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David Atienza Alonso

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Related publications (385)

Page 3 of 20

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

David Atienza Alonso, Amir Aminifar, Miguel Peon Quiros, Adriana Arza Valdes, Elisabetta De Giovanni

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel compu ...

2021

Exploration of Memory Hierarchy Configurations for Efficient Garbage Collection on High-Performance Embedded Systems

David Atienza Alonso

Modern embedded devices (e.g., PDAs, mobile phones) are now incorporating Java as a very popular implementation language in their designs. These new embedded systems include multiple applications that are dynamically launched by the user, which can produce ...

ACM Press2009

Register File Reliability Analysis Through Cycle-Accurate Thermal Emulation

David Atienza Alonso, José Luis Ayala Rodrigo, Pablo Garcia del Valle

Continuous transistor scaling due to improvements in CMOS devices and manufacturing technologies is increasing processor power densities and temperatures; thus, creating challenges when trying to maintain manufacturing yield rates and devices which will be ...

IEEE Computer Society2008

Reconfiguration Strategies for Environmentally Powered Devices: Theoretical Analysis and Experimental Validation

Giovanni De Micheli, David Atienza Alonso

Environmental energy is becoming a feasible alternative to traditional energy sources for ultra low-power devices such as sensor nodes. These devices can run reactive applications that adapt their control flow depending on the sensed data. In order to redu ...

Springer-Verlag Berling2007

Run-time Mapping of Applications on FPGA-based Reconfigurable Systems

David Atienza Alonso, Ivan Beretta

The role of Field-Programmable Gate Arrays (FPGAs) in System-on-Chip (SoC) design considerably increased in the last few years. Their established importance is due to the large amount of hardware resources they offer, as well as to their increasing perform ...

IEEE Press2010

Cough-E: A multimodal, privacy-preserving cough detection algorithm for the edge

David Atienza Alonso, Tomas Teijeiro Campo, Jonathan Dan, Lara Orlandic, Jérôme Paul Rémy Thevenot, Stefano Albini

Continuous cough monitors can greatly benefit doctors in home monitoring and treatment of respiratory diseases. Although many works propose algorithms to automate this task, they suffer of poor data privacy and short-term monitoring. Edge-AI is a promising ...

2025

REMOTE: Re-thinking Task Mapping on Wireless 2.5D Systems-on-Package for Hotspot Removal

David Atienza Alonso, Giovanni Ansaloni, Marina Zapater Sancho, Darong Huang, Rafael Medina Morillas

2.5D Systems-on-Package (SoPs) are composed by several chiplets placed on an interposer. They are becoming increasingly popular as they enable easy integration of electronic components in the same package and high fabrication yields. Nevertheless, they int ...

2023

An Inexact Ultra-low Power Bio-signal Processing Architecture With Lightweight Error Recovery

David Atienza Alonso, Giovanni Ansaloni, Ruben Braojos Lopez, Soumya Subhra Basu, Loris Gérard Duch

The energy e fficiency of digital architectures is tightly linked to the voltage level (Vdd) at which they operate. Aggressive voltage scaling is therefore mandatory when ultra-low power processing is required. Nonetheless, the lowest admissible Vdd is o e ...

2017

Systolic Arrays and Structured Pruning Co-design for Efficient Transformers in Edge Systems

David Atienza Alonso, Giovanni Ansaloni, Rafael Medina Morillas, Pedro Palacios Almendros

Efficient deployment of resource-intensive transformers on edge devices necessitates cross-stack optimization. We thus study the interrelation between structured pruning and systolic acceleration, matching the size of pruned blocks with the systolic array ...

Association for Computing Machinery2025

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Qunyou Liu, David Atienza Alonso, Marina Zapater Sancho, Darong Huang, Luis Maria Costero Valero

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

2024

Point-process-based Representation Learning for Electronic Health Records

David Atienza Alonso, Anisoara Ionescu, Hojjat Karami

Irregular sampling of time series in electronic health records (EHRs) presents a challenge for the development of machine learning models. Additionally, the pattern of missing data in certain clinical variables is not random, but depends on the decisions o ...

IEEE2023

A hardware/software co-design vision for deep learning at the edge

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Miguel Peon Quiros, Flavio Ponzina, Marco Antonio Rios, Benoît Walter Denkinger, Simone Machetti

The growing popularity of edgeAI requires novel solutions to support the deployment of compute-intense algorithms in embedded devices. In this article, we advocate for a holistic approach, where application-level transformations are jointly conceived with ...

2022

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

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

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

Big-Data Streaming Applications Scheduling Based on Staged Multi-Armed Bandits

David Atienza Alonso, Karim Kanoun, Cem Tekin

Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to adapt at run-time the throughput and ...

Institute of Electrical and Electronics Engineers2016

Object-oriented modelling of advanced computer cooling solutions

David Atienza Alonso

Modern computing systems are so energy- intensive to make efficient cooling vital for their operation. This is giving rise to a variety of innovative cooling solutions based on a mix of traditional and new techniques. The design and engineering of these so ...

Elsevier2023

Low-power processor architecture exploration for online biomedical signal analysis

David Atienza Alonso, Andreas Peter Burg, Luca Benini, Jeremy Hugues-Felix Constantin, Ahmed Yasir Dogan

In this study, the authors explore sequential and parallel processing architectures, utilising a custom ultra-low-power (ULP) processing core, to extend the lifetime of health monitoring systems, where slow biosignal events and highly parallel computations ...

Inst Engineering Technology-Iet2012

Knowledge-based design space exploration of wireless sensor networks

David Atienza Alonso, Ivan Beretta

The complexity of Wireless Sensor Networks (WSNs) has been constantly increasing over the last decade, and the necessity of efficient CAD tools has been growing accordingly. In fact, the size of the design space of a WSN has become large, and an exploratio ...

ACM Press2012

Reliability-Aware Design for Nanometer-Scale Devices

Giovanni De Micheli, David Atienza Alonso, Luca Benini, José Luis Ayala Rodrigo, Pablo Garcia del Valle

Continuous transistor scaling due to improvements in CMOS devices and manufacturing technologies is increasing processor power densities and temperatures; thus, creating challenges to maintain manufacturing yield rates and reliable devices in their expecte ...

2008

A Parallel Evolutionary Algorithm to Optimize Dynamic Memory Managers in Embedded Systems

David Atienza Alonso

For the last 30 years, several dynamic memory managers (DMMs) have been proposed. Such DMMs include first fit, best fit, segregated fit and buddy systems. Since the performance, memory usage and energy consumption of each DMM differs, software engineers of ...

Elsevier2010

Towards Near-Threshold Server Processors

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

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