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Listar por autor "Dolz Zaragozá, Manuel Francisco"

Mostrando ítems 1-20 de 24

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A Pipeline for the QR Update in Digital Signal Processing

Dolz, Manuel F.; Alventosa, Fran J.; Alonso-Jordá, Pedro; Vidal Maciá, Antonio Manuel (John Wiley & Sons, 2019)

[EN] The input and output signals of a digital signal processing system can often be represented by a rectangular matrix as it is the case of the beamformer algorithm, a very useful particular algorithm that allows extraction ...
A pipeline structure for the block QR update in digital signal processing

Dolz, Manuel F.; Alventosa, Fran J.; Alonso-Jordá, Pedro; Vidal Maciá, Antonio Manuel (Springer-Verlag, 2019)

[EN] There exist problems in the field of digital signal processing, such as filtering of acoustic signals that require processing a large amount of data in real time. The beamforming algorithm, for instance, is a process ...
Analyzing the impact of the MPI allreduce in distributed training of convolutional neural networks

Castelló, Adrián; Catalán, Mar; Dolz, Manuel F.; Quintana-Ortí, Enrique S.; Duato, José (Springer-Verlag, 2023-05)

[EN] For many distributed applications, data communication poses an important bottleneck from the points of view of performance and energy consumption. As more cores are integrated per node, in general the global performance ...
Assessing power monitoring approaches for energy and power analysis of computers

Diouri, Mohammed El Mehdi; Dolz Zaragozá, Manuel Francisco; Glück, Olivier; Lefèvre, Laurent; Alonso-Jordá, Pedro; Catalán, Sandra; Mayo, Rafael; Quintana Ortí, Enrique Salvador (Elsevier, 2014-06)

Large-scale distributed systems (e.g., datacenters, HPC systems, clouds, large-scale networks, etc.) con- sume and will consume enormous amounts of energy. Therefore, accurately monitoring the power dissipation and energy ...
BestOf: an online implementation selector for the training and inference of deep neural networks

Barrachina, Sergio; Castelló, Adrián; Dolz, Manuel F.; Tomás Domínguez, Andrés Enrique (Springer-Verlag, 2022-05-20)

[EN] Tuning and optimising the operations executed in deep learning frameworks is a fundamental task in accelerating the processing of deep neural networks (DNNs). However, this optimisation usually requires extensive ...
Block pivoting implementation of a symmetric Toeplitz solver

Alonso-Jordá, Pedro; Dolz Zaragozá, Manuel Francisco; Vidal Maciá, Antonio Manuel (Elsevier, 2014-05-01)

Toeplitz matrices are characterized by a special structure that can be exploited in order to obtain fast linear system solvers. These solvers are difficult to parallelize due to their low computational cost and their closely ...
Desarrollo y evaluación de los esquemas de paralelización de datos y de modelo para el entrenamiento de redes neuronales convolucionales

Catalán Carbó, Mar (Universitat Politècnica de València, 2020-09-04)

[ES] En los últimos años, las Redes Neuronales Profundas (RNPs) han resurgido debido a la confluencia de tres importantes factores: i) la avalancha de datos disponibles (big data), que incrementan la robustez de las RNPs; ...
Desarrollo y paralelización del algoritmo de convolución rápida de Winograd sobre plataformas ARM de bajo consumo.

Cuadrillero Geer, Duero Joshua (Universitat Politècnica de València, 2021-12-28)

[ES] Los avances en el diseño y desarrollo de redes neuronales convolucionales profundas, así como el incremento de la precisión de las mismas en el campo de la visión artificial, ha supuesto su amplia adopción en un gran ...
Desarrollo, optimización y despliegue de un servidor eficiente para la inferencia de redes neuronales de apoyo al radiodiagnóstico.

Dorronsoro Larbide, Ibai (Universitat Politècnica de València, 2023-01-09)

[ES] En este documento se presenta el Trabajo de Final de Máster del Máster Universitario en Computación en la Nube y de Altas Prestaciones de la Universidad Politécnica de Valencia, consistente en el desarrollo, optimización ...
Despliegue de un entorno de trabajo con redes neuronales en un clúster en AKS

Mira Hernández, Ismael (Universitat Politècnica de València, 2024-10-22)

[ES] Las necesidades de cómputo tanto de empresas como de particulares han experimentado un gran crecimiento en la última década, principalmente por la combinación de varios factores, entre los que se incluye la cada vez ...
DVFS-control techniques for dense linear algebra operations on multi-core processors

Alonso-Jordá, Pedro; Dolz Zaragozá, Manuel Francisco; Igual, Francisco D.; Mayo, Rafael; Quintana Ortí, Enrique Salvador (Springer Verlag (Germany), 2012-11)

[EN] This paper analyzes the impact on power con- sumption of two DVFS-control strategies when applied to the execution of dense linear algebra operations on multi- core processors. The strategies considered here, prototyped ...
Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors

Barrachina, Sergio; Dolz, Manuel F.; San Juan, Pablo; Quintana-Ortí, Enrique S. (Elsevier, 2022-09)

[EN] Convolutional Neural Networks (CNNs) play a crucial role in many image recognition and classification tasks, recommender systems, brain-computer interfaces, etc. As a consequence, there is a notable interest in ...
Efficient and Portable Winograd Convolutions for Multi-core Processors

Dolz Zaragozá, Manuel Francisco; Martínez, Héctor; Castelló, Adrián; Alonso-Jordá, Pedro; Quintana-Ortí, Enrique S. (Springer-Verlag, 2023-02-12)

[EN] We take a step forward towards developing high-performance codes for the convolution operator, based on the Winograd algorithm, that are easy to customise for general-purpose processor architectures. In our approach, ...
Energy-efficient execution of dense linear algebra algorithms on multi-core processors

Alonso-Jordá, Pedro; Dolz Zaragozá, Manuel Francisco; Mayo, Rafael; Quintana-Ortí, Enrique S. (Springer Verlag (Germany), 2013-09)

This paper addresses the efficient exploitation of task-level parallelism, present in many dense linear alge- bra operations, from the point of view of both computa- tional performance and energy consumption. The strategies ...
Enhancing performance and energy consumption of runtime schedulers for dense linear algebra

Alonso-Jordá, Pedro; Dolz Zaragozá, Manuel Francisco; Igual, Francisco D.; Mayo, Rafael; Quintana Ortí, Enrique Salvador (Wiley, 2014-10)

The road towards Exascale Computing requires a holistic effort to address three different challenges simultaneously: high performance, energy efficiency, and programmability. The use of runtime task schedulers to orchestrate ...
High performance and energy efficient inference for deep learning on multicore ARM processors using general optimization techniques and BLIS

Castelló, Adrián; SERGIO BARRACHINA; DOLZ ZARAGOZÁ, MANUEL FRANCISCO; Enrique S. Quintana-Ortí; San Juan-Sebastian, Pablo; Tomás Domínguez, Andrés Enrique (Elsevier, 2022-04)

[EN] We evolve PyDTNN, a framework for distributed parallel training of Deep Neural Networks (DNNs), into an efficient inference tool for convolutional neural networks. Our optimization process on multicore ARM processors ...
Modeling power and energy consumption of dense matrix factorizations on multicore processors

Alonso Jordá, Pedro; Dolz Zaragozá, Manuel Francisco; Mayo, Rafael; Quintana Ortí, Enrique Salvador (Wiley, 2014-12)

[EN] In this paper, we propose a model for the energy consumption of the concurrent execution of three key dense matrix factorizations, with task parallelism leveraged via the Symmetric Multi-Processing Superscalar (SMPSs) ...
Modeling power and energy of the task-parallel Cholesky factorization on multicore processors

Alonso-Jordá, Pedro; Dolz Zaragozá, Manuel Francisco; Mayo, Rafael; Quintana Ortí, Enrique Salvador (Springer Verlag (Germany), 2014-05)

[EN] In this paper we introduce a model for the total energy consumption of the Cholesky factorization on a multicore processor. Our model assumes a task- parallel execution of the factorization process, with con- currency ...
Optimización de los procesos de triaje en servicios de urgencias mediante transformadores de visión sobre radiografías de tórax

Soler Guiral, Ferran (Universitat Politècnica de València, 2023-09-25)

[ES] La sencillez de adquisición de las radiografías simples de tórax, así como su gran utilidad en la detección de diversas patologías, las convierten en una de las pruebas más solicitadas en los servicios de urgencias ...
Optimización de software científico mediante diversas herramientas de paralelización

Pasogias Guallart, Juan Teodoro (Universitat Politècnica de València, 2019-10-25)

[ES] El presente trabajo de final de máster presenta una comparativa entre dos herramientas de paralelización de CPUs multi-core. El entorno de trabajo sobre el que se realiza la comparativa es un benchmark, una herramienta ...