Concept

Problème des généraux byzantins

Publications associées (171)

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Leaderless Consensus

Rachid Guerraoui, Vincent Gramoli, Mihail Igor Zablotchi, Karolos Antoniadis, Antoine Philippe Matthieu Desjardins

Abstract—Classical synchronous consensus algorithms are leaderless: processes exchange their proposals, pick the max and decide when they see the same choice across a couple of rounds. Indulgent consensus algorithms are more robust in that they only req ...

2021

Learning from History for Byzantine Robust Optimization

Martin Jaggi, Lie He, Sai Praneeth Reddy Karimireddy

Byzantine robustness has received significant attention recently given its importance for distributed and federated learning. In spite of this, we identify severe flaws in existing algorithms even when the data across the participants is identically distri ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

Rachid Guerraoui, El Mahdi El Mhamdi, Sébastien Louis Alexandre Rouault

Byzantine-resilient Stochastic Gradient Descent (SGD) aims at shielding model training from Byzantine faults, be they ill-labeled training datapoints, exploited software/hardware vulnerabilities, or malicious worker nodes in a distributed setting. Two rece ...

2021

This paper considers the Byzantine fault-tolerance problem in distributed stochastic gradient descent (D-SGD) method - a popular algorithm for distributed multi-agent machine learning. In this problem, each agent samples data points independently from a ce ...

IEEE COMPUTER SOC2021

Asynchronous distributed coordination and consensus with threshold logical clocks

Bryan Alexander Ford

Consensus protocols for asynchronous networks are usually complex and inefficient, leading practical systems to rely on synchronous protocols. The invention proposes an approach to simplify asynchronous consensus by building it atop a novel threshold logic ...

2021

Diablo: A Distributed Analytical Blockchain Benchmark Framework Focusing on Real-World Workloads

Rachid Guerraoui, Vincent Gramoli

The plethora of blockchain proposals raises the question of selecting the ideal blockchain for a given decentralised application (DApp). Most blockchain performance evaluations are obtained through tailored environments under unknown experimental settings ...

2021

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Modern machine learning architectures distinguish servers and workers. Typically, a d-dimensional model is hosted by a server and trained by n workers, using a distributed stochastic gradient descent (SGD) optimization scheme. At each SGD step, the goal is ...

Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik2021

The Performance of Byzantine Fault Tolerant Blockchains

Vincent Gramoli

Blockchains have captured the attention of many, resulting in an abundance of new systems available for use. However, selecting an appropriate blockchain for an application is challenging due to the lack of comparative information discussing core metrics s ...

IEEE2020

Genuinely Distributed Byzantine Machine Learning

Rachid Guerraoui, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

Machine Learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...

Association for Computing Machinery2020

Mneme: A Mobile Distributed Ledger

Boi Faltings, Sujit Prakash Gujar, Dimitrios Chatzopoulos

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on device-to-device (D2D) ecosystems (e.g., crowdsensing). More sophisticated applications, like cryptocurrencies, need ...

IEEE2020