David Atienza Alonso

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A considerable portion of government health-care spending is allocated to the continuous monitoring of patients suffering from cardiovascular diseases, particularly myocardial infarction (MI). Wearable devices present a cost-effective means of monitoring p ...

Deep convolutional neural networks have recently emerged as a state-of-the art tool in detection of seizures. Such models offer the ability to extract complex nonlinear representations of an electroencephalogram (EEG) signal which can improve accuracy over ...

Network-on-Chip (NoC) has emerged as a very promising paradigm for designing scalable communication architecture for Systems on Chips (SoCs). However, NoCs designed to fulfill the bandwidth requirements between the cores of an SoC for a certain set of runn ...

Numerous Directed-Acyclic Graph (DAG) schedulers have been developed to improve the energy efficiency of various multi-core platforms. However, these schedulers make a priori assumptions about the relationship between the task dependencies, and they are un ...

When arranged in a crossbar configuration, resistive memory devices can be used to execute Matrix-Vector Multiplications (MVMs), the most dominant operation of many Machine Learning (ML) algorithms, in constant time complexity. Nonetheless, when performing ...

Vertically-integrated 3D multiprocessors systems-on-chip (3D MPSoCs) provide the means to continue integrating more functionality within a unit area while enhancing manufacturing yields and runtime performance. However, 3D MPSoCs incur amplified thermal ch ...

The advent of online video streaming services along with the users' demand for high-quality contents require High Efficiency Video Coding (HEVC), which provides higher quality and compression at the cost of increased complexity. On one hand, HEVC exposes a ...

This study presents a single-core and a multi-core processor architecture for health monitoring systems where slow biosignal events and highly parallel computations exist. The single-core architecture is composed of a processing core (PC), an instruction m ...

Wireless sensor networks (WNSs) are gradually evolving from a promising technology to a well-established reality in a large set of different domains. In order to fulfill the requirements of the specific scenario, a WSN must provide the right tradeoffs betw ...

In deep submicron circuits, high temperatures have created critical issues in reliability, timing, performance, coolings costs and leakage power. Task migration techniques have been proposed to manage efficiently the thermal distribution in multi-processor ...

Traditionally, parallel implementations of multimedia algorithms are carried out manually, since the automation of this task is very difficult due to the complex dependencies that generally exist between different elements of the data set. Moreover, there ...

Edge devices must support computationally demanding algorithms, such as neural networks, within tight area/energy budgets. While approximate computing may alleviate these constraints, limiting induced errors remains an open challenge. In this paper, we pro ...

Full-System (FS) simulation is essential for performance evaluation of complete systems that execute complex applications on a complete software stack consisting of an operating system and user applications. Nevertheless, they require careful fine-tuning a ...

Inferences using Convolutional Neural Networks (CNNs) are resource and energy intensive. Therefore, their execution on highly constrained edge devices demands the careful co-optimization of algorithms and hardware. Addressing this challenge, in this paper ...

Today, wearable systems are facing fundamental barriers in terms of battery lifetime and quality of their results. The main challenge in wearable systems is to increase the battery lifetime, while maintaining the machine-learning performance of the system. ...

Temperature-driven floorplaners have been recently proposed to alleviate the thermal problem in 3D multi-processor systems-on-chip (MPSoC). However, the proposed algorithms fail to provide fast placement of the modules when the complexity and the number of ...

Cognitive workload affects operators' performance principally in high-risk or time-demanding situations and when multitasking is required. An online cognitive workload monitoring system can provide valuable inputs to decision-making instances, such as the ...

As the geometries of the transistors reach the physical limits of operation, one of the main design challenges of Systems-on-Chips (SoCs) will be to provide dynamic (run-time) support against permanent and intermittent faults that can occur in the system. ...

At the intersection between traditional CPU architectures and more specialized options such as FPGAs or ASICs lies the family of reconfigurable hardware architectures, termed Coarse-Grained Reconfigurable Arrays (CGRAs). CGRAs are composed of a 2-dimension ...

Epilepsy is one of the most prevalent paroxystic neurological disorders that can dramatically degrade the quality of life and may even lead to death. Therefore, real-time epilepsy monitoring and seizure detection has become important over the past decades. ...

David Atienza Alonso

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Real-Time Event-Driven Classification Technique for Early Detection and Prevention of Myocardial Infarction on Wearable Systems

Noise-Resilient and Interpretable Epileptic Seizure Detection

A Reconfigurable Network-on-Chip Architecture for Optimal Multi-Processor SoC Communication

Online Energy-Efficient Task-Graph Scheduling for Multicore Platforms

LIONHEART: A Layer-based Mapping Framework for Heterogeneous Systems with Analog In-Memory Computing Tiles

Temperature-Aware Design and Management for 3D Multi-Core Architectures

Resource Management for Power-Constrained HEVC Transcoding Using Reinforcement Learning

Power/Performance Exploration of Single-core and Multi-core Processor Approaches for Biomedical Signal Processing

Design Exploration of Energy-Performance Trade-offs for Wireless Sensor Networks

Adaptive Task Migration Policies for Thermal control in MPSoCs

Design Methods for Parallel Hardware Implementation of Multimedia Iterative Algorithms

Exact Neural Networks from Inexact Multipliers via Fibonacci Weight Encoding

Towards Accurate RISC-V Full System Simulation via Component-level Calibration

A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs

Self-Aware Wearable Systems in Epileptic Seizure Detection

Fast and Scalable Temperature-driven Floorplan Design in 3D MPSoCs

MBioTracker: Multimodal Self-Aware Bio-Monitoring Wearable System for Online Workload Detection

Reliability Support for On-chip Memories Using Networks-on-Chips

A flexible framework for early power and timing comparison of time-multiplexed CGRA kernel executions

A Self-Aware Epilepsy Monitoring System for Real-Time Epileptic Seizure Detection