Publications associées à Development of a Bond Graph Based Model of Computation for SystemC-AMS

Highly Parallel RTL Simulation

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

EPFL2024

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

Johanna Kristin Maria Becker

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

EPFL2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Primary and secondary order parameters in the fully frustrated transverse-field Ising model on the square lattice

Frédéric Mila

Using quantum Monte Carlo simulations and field-theory arguments, we study the fully frustrated transversefield Ising model on the square lattice for the purpose of quantitatively relating two different order parameters to each other. We consider a "primar ...

Amer Physical Soc2024

Intelligent RF System for Ultra Low Power Spectrum Sensing with Machine Learning

Naci Pekçokgüler

The crowdedness of the RF spectrum constitutes problems in communication, however it also accommodates large amount of useful information. This information can be used to determine existing signals and operating contexts. However, spectrum condition varies ...

EPFL2024

Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems

Keyvan Farhang Razi

Epilepsy is a common chronic neurological disorder that causes recurring seizures and affects more than 50 million people worldwide. Implantable medical devices (IMDs) are regarded as effective tools to cure patients who suffer from refractory epilepsy. Se ...

EPFL2023

Building Chips Faster: Hardware-Compiler Co-Design for Accelerated RTL Simulation

Sahand Kashani

The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators. Specialized hardware has already redefine ...

EPFL2023

A Front-End CMOS Interface Circuit With High Voltage Charge Pump and Oscillator for Capacitive Micromachined Ultrasonic Transducers

Sandro Carrara, Zhengwen Jiang, Gian Luca Barbruni, Yihe Zhao

Label-free biosensors, combined with miniaturized micro-electromechanical sensory platforms, offer an attractive solution for real-time and facile monitoring of biomolecules due to their high sensitivity and selectivity without the need for specifically la ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Analytic modelling of passive microfluidic mixers

Christophe Lallement, Jean-Michel Sallese

This paper deals with a new analytical model for microfluidic passive mixers. Two common approaches already exist for such a purpose. On the one hand, the resolution of the advection-diffusion-reaction equation (ADRE) is the first one and the closest to ph ...

AMER INST MATHEMATICAL SCIENCES-AIMS2022

Optimizing Lattice-based Post-Quantum Cryptography Codes for High-Level Synthesis

Andres Upegui, Francesco Regazzoni, Andrea Guerrieri

High-level synthesis is a mature Electronics Design Automation (EDA) technology for building hardware design in a short time. It produces automatically HDL code for FPGAs out of C/C++, bridging the gap from algorithm to hardware. Nevertheless, sometimes th ...

IEEE2022

Anisotropic and nonlinear transport in microstructured 3D topological semimetals

Xiangwei Huang

Topological semimetals are frequently discussed as materials platforms for future electronics that exploit the remarkable properties of their quasiparticles. These ideas are mostly based on dispersion relations that mimic relativistic particles, such as We ...

EPFL2022

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Andras Kis, Aleksandra Radenovic, Zhenyu Wang, Guilherme Migliato Marega, Mukesh Kumar Tripathi

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

High-Level Synthesis of Dynamically Scheduled Circuits

Lana Josipovic

High-Level Synthesis (HLS) tools generate hardware designs from high-level programming languages. These tools almost universally build datapaths that are controlled using a centralized controller which relies on a static, compile-time schedule to determine ...

EPFL2021

Nanowatt Acoustic Inference Sensing Exploiting Nonlinear Analog Feature Extraction

Christian Enz, Minhao Yang, Jun Zhang

Ultralow-power sensing with inference functionality embedded in sensor nodes is essential for enabling the emerging pervasive intelligence. For acoustic inference sensing, the feature extraction can take advantage of power-efficient analog circuits. Howeve ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure

Davide Pradovera

Many engineering fields rely on frequency-domain dynamical systems for the mathematical modeling of physical (electrical/mechanical/etc.) structures. With the growing need for more accurate and reliable results, the computational burden incurred by frequen ...

EPFL2021

Adaptive Body Biasing in Strong Body Factor Technologies

Thomas Christoph Müller

With the advent of intelligent sensor nodes in everyday life, low power aspects of system design become more and more important. Adaptive body biasing is a promising methodology to achieve dynamic adaptation of the tradeoff between performance and energy b ...

EPFL2021

Characterization of Real-World Power System Signals in Non-Stationary Conditions using a Dictionary Approach

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

As power grids transition towards low-inertia net-works based on converter-interfaced renewable energy resources, they become increasingly vulnerable to extreme dynamics. Currently, the most advanced methods for signal processing in power systems are embed ...

IEEE2021

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

A Laplacian approach to stubborn agents and their role in opinion formation on influence networks

Melvyn Sandy Tyloo

Within the framework of a simple model for social influence, the Taylor model, we analytically investigate the role of stubborn agents in the overall opinion dynamics of networked systems. Similar to zealots, stubborn agents are biased towards a certain op ...

2020

Prediction of optically-triggered amplification in phototransistor with SPICE circuit simulators

Jean-Michel Sallese, Chiara Rossi

Modeling of optoelectronic devices involves long and complex numerical simulations, usually performed with TCAD tools. Numerical simulations provide accurate results for a single device but are not feasible when dealing with a full circuit comprising sever ...

SPIE-INT SOC OPTICAL ENGINEERING2020