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Giovanni Ansaloni

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Publications associées (67)

A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

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 ...

2021

Exact Neural Networks from Inexact Multipliers via Fibonacci Weight Encoding

David Atienza Alonso, Giovanni Ansaloni, William Andrew Simon, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse

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 ...

2021

DB4HLS: A Database of High-Level Synthesis Design Space Explorations

Giovanni Ansaloni

High-level synthesis (HLS) frameworks allow to easily specify a large number of variants of the same hardware design by only acting on optimization directives. Nonetheless, the hardware synthesis of implementations for all possible combinations of directiv ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Running Efficiently CNNs on the Edge Thanks to Hybrid SRAM-RRAM In-Memory Computing

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

The increasing size of Convolutional Neural Networks (CNNs) and the high computational workload required for inference pose major challenges for their deployment on resource-constrained edge devices. In this paper, we address them by proposing a novel In-M ...

IEEE2021

Modelling of vertical and ferroelectric junctionless technology for efficient 3D neural network compute cube dedicated to embedded artificial intelligence

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse

This paper presents the set of simulation means used to develop the concept of N2C2 (neural network compute cube) based on a vertical transistor technology platform. On the basis of state-of-the-art junctionless nanowire transistors (JLNT), TCAD simulation ...

2021

i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing

David Atienza Alonso, Soumya Subhra Basu, Giovanni Ansaloni, Loris Gérard Duch, Miguel Peon Quiros

Smart edge sensors for bio-signal monitoring must support complex signal processing routines within an extremely small energy envelope. Coarse-Grained Reconfigurable Arrays (CGRAs) are good candidates for tackling these conflicting objectives because, than ...

2019

Tailoring SVM Inference for Resource-Efficient ECG-Based Epilepsy Monitors

David Atienza Alonso, Amir Aminifar, Leila Cammoun, Giovanni Ansaloni

Event detection and classification algorithms are resilient towards aggressive resource-aware optimisations. In this paper, we leverage this characteristic in the context of smart health monitoring systems. In more detail, we study the attainable benefits ...

IEEE2019

Heterogeneous and Inexact: Maximizing Power Efficiency of Edge Computing Sensors for Health Monitoring Applications

David Atienza Alonso, Soumya Subhra Basu, Giovanni Ansaloni, Loris Gérard Duch, Miguel Peon Quiros

In the Internet-of-Things (IoT) era, there is an increasing trend to enable intelligent behavior in edge computing sensors. Thus, a new generation of smart wearable devices for health monitoring is being developed, able to perform complex Digital Signal Pr ...

IEEE2018

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

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

The energy efficiency 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 ofte ...

Assoc Computing Machinery2017

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

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

A Synchronization-Based Hybrid-Memory Multi-Core Architecture for Energy-Efficient Biomedical Signal Processing

David Atienza Alonso, Luca Benini, Ruben Braojos Lopez, Giovanni Ansaloni

In the last decade, improvements on technology scaling have enabled the design of a novel generation of wearable bio-sensing monitors. These smart Wireless Body Sensor Nodes (WBSNs) are able to acquire and process biological signals, such as electrocardiog ...

Institute of Electrical and Electronics Engineers2017

HEAL-WEAR: an Ultra-Low Power Heterogeneous System for Bio-Signal Analysis

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

Personalized healthcare devices enable low-cost, unobtrusive and long-term acquisition of clinically-relevant biosignals. These appliances, termed Wireless Body Sensor Nodes (WBSNs), are fostering a revolution in health monitoring for patients affected by ...

Ieee-Inst Electrical Electronics Engineers Inc2017

A Multi-Core Reconfigurable Architecture for Ultra-Low Power Bio-Signal Analysis

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

This paper introduces a novel computing architecture devoted to the ultra-low power analysis of multiple bio-signals. Its structure comprises several processors interfaced with a shared acceleration resource, implemented as a Coarse Grained Reconfigurable ...

2016

Nano-Engineered Architectures for Ultra-Low Power Wireless Body Sensor Nodes

David Atienza Alonso, Mohamed Mostafa Sabry Aly, Ruben Braojos Lopez, Giovanni Ansaloni, Subhasish Mitra

Wireless body sensor nodes (WBSNs) are miniaturized devices that are able to acquire, process and transmit bio-signals (such as electrocardiograms, respiration or human-body kinetics). WBSNs face major design challenges due to extremely limited power budge ...

Assoc Computing Machinery2016

Inexact-Aware Architecture Design for Ultra-Low Power Bio-Signal Analysis

David Atienza Alonso, Pablo Garcia del Valle, Soumya Subhra Basu, Giovanni Ansaloni

This paper introduces an inexact, but ultra-low power, computing architecture devoted to the embedded analysis of bio-signals. The platform operates at extremely low voltage supply levels to minimize energy consumption. In this scenario, the reliability of ...

Inst Engineering Technology-Iet2016

Heterogeneous Error-Resilient Scheme for Spectral Analysis in Ultra-Low Power Wearable Electrocardiogram Devices

David Atienza Alonso, Pablo Garcia del Valle, Soumya Subhra Basu, Georgios Karakonstantis, Giovanni Ansaloni

Wearable devices performing advanced bio-signal analysis algorithms will foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term operations must be performed withi ...

IEEE Press2015

Method for detecting abnormalities in an electrocardiogram

David Atienza Alonso, Srinivasan Murali, Francisco Javier Rincon Vallejos, Ruben Braojos Lopez, Giovanni Ansaloni

A method for classification of ECG beats into normal and different categories of abnormal beats. The method comprises the following steps, performed on a computing platform: a. performing a training phase comprising taking as an input one or more ECG beats ...

2015

Hardware/Software Approach for Code Synchronization in Low-Power Multi-Core Sensor Nodes

David Atienza Alonso, Ruben Braojos Lopez, Ivan Beretta, Giovanni Ansaloni

Latest embedded bio-signal analysis applications, targeting low-power Wireless Body Sensor Nodes (WBSNs), present conflicting requirements. On one hand, bio-signal analysis applications are continuously increasing their demand for high computing capabiliti ...

IEEE/ACM Press2014

Early Classification of Pathological Heartbeats on Wireless Body Sensor Nodes

David Atienza Alonso, Ruben Braojos Lopez, Ivan Beretta, Giovanni Ansaloni

Smart Wireless Body Sensor Nodes (WBSNs) are a novel class of unobtrusive, battery-powered devices allowing the continuous monitoring and real-time interpretation of a subject's bio-signals, such as the electrocardiogram (ECG). These low-power platforms, w ...

MDPI2014

Ultra-Low Power Design of Wearable Cardiac Monitoring Systems

David Atienza Alonso, Srinivasan Murali, Francisco Javier Rincon Vallejos, Hossein Mamaghanian, Ruben Braojos Lopez, Giovanni Ansaloni, Alair Dias Junior

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, ...

IEEE2014

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