aplicaciones con altas cargas computacionales adquiere una creciente demanda hoy en día, por lo que se manifiesta la necesidad de contar con una infraestructura adecuada y una correcta gestión de la ...
Experimentación con el entorno de deep learning TensorFlow

Boix Ramos, Jordi (Universitat Politècnica de València, 2018-05-03)

[ES] El Deep Learning (o aprendizaje profundo) es un término que está tomando mucha fuerza en muchas de las ramas de la ciencia a día de hoy. La facilidad de generar modelos de Inteligencia Artificial con entornos de ...
GPU-Job Migration: The rCUDA Case

Prades, Javier; Silla Jiménez, Federico (Institute of Electrical and Electronics Engineers, 2019-12)

[EN] Virtualization techniques have been shown to report benefits to data centers and other computing facilities. In this regard, not only virtual machines allow to reduce the size of the computing infrastructure while ...
Improving Performance and Energy Efficiency of Heterogeneous Systems with rCUDA

Prades Gasulla, Javier (Universitat Politècnica de València, 2021-06-14)

[ES] En la última década la utilización de la GPGPU (General Purpose computing in Graphics Processing Units; Computación de Propósito General en Unidades de Procesamiento Gráfico) se ha vuelto tremendamente popular en los ...
Improving the management efficiency of GPU workloads in data centers through GPU virtualization

Iserte, Sergio; Prades, Javier; Reaño González, Carlos; Silla, Federico (John Wiley & Sons, 2021-01-25)

[EN] Graphics processing units (GPUs) are currently used in data centers to reduce the execution time of compute-intensive applications. However, the use of GPUs presents several side effects, such as increased acquisition ...
Improving the performance of physics applications in atom-based clusters with rCUDA

Silla, Federico; Prades, Javier; Baydal Cardona, María Elvira; Reaño, Carlos (Elsevier, 2020-03)

[EN] Traditionally, High-Performance Computing (HPC) has been associated with large power requirements. The reason was that chip makers of the processors typically employed in HPC deployments have always focused on getting ...
Iniciación al entorno de deep learning Torch

Martínez Marhuenda, Javier (Universitat Politècnica de València, 2018-10-05)

[ES] El Deep Learning es una tecnología puntera actual que va a tener gran presencia en el futuro. Sin embargo, dominarlo es una tarea compleja y laboriosa que no todo el mundo está dispuesto a emprender. En este trabajo ...
Instalación, configuración y evaluación de la red de interconexión EXTOLL en un entorno de memoria distribuida

Prades Gasulla, Javier (Universitat Politècnica de València, 2014-09-15)

EXTOLL es una nueva arquitectura de red de interconexión, desarrollada por la Universidad de Heidelberg, que pretende establecerse en el sector del HPCC como una alternativa altamente eficiente y económica. EXTOLL proporciona ...
Maximizing resource usage in multifold molecular dynamics with rCUDA

Prades, Javier; Imbernon, Baldomero; Reaño González, Carlos; Peña-García, Jorge; Cerón-Carrasco, Jose Pedro; Silla Jiménez, Federico; Pérez-Sánchez, Horacio (SAGE Publications, 2020-01)

[EN] The full-understanding of the dynamics of molecular systems at the atomic scale is of great relevance in the fields of chemistry, physics, materials science, and drug discovery just to name a few. Molecular dynamics ...
Multi-tenant virtual GPUs for optimising performance of a financial risk application

Prades Gasulla, Javier; Varghese, Blesson; Reaño González, Carlos; Silla Jiménez, Federico (Elsevier, 2017)

[EN] Graphics Processing Units (GPUs) are becoming popular accelerators in modern High-Performance Computing (HPC) clusters. Installing GPUs on each node of the cluster is not efficient resulting in high costs and power ...
On the Benefits of the Remote GPU Virtualization Mechanism: the rCUDA Case

Silla Jiménez, Federico; Iserte Agut, Sergio; Reaño González, Carlos; Prades, Javier (John Wiley & Sons, 2017-07-10)

[EN] Graphics processing units (GPUs) are being adopted in many computing facilities given their extraordinary computing power, which makes it possible to accelerate many general purpose applications from different domains. ...
On the design of a new dynamic credit-based end-to-end flow control mechanism for HPC clusters

Prades Gasulla, Javier; Silla Jiménez, Federico; Fröning, Holger; Nuessle, Mondrian; Duato Marín, José Francisco (Elsevier, 2015-07)

High Performance Computing usually leverages messaging libraries such as MPI, GASNet, or OpenSHMEM, among others, in order to exchange data among processes in large-scale clusters. Furthermore, these libraries make use ...
On the Effect of using rCUDA to Provide CUDA Acceleration to Xen Virtual Machines

Prades, Javier; Reaño González, Carlos; Silla Jiménez, Federico (Springer-Verlag, 2019-03)

[EN] Nowadays, many data centers use virtual machines (VMs) in order to achieve a more efficient use of hardware resources. The use of VMs provides a reduction in equipment and maintenance expenses as well as a lower ...
SLURM Support for Remote GPU Virtualization: Implementation and Performance Study

Iserte Agut, Sergio; Castello Gimeno, Adrián; Mayo Gual, Rafael; Quintana Ortí, Enrique Salvador; Silla Jiménez, Federico; Duato Marín, José Francisco; Reaño González, Carlos; Prades Gasulla, Javier (IEEE, 2014-10-22)

SLURM is a resource manager that can be leveraged to share a collection of heterogeneous resources among the jobs in execution in a cluster. However, SLURM is not designed to handle resources such as graphics processing ...
Un nuevo protocolo de control de flujo de extremo a extremo basado en crréditos para redes de altas prestaciones

Prades Gasulla, Javier (Universitat Politècnica de València, 2015-07-28)

[EN] High Performance Computing usually leverages messaging libraries such as MPI, GASNet, or OpenSHMEM, among others, in order to exchange data among processes in large-scale clusters. Furthermore, these libraries make ...