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Publications associées (29)

Automatic and high-precision microseismic monitoring of progressive failure prior, during, and after tunnel excavation

Brice Tanguy Alphonse Lecampion, Seyyedmaalek Momeni, Christophe Nussbaum

Acoustic emission (AE) monitoring is commonly used to inspect the health of a structure continuously. During fracture processes elastic waves of AE are created and emitted, and sensors can capture these waves. The acquired signals can be processed to track ...

2023

Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

Brice Tanguy Alphonse Lecampion, Seyyedmaalek Momeni

Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by senso ...

DESTech publications inc.2023

Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...

SPRINGER2023

Overflow-free compute memories for edge AI acceleration

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

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

2023

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Aurélien François Gilbert Bloch

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

EPFL2023

Multicore fiber endoscope for phase imaging based on intensity recording using deep neural networks

Demetri Psaltis, Christophe Moser, Eirini Kakkava, Navid Borhani

The present invention is related to an endoscopic system for phase imaging, comprising a multicore waveguide (080), an optical system comprising at least one first light source (002), for illuminating the sample to be examined, a first camera (010) that is ...

2022

Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...

MDPI2022

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Mirjana Stojilovic, Dina Gamaleldin Ahmed Shawky Mahmoud

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

2022

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms by Dynamic Network Execution

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...

MDPI2022

Conjugate heat transfer in isolated granular clusters with interstitial fluid using lattice Boltzmann method

Mehrdad Kiani Oshtorjani

The conjugate heat transfer in mixtures of a fluid and single granular clusters is studied in this paper using a novel lattice Boltzmann method (LBM) programmed for parallel computation on the graphics processing unit (GPU). The LBM is validated for heat c ...

PERGAMON-ELSEVIER SCIENCE LTD2022

JPEG XS-A New Standard for Visually Lossless Low-Latency Lightweight Image Coding

Touradj Ebrahimi

Joint Photographic Experts Group (JPEG) XS is a new International Standard from the JPEG Committee (formally known as ISO/International Electrotechnical Commission (IEC) JTC1/SC29/WG1). It defines an interoperable, visually lossless low-latency lightweight ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

High-Speed ADC Design and Optimization for Wireline Links

Ayça Akkaya

The ever-growing global internet traffic has increased demand for higher speed data transmission. As the bandwidth requirements of wireline links increase, extensive digital equalization techniques are required to compensate for the high-frequency channel ...

EPFL2021

Operational Map And Thermal Performance Of A Thermosyphon Cooling System For Compact Servers

John Richard Thome, Jackson Braz Marcinichen, Raffaele Luca Amalfi, Filippo Cataldo

This paper advances the state-of-the-art in novel passive two-phase systems for more efficient cooling of datacenters and telecom central offices compared to the traditional air-based cooling solutions (e.g. aisle-based containment systems). The proposed p ...

AMER SOC MECHANICAL ENGINEERS2021

Biosensors for Bimolecular Computing: a Review and Future Perspectives

Sandro Carrara, Danilo Demarchi, Simone Aiassa

Biomolecular computing is the field of engineering where computation, storage, communication, and coding are obtained by exploiting interactions between biomolecules, especially DNA, RNA, and enzymes. They are a promising solution in a long-term vision, br ...

SPRINGER2020

Large field of view multi-camera endoscopic apparatus with omni-directional illumination

Yusuf Leblebici, Ömer Cogal

A multi-camera hemispherical very wide field of view imaging apparatus with omnidirectional illumination capability comprises a cylindrical body (4, 4.a, 4.b), a hemispherical mechanical frame (2) arranged on one end of the cylindrical body (4, 4.a, 4.b), ...

2020

MORPHIC: Programmable photonic circuits enabled by silicon photonic MEMS

Niels Quack, Alain Yuji Takabayashi, Hamed Sattari, Banafsheh Abasahl

In the European project MORPHIC we develop a platform for programmable silicon photonic circuits enabled by waveguide-integrated micro-electro-mechanical systems (MEMS). MEMS can add compact, and low-power phase shifters and couplers to an established sili ...

SPIE-INT SOC OPTICAL ENGINEERING2020

Synthesis of Flexible Accelerators for Early Adoption of Ring-LWE Post-quantum Cryptography

Francesco Regazzoni, Subhadeep Banik

The advent of the quantum computer makes current public-key infrastructure insecure. Cryptography community is addressing this problem by designing, efficiently implementing, and evaluating novel public-key algorithms capable of withstanding quantum comput ...

ASSOC COMPUTING MACHINERY2020

FPGAs in the Datacenters: the Case of Parallel Hybrid Super Scalar String Sample Sort

Paolo Ienne, Mikhail Asiatici

String sorting is an important part of database and MapReduce applications; however, it has not been studied as extensively as sorting of fixed-length keys. Handling variable-length keys in hardware is challenging and it is no surprise that no string sorte ...

IEEE COMPUTER SOC2020

Methods for strong gravitational lens detection and analysis using machine learning and high performance computing

Christoph Ernst René Schäfer

The study of strong gravitational lenses is a relatively new scientific field in astronomy with many applications in cosmology. Its unique observables allow astronomers to trace dark matter, determine the expansion of the universe and study galaxy evolutio ...

EPFL2020

Mixed-Precision Deep Learning Based on Computational Memory

Irem Boybat Kara, Abu Sebastian

Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...

FRONTIERS MEDIA SA2020