Adaptive sampling for performance characterization of application kernels. - Pablo de Oliveira Castro; Eric Petit 002; Asma Farjallah; William Jalby (Concurr. Comput. Pract. Exp., 2013)

Preparing depth imaging applications for Exascale challenges and impacts. (Etude de l'adéquation des machines Exascale pour les algorithmes implémentant la méthode du Reverse Time Migation). - Asma Farjallah (2014)

Adaptive SIMD optimizations in particle-in-cell codes with fine-grain particle sorting. - Arnaud Beck; Julien Derouillat; Mathieu Lobet; Asma Farjallah; Francesco Massimo; Imene Zemzemi; Frédéric Pérez; Tommaso Vinci; Mickael Grech (Comput. Phys. Commun., 2019)

LIPS - Learning Industrial Physical Simulation benchmark suite. - Milad Leyli-Abadi; Antoine Marot; Jérôme Picault; David Danan; Mouadh Yagoubi; Benjamin Donnot; Seif Attoui; Pavel Dimitrov; Asma Farjallah; Clement Etienam (NeurIPS, 2022)

ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design). - Mouadh Yagoubi; Milad Leyli-Abadi; David Danan; Jean-Patrick Brunet; Jocelyn Ahmed Mazari; Florent Bonnet; Asma Farjallah; Marc Schoenauer; Patrick Gallinari (CoRR, 2024)

NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design. - Mouadh Yagoubi; David Danan; Milad Leyli-Abadi; Jean-Patrick Brunet; Jocelyn Ahmed Mazari; Florent Bonnet; Maroua Gmati; Asma Farjallah; Paola Cinnella; Patrick Gallinari; Marc Schoenauer (CoRR, 2024)