David Atienza Alonso

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New tendencies in the consumer electronics market present Multi-Processor Systems-On-Chip (MPSoCs) as a promising solution for meeting the processing demands of upcoming generations of user applications. MPSoCs are complex to design, as they must execute m ...

This paper introduces SIMinG-1k-a manycore simulator infrastructure. SIMinG-1k is a graphics processing unit accelerated, parallel simulator for design-space exploration of large-scale manycore systems. It features an optimal trade-off between modeling acc ...

This paper presents the system-level architecture of novel ultra-low power wireless body sensor nodes (WBSNs) for real-time cardiac monitoring and analysis, and discusses the main design challenges of this new generation of medical devices. In particular, ...

The design of reliable wearable technologies for real-time and long-term monitoring presents a major challenge. Self-awareness is a promising solution that enables the system to monitor itself in interaction with the environment and to manage its resources ...

Continuous monitoring of patients suffering from cardiovascular diseases and, in particular, myocardial infarction (MI) places a considerable burden on health-care systems and government budgets. The rise of wearable devices alleviates this burden, allowin ...

Epilepsy is a highly prevalent chronic neurological disorder with great negative impact on patients' daily lives. Despite this there is still no adequate technological support to enable epilepsy detection and continuous outpatient monitoring in everyday li ...

With technology advances, the number of cores integrated on a chip and their speed of operation is increasing. This, in turn is leading to a significant increase in chip temperature. Temperature gradi- ents and hot-spots not only affect the performance of ...

Objective: Today, stress monitoring on wearable devices is challenged by the tension between high-detection accuracy and battery lifetime driven by multimodal data acquisition and processing. Limited research has addressed the classification cost on multim ...

Multi-Scale computing systems aim at bringing the computing as close as possible to the data sources, to optimize both computation and networking. These systems are composed of at least three computing layers: the terminal layer, the edge layer, and the cl ...

Wearable devices for health monitoring are essential for tracking individuals' health status and facilitating early detection of diseases. However, processing biomedical signals online for real-time monitoring is challenging due to limited computational re ...

Energy consumption is a significant obstacle to integrate deep learning into edge devices. Two common techniques to curve it are quantization, which reduces the size of the memories (static energy) and the number of accesses (dynamic energy), and voltage s ...

Multi-Processor System-On-Chip (MPSoC) can provide the performance levels required by high-end embedded applications. However, they do so at the price of an increasing power density, which may lead to thermal runaway if coupled with low-cost packaging and ...

Modern high-performance processors employ ther- mal management systems, which rely on accurate readings of on-die thermal sensors. Systematic tools for analysis and determination of best allocation and placement of thermal sensors is therefore a highly rel ...

New applications demand very high processing power when run on embedded systems. Very Long Instruction Word (VLIW) architectures have emerged as a promising alternative to provide such processing capabilities under the given energy budget. However, in this ...

Objective Long-term automatic detection of focal seizures remains one of the major challenges in epilepsy due to the unacceptably high number of false alarms from state-of-the-art methods. Our aim was to investigate to what extent a new patient-specific ap ...

The increasing adoption of smart systems in our daily life has led to the development of new applications with varying performance and energy constraints, and suitable computing architectures need to be developed for these new applications. In this paper, ...

Several technologies with sub-lithographic features are targeting the fabrication of crossbar memories in which the nanowire decoder is playing a major role. In this paper, we suggest a way to reduce the decoder size and keep it defect tolerant by using mu ...

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 ...

As the demand for high channel counts and high-resolution recordings of neural activity continues to grow, the increased power and data rate generated impose hard constraints on the telemetry capabilities of wireless implantable neural interfaces. To addre ...

Integrated microfluidic power generation and power delivery promises to be a disruptive packaging technology with the potential to combat dark silicon. It essentially consists of integrated microchannel-based electrochemical “flow cells” in a 2D/3D multipr ...

David Atienza Alonso

Chattez avec Graph Search

Application of FPGA Emulation to SoC Floorplan and Packaging Exploration

SIMinG-1k: A thousand-core simulator running on general-purpose graphical processing units

Ultra-Low Power Design of Wearable Cardiac Monitoring Systems

Self-Aware Machine Learning for Multimodal Workload Monitoring During Manual Labor on Edge Wearable Sensors

Real-time classification technique for early detection and prevention of myocardial infarction on wearable devices

Combining general and personal models for epilepsy detection with hyperdimensional computing

Temperature Control of High Performance Multicore Platforms Using Convex Optimization

CAFS: Cost-Aware Features Selection Method for Multimodal Stress Monitoring on Wearable Devices

Special Session: Challenges and Opportunities for Sustainable Multi-Scale Computing Systems

ACE: Automated optimization towards iterative Classification in Edge health monitors

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

Multi-Processor Operating System Emulation Framework with Thermal Feedback for Systems-on-Chip

Temperature sensor placement in thermal management systems for MPSoCs

Joint Hardware-Software Leakage Minimization Approach for the Register File of VLIW Embedded Architectures

Personalized seizure signature: An interpretable approach to false alarm reduction for long‐term epileptic seizure detection

Gem5-X : A Many-Core Heterogeneous Simulation Platform for Architectural Exploration and Optimization

Fault-Tolerant Multi-Level Logic Decoder for Nanoscale Crossbar Memory Arrays

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

A Reconfigurable High-Dynamic Range ∆Σ Front-End with Event-Based Decimation for Bandwidth-Efficient Implantable Neural Interfaces

PowerCool: Simulation of Integrated Microfluidic Power Generation in Bright Silicon MPSoCs