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Publications associées (27)

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

EPFL2024

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

David Atienza Alonso, Marina Zapater Sancho, Darong Huang, Luis Maria Costero Valero, Qunyou Liu

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

2024

Imprecise Store Exceptions

Babak Falsafi, Mathias Josef Payer, Siddharth Gupta, Yunho Oh, Yuanlong Li, Abhishek Bhattacharjee, Qingxuan Kang

Precise exceptions are a cornerstone of modern computing as they provide the abstraction of sequential instruction execution to programmers while accommodating microarchitectural optimizations. However, increasing compute capabilities in deep memory hierar ...

ACM2023

Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment

Florent Gérard Krzakala

Artificial Neural Networks (ANN) are habitually trained via the back-propagation (BP) algorithm. This approach has been extremely successful: Current models like GPT-3 have O(10 11 ) parameters, are trained on O(10 11 ) words and produce awe-inspiring resu ...

IEEE2023

Rebooting Virtual Memory with Midgard

Siddharth Gupta

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

EPFL2023

Maximum Radiation Efficiency of an Implantable Antenna: The Role of High-Order Modes

Anja Skrivervik, Mingxiang Gao

A combination of two numerical techniques of computational electromagnetics, namely, method of moments and vector spherical wave expansion, is used to show performance limitations on the radiation efficiency of implantable antennas and to efficiently resol ...

IEEE2023

Object-oriented modelling of advanced computer cooling solutions

David Atienza Alonso

Modern computing systems are so energy- intensive to make efficient cooling vital for their operation. This is giving rise to a variety of innovative cooling solutions based on a mix of traditional and new techniques. The design and engineering of these so ...

Elsevier2023

System Support for Robust Distributed Learning

Arsany Hany Abdelmessih Guirguis

Machine learning (ML) applications are ubiquitous. They run in different environments such as datacenters, the cloud, and even on edge devices. Despite where they run, distributing ML training seems the only way to attain scalable, high-quality learning. B ...

EPFL2022

The Universal Gossip Fighter

Rachid Guerraoui, Anne-Marie Kermarrec, Rafaël Benjamin Pinot, Anastasiia Kucherenko

The notion of adversary is a staple of distributed computing. An adversary typically models “hostile” assumptions about the underlying distributed environment, e.g., a network that can drop messages, an operating system that can delay processes or an attac ...

IEEE2022

Energy-Efficient Design Techniques for High-Speed Wireline Serial Links

Firat Çelik

The exponential growth in computing power and multimedia services has caused a tremendous increase in data traffic in recent years. This increase in data traffic brings a strong demand for data bandwidth of electrical input/output (I/O) links and pushes th ...

EPFL2021

A review of CUDA optimization techniques and tools for structured grid computing

Mohammad Khaja Nazeeruddin

Recent advances in GPUs opened a new opportunity in harnessing their computing power for general purpose computing. CUDA, an extension to C programming, is developed for programming NVIDIA GPUs. However, efficiently programming GPUs using CUDA is very tedi ...

2020

Distributed Computing with Modern Shared Memory

Mihail Igor Zablotchi

In this thesis, we revisit classic problems in shared-memory distributed computing through the lenses of (1) emerging hardware technologies and (2) changing requirements. Our contributions consist, on the one hand, in providing a better understanding of th ...

EPFL2020

Containergy-A Container-Based Energy and Performance Profiling Tool for Next Generation Workloads

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar

Run-time profiling of software applications is key to energy efficiency. Even the most optimized hardware combined to an optimally designed software may become inefficient if operated poorly. Moreover, the diversification of modern computing platforms and ...

2020

BLADE: A BitLine Accelerator for Devices on the Edge

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, William Andrew Simon, Yasir Mahmood Qureshi

The increasing ubiquity of edge devices in the consumer market, along with their ever more computationally expensive workloads, necessitate corresponding increases in computing power to support such workloads. In-memory computing is attractive in edge devi ...

2019

Non-intrusive reduced-order modeling for fluid problems: A brief review

Mengwu Guo

Despite tremendous progress seen in the computational fluid dynamics community for the past few decades, numerical tools are still too slow for the simulation of practical flow problems, consuming thousands or even millions of computational core-hours. To ...

SAGE PUBLICATIONS LTD2019

Asynchronous Simulation of Neuronal Activity

Bruno Ricardo Da Cunha Magalhães

Simulations of the electrical activity of networks of morphologically-detailed neuron models allow for a better understanding of the brain. Short time to solution is critical in order to study long biological processes such as synaptic plasticity and learn ...

EPFL2019

Essays on adaptation to rare disasters

Takafumi Usui

This thesis aims to further investigate rare natural disasters and studies adaptation decisions under uncertainty by solving several computational economic models. The modeling of rare natural disasters depends on the treatment of catastrophic outcomes wit ...

EPFL2019

Asynchronous Branch-Paralle Simulation of Detailed Neuron Models

Felix Schürmann

Simulations of electrical activity of networks of morphologically detailed neuron models allow for a better understanding of the brain. State-of-the-art simulations describe the dynamics of ionic currents and biochemical processes within branching topologi ...

2019

A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories

David Atienza Alonso, Pierre-Emmanuel Julien Marc Gaillardon, Marina Zapater Sancho, Xifan Tang, Yasir Mahmood Qureshi, Edouard Giacomin

The need for running complex Machine Learning (ML) algorithms, such as Convolutional Neural Networks (CNNs), in edge devices, which are highly constrained in terms of computing power and energy, makes it important to execute such applications efficiently. ...

2019

The Future of Electronics: Silicon to Cloud Technologies

Mihai Adrian Ionescu

We will present and discuss some of the great research challenges and opportunities related to 21st century energy efficient computing and sensing devices and systems, in the context of the Internet of Things (IoT) revolution. In the future, major innovati ...

IEEE2018