David Atienza Alonso

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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. ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

New tendencies envisage Multi-Processor Systems-On-Chip (MPSoCs) as a promising solution for the consumer electronics market. MPSoCs are complex to design, as they must execute multiple applications (games, video), while meeting additional design constrain ...

Epilepsy is one of the most common neurological disorders and affects over 65 million people worldwide. Despite the continuing advances in anti-epileptic treatments, one third of the epilepsy patients live with drug resistant seizures. Besides, the mortali ...

The development of compiler-based mechanisms to optimize the thermal profile of large register files to improve the processor reliability has become an important issue. Thermal hotspots have been known to cause severe reliability issues, while the thermal ...

Free cooling, i.e., directly using outside cold air and/or water to cool down datacenters, can provide significant power savings of datacenters. However, due to the limited cooling capability, which is tightly coupled with climate conditions, free cooling ...

The fabrication of crossbar memories with sublithographic features is expected to be feasible within several emerging technologies; in all of them, the nanowire (NW) decoder is a critical part since it bridges the sublithographic wires to the outer circuit ...

David Atienza Alonso

Chattez avec Graph Search

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

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

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

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

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

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

Point-process-based Representation Learning for Electronic Health Records

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

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

Object-oriented modelling of advanced computer cooling solutions

Low-power processor architecture exploration for online biomedical signal analysis

Towards Near-Threshold Server Processors

Knowledge-based design space exploration of wireless sensor networks

Reliability-Aware Design for Nanometer-Scale Devices

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

HW-SW Emulation Framework for Temperature-Aware Design in MPSoCs

A Self-Learning Methodology for Epileptic Seizure Detection with Minimally Supervised Edge Labeling

Thermal-Aware Compilation for Register Window-Based Embedded Processors

Free Cooling-Aware Dynamic Power Management for Green Datacenters

Variability-Aware Design of Multilevel Logic Decoders for Nanoscale Crossbar Memories