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Modular Design and Optimization of Biomedical Applications for Ultra-Low Power Heterogeneous Platforms

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Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

2024

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Embedded systems confront two opposite goals: low-power operation and high performance. The current trend to reach these goals is toward heterogeneous platforms, including multi-core architectures with heterogeneous cores and hardware accelerators. The lat ...

2023

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

EPFL2023

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Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

2022

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Objective: Continuous monitoring of biosignals via wearable sensors has quickly expanded in the medical and wellness fields. At rest, automatic detection of vital parameters is generally accurate. However, in conditions such as high-intensity exercise, sud ...

2022

In recent years, population aging and the consequent higher incidence of noncommunicable diseases, have increased the need for long-term health monitoring. Moreover, as healthcare cost is projected to grow substantially by 2030 in OECD countries, the deman ...

EPFL2021

Architecture Exploration and Optimization of Heterogeneous Many-Core Compute and Memory Architectures with Architectural Extensions

Yasir Mahmood Qureshi

The expeditious proliferation of Internet connectivity and the growing adoption of digital products have transformed various spheres of our everyday lives. This increased digitization of society has led to the emergence of new applications, which are deplo ...

EPFL2021

Modular Design and Optimization of Biomedical Applications for Ultralow Power Heterogeneous Platforms

David Atienza Alonso, Miguel Peon Quiros, Simone Machetti, Luca Benini, Benoît Walter Denkinger, Elisabetta De Giovanni, Fabio Montagna

In the last years, remote health monitoring is becoming an essential branch of health care with the rapid development of wearable sensors technology. To meet the demand of new more complex applications and ensuring adequate battery lifetime, wearable senso ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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 ...

2020

Pattern Recognition in Non-uniformly sampled electrocardiogram signal for wearable sensors

Silvio Zanoli

In this thesis, we explore 3 main topics: non-uniform (in time) sub-sampling, QRS detection in an event-based sub-sampled ECG (electrocardiogram) and implementation on a low-power MCU (Micro Controller Unit). The main idea behind this work is to reduce the ...

2019