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Marina Zapater Sancho

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Publications associées (59)

A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories

David Atienza Alonso, Xifan Tang, Pierre-Emmanuel Julien Marc Gaillardon, Edouard Giacomin, Marina Zapater Sancho, Yasir Mahmood Qureshi, João Miguel Morgado Pereira Vieira

The need for running complex Machine Learning (ML) algorithms, such as Convolutional Neural Networks (CNNs), in edge devices, which are highly constrained in terms of computing power and energy, makes it important to execute such applications efficiently. ...

2019

HackRF plus GNU Radio: A software-defined radio to teach communication theory

José Luis Ayala Rodrigo, Roman Hermida Correa, Marina Zapater Sancho

In this paper, an alternative to the traditional methodology related to signal processing-like subjects is proposed. These are subjects that require a deep mathematical and theoretical basis, but the practical goal is not often emphasized, which drives stu ...

SAGE PUBLICATIONS LTD2019

A QoS and Container-Based Approach for Energy Saving and Performance Profiling in Multi-Core Servers

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar, Wellington Silva De Souza

In this work we present ContainEnergy, a new performance evaluation and profiling tool that uses software containers to perform application runtime assessment, providing energy and performance profiling data. It is focused on energy efficiency for next gen ...

IEEE2019

A Machine Learning-Based Framework for Throughput Estimation of Time-Varying Applications in Multi-Core Servers

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar, Wellington Silva De Souza

2019

A Design Framework for Thermal-Aware Power Delivery Network in 3D MPSoCs with Integrated Flow Cell Arrays

Halima Najibi, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse

Integrated Flow Cell Array (FCA) technology promises to address the power delivery and heat dissipation challenges in three-dimensional Multi Processor Systems-on-Chips (3D MPSoCs) by providing combined inter-tier liquid cooling and power generation capabi ...

2019

An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication

David Atienza Alonso, William Andrew Simon, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios

With the spread of cloud services and Internet of Things concept, there is a popularization of machine learning and artificial intelligence based analytics in our everyday life. However, an efficient deployment of these data-intensive services requires per ...

2019

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Xiaoyu Qu

Modern cloud data centers (DCs) need to tackle efficiently the increasing demand for computing resources and address the energy efficiency challenge. Therefore, it is essential to develop resource provisioning policies that are aware of virtual machine (VM ...

2018

Machine Learning-Based Quality-Aware Power and Thermal Management of Multistream HEVC Encoding on Multicore Servers

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar

The emergence of video streaming applications, together with the users’ demand for high-resolution contents, has led to the development of new video coding standards, such as High Efficiency Video Coding (HEVC). HEVC provides high efficiency at the cost of ...

2018

Design of a Two-Phase Gravity-Driven Micro-Scale Thermosyphon Cooling System for High-Performance Computing Data Centers

John Richard Thome, David Atienza Alonso, André Olivier Seuret, Marina Zapater Sancho, Arman Iranfar

Next-generation High-Performance Computing (HPC) systems need to provide outstanding performance with unprecedented energy efficiency while maintaining servers at safe thermal conditions. Air cooling presents important limitations when employed in HPC infr ...

2018

Design Optimization of 3D Multi-Processor System-on-Chip with Integrated Flow Cell Arrays

David Atienza Alonso, Ayse Kivilcim Coskun, Artem Andreev, Marina Zapater Sancho, Fulya Kaplan

Integrated flow cell array (FCA) is an emerging technology, targeting the cooling and power delivery challenges of modern 2D/3D Multi-Processor Systems-on-Chip (MPSoCs). In FCA, electrolytic solutions are pumped through microchannels etched in the silicon ...

2018

Reliable Power and Time-Constraints-Aware Predictive Management of Heterogeneous Exascale Systems

David Atienza Alonso, Leila Cammoun, Marina Zapater Sancho, Simone Libutti

ASSOC COMPUTING MACHINERY2018

Fast Energy Estimation Through Partial Execution of HPC Applications

José Luis Ayala Rodrigo, Marina Zapater Sancho

In order to optimize the energy use of servers in Data Centers, techniques such as power capping or power budgeting are usually deployed. These techniques rely on the prediction of the power and execution time of applications. These data are obtained via d ...

IEEE2018

Online Efficient Bio-Medical Video Transcoding on MPSoCs Through Content-Aware Workload Allocation

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Arman Iranfar

Bio-medical image processing in the field of telemedicine, and in particular the definition of systems that allow medical diagnostics in a collaborative and distributed way is experiencing an undeniable growth. Due to the high quality of bio-medical videos ...

IEEE and ACM Press2018

Exploring manycore architectures for next-generation HPC systems through the MANGO approach

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar, Simone Libutti

The Horizon 2020 MANGO project aims at exploring deeply heterogeneous accelerators for use in High Performance Computing systems running multiple applications with different Quality of Service (QoS) levels. The main goal of the project is to exploit custom ...

ELSEVIER SCIENCE BV2018

Energy Proportionality in Near-Threshold Computing Servers and Cloud Data Centers: Consolidating or Not?

David Atienza Alonso, Luca Benini, Ali Pahlevan, Marina Zapater Sancho, Yasir Mahmood Qureshi

Cloud Computing aims to efficiently tackle the increasing demand of computing resources, and its popularity has led to a dramatic increase in the number of computing servers and data centers worldwide. However, as effect of post-Dennard scaling, computing ...

2018

A Machine Learning-Based Strategy for Efficient Resource Management of Video Encoding on Heterogeneous MPSoCs

David Atienza Alonso, William Andrew Simon, Marina Zapater Sancho, Arman Iranfar

The design of new streaming systems is becoming a major area of research to deploy services targeted in the Internet-of-Things (IoT) era. In this context, the new High Efficiency Video Coding (HEVC) standard provides high efficiency and scalability of qual ...

2018

PowerCool: Simulation of Cooling and Powering of 3D MPSoCs with Integrated Flow Cell Arrays

David Atienza Alonso, Mohamed Mostafa Sabry Aly, Arvind Raj Mahankali Sridhar, Bruno Michel, Artem Andreev, Marina Zapater Sancho

Integrated Flow-Cell Arrays (FCAs) represent a combination of integrated liquid cooling and on-chip power generation, converting chemical energy of the flowing electrolyte solutions to electrical energy. The FCA technology provides a promising way to addre ...

Institute of Electrical and Electronics Engineers2017

Work-in-Progress: A Machine Learning-Based Approach for Power and Thermal Management of Next-Generation Video Coding on MPSoCs

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar

2017

Towards Near-Threshold Server Processors

David Atienza Alonso, Luca Benini, Pablo Garcia del Valle, Babak Falsafi, Javier Picorel Obando, Ali Pahlevan, Arash Pourhabibi Zarandi, Marina Zapater Sancho

The popularity of cloud computing has led to a dramatic increase in the number of data centers in the world. The ever-increasing computational demands along with the slowdown in technology scaling has ushered an era of power-limited servers. Techniques suc ...

IEEE/ACM2016

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