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Inria est un organisme public de recherche, dédié aux sciences et technologies du numérique.

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We introduce and study the computational power of Oritatami, a theoretical model to explore greedy molecular folding, by which the molecule begins to fold before waiting the end of its production. This model is inspired by our recent experimental work demonstrating the construction of shapes at the nanoscale by folding an ...
Cet exposé retrace brièvement l'historique de l'algorithmique répartie à travers l'un de ses problèmes les plus fondamentaux: la validation atomique.
Les systèmes distribués sont divers mais peuvent être classés en deux classes principales, ceux à communication par messages et ceux à mémoire partagée. Depuis ...
In this talk, I describe some of the work I have done with Michel (and others) over a very productive period that started 15 years ago, and hopefully will last for many more years, where we have published an average of two conference papers and one journal paper per year, and have met many ...
This talk discusss the most fundamental notion in distributed computing. I will present and prove a universal property for distributed computing, and discuss implications and applications.  
Cet exposé fait un tour d'horizon sur les détecteurs de défaillances, introduits par Chandra et Toueg en 1996.  Michel Raynal a largement participé aux recherches sur ce sujet.
Modern cryptocurrency systems, such as Ethereum, permit complex financial transactions through scripts called *smart contracts*. These smart contracts are executed many, many times, always without concurrency. First, smart contracts are serially executed before being recorded on the blockchain, and once recorded, they are serially re-executed whenever it is necessary to check that the blockchain is ...
This talk revisits the Bakery Algorithm I proposed in 1974 from the point of view of the tools that we now have at our disposal in 2015, notably the PlusCal Algorithm Language, and the TLA+ specification language
The current spreading of multi-scale and multi-process integrative simulations is challenging for the philosophy of science. What is the epistemic function of such a simulation? What does it really show? On what grounds? Is it an experimental design or a theoretical construction? To contribute to these debates, I suggest analyzing ...
Deep neural networks have achieved impressive experimental results in image classification, but can surprisingly be unstable with respect to adversarial perturbations, that is, minimal changes to the input image that cause the network to misclassify it. With potential applications including perception modules and end-to-end controllers for self-driving cars, this raises ...
 
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