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Publications associées (28)

GLeeFuzz: FuzzingWebGL Through Error Message Guided Mutation

Mathias Josef Payer

WebGL is a set of standardized JavaScript APIs for GPU accelerated graphics. Security of the WebGL interface is paramount because it exposes remote and unsandboxed access to the underlying graphics stack (including the native GL libraries and GPU drivers) ...

Usenix Assoc2023

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

Perceptual Quality of Point Clouds with application to Compression

Evangelos Alexiou

Modern information technologies and human-centric communication systems employ advanced content representations for richer portrayals of the real world. The newly adopted imaging modalities offer additional information cues and permit the depiction of real ...

EPFL2021

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

Edoardo Charbon, Claudio Bruschini, Ivan Michel Antolovic

Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...

SPIE2021

High Performance Computing for gravitational lens modeling: Single vs double precision on GPUs and CPUs

Jean-Paul Richard Kneib, Markus Rexroth, Christoph Ernst René Schäfer

Strong gravitational lensing is a powerful probe of cosmology and the dark matter distribution. Efficient lensing software is already a necessity to fully use its potential and the performance demands will only increase with the upcoming generation of tele ...

ELSEVIER2020

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

Nanometric axial resolution of fibronectin assembly units achieved with an efficient reconstruction approach for multi-angle-TIRF microscopy

Emmanuel Emilien Louis Soubies, Sébastien Schaub

High resolution imaging of molecules at the cell-substrate interface is required for understanding key biological processes. Here we propose a complete pipeline for multi-angle total internal reflection fluorescence microscopy (MA-TIRF) going from instrume ...

Nature Research2019

GPU-Accelerated Finite Volume Particle Simulation of Free Jet Deviation by Multi-jet Rotating Pelton Runner

Siamak Alimirzazadeh

Numerical simulation of Pelton turbine hydrodynamics is helpful to identify the energy loss mechanisms in the runner and minimize their effect. However, it is a challenging task that involves handling the unsteady free surface flow and moving boundaries re ...

EPFL2019

Redefining energy system flexibility for distributed energy system design

Jean-Louis Scartezzini, Amarasinghage Tharindu Dasun Perera, Vahid Moussavi Nik

A novel method is introduced in this study to consider flexibility taking into account both system design and operation strategy by using fuzzy logic. A stochastic optimization algorithm is introduced to optimize the system design and operation strategy of ...

2019

Recurrent U-Net for Resource-Constrained Segmentation

Pascal Fua, Mathieu Salzmann, Wei Wang, Kaicheng Yu, Joachim Ludovic Hugonot

State-of-the-art segmentation methods rely on very deep networks that are not always easy to train without very large training datasets and tend to be relatively slow to run on standard GPUs. In this paper, we introduce a novel recurrent U-Net architecture ...

IEEE COMPUTER SOC2019

A method for voxel ray-casting of scenes on a whole screen

Robin Mange

A method for screen-space voxel ray-casting of scenes on a whole screen. The method comprises providing a graphics card; rendering seamlessly any one of the following list of primitives containing at least polygons, voxels; using a GPU pipeline of the grap ...

2019

Milkomeda: Safeguarding the Mobile GPU Interface Using WebGL Security Checks

Mathias Josef Payer

GPU-accelerated graphics is commonly used in mobile applications. Unfortunately, the graphics interface exposes a large amount of potentially vulnerable kernel code (i.e., the GPU device driver) to untrusted applications. This broad attack surface has resu ...

ASSOC COMPUTING MACHINERY2018

Holographic Visualisation and Interaction of Fused CT, PET and MRI Volumetric Medical Imaging Data Using Dedicated Remote GPGPU Ray Casting

Patric Hagmann, Stéphane Gobron, Adrien Raphaël Depeursinge

Medical experts commonly use imaging including Computed Tomography (CT), Positron-Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) for diagnosis or to plan a surgery. These scans give a highly detailed representation of the patient anatomy, b ...

SPRINGER INTERNATIONAL PUBLISHING AG2018

Distributed Learning of CNNs on Heterogeneous CPU/GPU Architectures

José Pedro Rebelo Ferreira Marques, Gabriel Falcao Paiva Fernandes, Alexandre Luisier

The convolutional neural networks (CNNs) have proven to be powerful classification tools in tasks that range from check reading to medical diagnosis, reaching close to human perception, and in some cases surpassing it. However, the problems to solve are be ...

TAYLOR & FRANCIS INC2018

LTRF: Enabling High-Capacity Register Files for GPUs via Hardware/Software Cooperative Register Prefetching

Babak Falsafi, Mario Paulo Drumond Lages De Oliveira, Hamid Sarbazi-Azad

Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bottleneck for future GPUs due to long access latency, high power consumption, ...

2018

Advanced gravitational lensing techniques for precision cosmology

Markus Rexroth

Gravitational lensing - the deflection of light by gravity - has greatly developed since its famous first observation in 1919, which validated Einstein's General Theory of Relativity. The strength of this effect does not depend on the nature of the mass wh ...

EPFL2018

A GPU-Friendly Skiplist Algorithm

Nachshon Cohen

We propose a design for a fine-grained lock-based skiplist optimized for Graphics Processing Units (GPUs). While GPUs are often used to accelerate streaming parallel computations, it remains a significant challenge to efficiently offload concurrent computa ...

Ieee2017

Fast Segmentation from Blurred Data in 3D Fluorescence Microscopy

Michaël Unser, Martin Kurt Storath

We develop a fast algorithm for segmenting 3D images from linear measurements based on the Potts model (or piecewise constant Mumford-Shah model). To that end, we first derive suitable space discretizations of the 3D Potts model, which are capable of deali ...

2017

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

Theo Lasser, Daniel Pawel Szlag, Paul James Marchand, Marcin Antoni Sylwestrzak

We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for m ...

Elsevier2017