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3 … 2 … 1 … Go! We are launching the CExA Moonshot project 🚀🌗

CExA projects aims to develop and support the adoption of a Kokkos-based GPU model to Compute at Exascale At CEA and beyond.

Over the next two years, we will be intensively developing a Kokkos-based platform to enable our demonstrators to run on GPUs. Our platform will then be extended to serve all codes wishing to go Exascale. Find out more on the official website:

If you’d like to meet us, or even join the adventure, we’re organizing our open kick-off and registration is now open:

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[SEMINAR] May 30 2023 – DENERGIUM 🧑‍🏫 Hervé MATHIEU

🧑‍🏫 Hervé MATHIEU – cofunder of DENERGIUM
🌎 May 30 2023
☕️ 4:00 PM
🏢 Maison de la Simulation, Batiment Digiteo Saclay, Salle Mandelbrot


DENERGIUM est une startup créée début 2023. DENERGIUM est une entreprise technologique, un éditeur de logiciels et un acteur environnemental positif. DENERGIUM a pour mission de rendre plus efficace l’utilisation des infrastructures informatiques. Pour cela DENERGIUM s’appuie sur une technologie issue d’Inria, qui à partir de données énergétiques acquises dans un datacenter et d’algorithmes avancés (modèles mathématiques, IA) permet d’apporter des optimisations aux gestionnaires de datacenter mais aussi aux utilisateurs des datacenters. Notre marché est l’ensemble des infrastructures informatiques opérant du calcul massif (HPC, IA, BigData). DENERGIUM est accompagnée par Inria Startup Studio, Unitec et Ovhcloud startup program.

A partir d’une démonstration d’EnergyScopium optimize, nous pourrons échanger sur la problématique de l’optimisation énergétique dans l’usage des clusters de calcul : configuration matérielle et logicielle des serveurs, lancement des calculs, choix des bibliothèques logicielles, développement logiciel.

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[JOB] C++ expert engineer 👩‍💻🧑‍💻- Contribution to the development of the Kokkos GPU computing library within the CExA “Moonshot” project

Join the CEA’s ambitious “Moonshot” project, CExA, and contribute to the development of the Kokkos GPU computing library. We are recruiting six talented and enthusiastic C++ development engineers for a period of 2 years to work at our CEA Saclay site near Paris.

To apply, please send your application (resume and cover letter) to You can use this same address for any questions concerning the offer. Applications will be evaluated from mid-May until the position is filled.


Europe is investing to build exaflop supercomputers in the coming years, including one in France, at the CEA, in 2025. These machines will be heterogeneous, accelerated by GPUs of various brands and architectures. Ensuring performance and portability under these conditions is certainly one of the greatest challenges of the Exascale. To address it, CEA is investing heavily in an ambitious “Moonshot” project: CExA. In this project, we will setup libraries to fully exploit this computing power in the scientific applications of the CEA by contributing, extending and adapting the open-source library Kokkos. Within CExA, we represent teams with expertise in numerical computation from the four components of the CEA.

  • Maison de la Simulation of the DRF is a joint research and engineering laboratory of CEA, CNRS, Univ. Paris-Saclay and UVSQ specialized in high performance computing and numerical simulation.
  • The DES’s software engineering department for simulation brings together three laboratories that address the issues of simulation environment, AI and data science, high performance computing and numerical analysis.
  • The DSCIN at DRT/LIST is responsible for the research and development of digital integrated circuits and processors for AI, as well as the design of complex digital architectures. It also works on solutions for embedded systems and develops design tools for embedded AI, embedded systems and trusted circuits.
  • The DSSI of the DAM manages activities in the fields of computer science, applied mathematics and information systems, covering a wide spectrum from definition and design to user services.


As part of a new agile team being set up to carry out the CExA project, you will work in collaboration with the European HPC ecosystem and the teams in charge of the development of Kokkos in the United States (Sandia and Oakridge National labs). You will enrich the library to fit the needs of the CEA applications and to the technologies developed by Europe for the Exascale (EPI, SiPearl, RISC-V)

Your mission will include:

  • Agile development in C++ of the CExA middleware to address the following areas of improvement:
    • Adaptation to “distributed memory” architectures
    • Support for heterogeneous architectures for European exaflop supercomputers
    • Interfacing with external libraries and data processing tools
    • Simplification of deployment
  • Porting via Kokkos and integration of new functionalities in selected application demonstrators (hydrodynamics, fusion energy, AI-assisted medicine)
  • Support and animation on parallel programming models within the laboratory and at the scale of European and global collaborations.


You have a master and/or an engineering degree in computer science and:

  • You have a solid knowledge of advanced C++ and the latest standards.
  • You know how to fit into an agile development process (SCRUM) and you master the basic tools associated with collaborative development (git, github, etc.).
  • You have skills in software engineering. You are familiar with common development environments and associated tools (cmake, docker, spack, gtest, ctest, etc.).
  • Knowledge of parallel programming (GPU, multi-threaded, etc.) is a plus, especially with the Kokkos library or equivalent.
  • You are autonomous and you wish to be part of an international work team. You master technical English (written and oral). You are interested in the world of high-performance computing and its challenges and follow the evolution of technologies.

Salary and benefits

The CEA offers salaries based on your degrees and experience.

This position offers several advantages:

  • the possibility to join collaborations with other European laboratories, the United States and Japan,
  • Numerous opportunities to travel internationally (exchanges, conferences, workshops and more)
  • Up to 3 days of telecommuting per week
  • Reimbursement of up to 75% of public transport cards and a free transport network throughout the Ile-de-France region,
  • An interesting complementary health insurance and several company savings plans,
  • 5 weeks of paid vacation and 4 weeks of RTT per year.
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[SEMINAR] May 16 2023 – Development and GPU porting efforts for a high-performance low-Mach CFD solver based on unstructured adaptive grids 🧑‍🏫 Patrick BEGOU and Vincent MOUREAU

🧑‍🏫 Patrick BEGOU – Research Engineer at LEGI, UMR 5519
🧑‍🏫 Vincent MOUREAU, CNRS research fellow at CORIA, UMR6614
🌎 May 16 2023
☕️ 9:30 AM
🏢 Maison de la Simulation, Batiment Digiteo Saclay, Salle Mandelbrot


With the steady increase of the power of parallel super-computers, 3D unsteady simulations offer a great potential to study turbulent flows. However, the simulation of highly non-linear phenomena such as turbulence, primary atomization or premixed flames requires very accurate numerical methods and high resolution to capture vortex and interface dynamics. While most direct numerical simulations of turbulent flows are carried out with structured grids or Cartesian-based Adaptive Mesh Refinement, recent advances in numerical methods for tetrahedron-based meshes and parallel mesh adaptation strategies raise the attractiveness of unstructured grids. The use of tetrahedra has two advantages for practical configurations: complex geometries are easily meshed and the mesh is locally more isotropic than Cartesian grids. The first part of the presentation will be focused on the development of highly-efficient dynamic adaptation of tetrahedron-based unstructured grids and on projection methods for low-Mach number flows which can cope with adaptive grids. The proposed methodology, which heavily relies on the remeshing library MMG ( has been thoroughly optimized to reach good performances with grids of several billion cells on more than 10 000 cores. This dynamic mesh adaptation strategy has been implemented in the YALES2 code ( and applied to the modeling of turbulent flows in many configurations. In these academic and industrial applications, the local mesh adaptation enabled a drastic reduction of the CPU cost compared to the fixed-grid approach and enabled to reach unprecedented mesh resolutions. The second part of the presentation will be dedicated to the efforts to port these methodologies to GPUs while continuing promoting fast development and innovation from a community of non-GPU experts.

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[SEMINAR] April 18 2023 – Quantum computers: What are they? What are they supposed to be good at? Will they work? 🧑‍🏫 by Xavier Waintal 

🧑‍🏫 Xavier Waintal, CEA Grenoble, PHELIQS
🌎 April 18 2023
☕️ 9:30 AM
🏢 Maison de la Simulation, Batiment Digiteo Saclay, Salle Mandelbrot


In the last three decades, our ability to build and control quantum states has improved dramatically and could become the basis of a new form of numerical calculation. While these machines are still in their infancy  (no existing quantum computer can multiply 5 by 3), the hope is that for a very specific class of problem, they could be exponentially faster than their classical counterpart. In this talk, I will give an introduction to quantum computing from the point of view of a physicist. In particular I will emphasize how the main quantum computing ressource, entanglement, is also its biggest problem, decoherence.

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[SEMINAR] March 2023 – Data-driven modelling of hypersonic flows in non-equilibrium 👩‍🏫 Taraneh Sayadi

👩‍🏫 Taraneh Sayadi – d’Alembert, Sorbonne University ITV, RWTH-Aachen University
🌎 March 9 2023


At very large Mach numbers, fluid flows are strongly influenced by non-equilibrium gas effects such as finite-rate chemical reactions or internal mode excitation arising from extreme temperatures. These effects have an order-one influence on quantities of interest, such as stability properties, transition and heating and must be taken into account to achieve effective designs, reliable predictions, and successful flow control.  Accurate simulations of these flows rely on detailed thermochemical gas models (look-up libraries), which dramatically increase the cost of the underlying calculations. In this talk I will first present state-of-the-art detailed simulations of such complex flows and the incurring cost, motivating the second part of the talk where I will present a novel model-agnostic data-driven technique to extract a surrogate of the thermochemical models, reducing the cost of the simulations considerably while maintaining accuracy. 


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[SEMINAR] January 2023 – Simulations numériques ab initio de l’irradiation ionisante de la matière 🧑‍🏫 Auréllien de la Lande

🧑‍🏫 Aurélien de la Lande, CNRS
🌎 January 25 2023

Nous avons développé à l’Institut de Chimie Physique d’Orsay des approches de simulation ab initio originales pour simuler le dépôt d’énergie par des ions rapides ou des photons XUV dans des systèmes moléculaires de grandes tailles, tels que ceux rencontrés en biologie1. Durant ce séminaire, nous intro- duirons les équations du mouvement des électrons dans le cadre de la théorie de la fonctionnelle de la densité2. 

Nos codes de simulation reposent sur de nouveaux algorithmes de la théorie de la fonctionnelle de la densité dépendant du temps permettant de simuler des systèmes de taille nanométrique et inhomo- gènes3,4. L’une des astuces principales est de recourir à des densités électroniques auxiliaires permettant de calculer la répulsion coulombienne et les effets liés à la nature quantique des électrons (échange et corrélation). Le couplage avec la librairie ScaLapack permet une réduction importante du cout de calcul du propagateur3. Pour aller plus loin une interface avec la libraire Magma a récemment été réalisée. La réduction du coût de calcul est remarquable et permet d’entrevoir des applications sans précédent en terme de taille de systèmes simulés. 

J’illustrerai l’apport de ces approches par diverses études récentes du groupe. Un premier exemple a trait à l’irradiation comparée d’oligomères d’ADN solvatés par des protons, de noyaux d’hélium ou de carbone (Fig. 1)5. L’étude a permis de mettre en évidence des processus clés de l’étape physique de l’irradiation ; par exemple le mécanisme d’ionisation par flux-et-reflux du nuage électronique, la localisation des électrons secondaires ou encore les probabilités d’ionisation des bases d’ADN ou du solvant5. Dans un second exemple je mettrai en évidence un effet de taille remarquable lors le processus d’ionisation d’acide aminés, de peptides et de protéines par des photons ionisant XUV. Cette découverte permet de faire des hypothèses sur les sites d’ionisation primaires possibles du milieu cellulaire par ce type de rayonnement. 

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[SEMINAR] January 2023 – Vers une accélération de la mise à l’équilibre des modèles de climat 👩‍🏫 by Julie DESHAYES

👩‍🏫 Julie Deshayes, CNRS
🌎 January 2023


La modélisation du climat terrestre est incontournable pour planifier l’adaptation et la mitigation du changement climatique. La réalisation de scénarios du climat futur a un coût numérique conséquent, même à basse résolution spatiale (de l’ordre de 1°). L’essentiel de la consommation en calcul et stockage est consacrée à la mise à l’équilibre du modèle (en particulier sa composante océanique) et à la calibration des paramètres. En collaboration avec Martial Mancip, et grâce au soutien du programme PNRIA du CNRS, nous avons commencé à élaborer une solution, basée sur des méthodes innovantes (statistiques avancées et issues de l’intelligence artificielle), pour accélérer la mise à l’équilibre de l’océan du modèle de climat de l’IPSL. L’idée est de disposer d’un modèle d’inférence qui extrapole une série de pas de temps de simulation (en mois/années), puis réinjecte la solution extrapolée dans le modèle climatique pour effectuer de nouvelles étapes de simulation. Ces deux étapes seraient répétées autant de fois que nécessaire pour obtenir un algorithme stable qui converge vers une solution physiquement admissible comparable aux équilibres complets, tout en réduisant considérablement le nombre de pas de temps calculés explicitement avec le modèle. La réduction du temps de calcul explicite par le modèle climatique (opéré sous CPU), qui est plus coûteux que l’inférence par les techniques de Data Science (réalisée sous GPU), conduit à une amélioration de la frugalité du calcul numérique de la modélisation climatique.

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[SEMINAR] March 2020 – Two-level Coarse Corrected Optimized Schwarz Methods using PETSc 🧑‍🏫 Serge Van Criekingen

🧑‍🏫 Serge Van Criekingen, IDRIS, France
🌎 March 2020


Parallel Schwarz-type domain decomposition methods are based on an iterative process where, at each iteration, a local solve is simultaneously performed on each of the (possibly overlapping) subdomains, using interface values previously computed on neighboring subdomains. The reference method in this framework is the Restricted Additive Schwarz (RAS) method, implemented as a preconditioner in the PETSc library. Using existing PETSc tools, we here implement two improvements to this method: a new coarse correction to obtain a two-level scalable method, as well as optimized transmission conditions, resulting in an Optimized 2-level Restricted Additive Schwarz method.

The first improvement, namely the introduction of a coarse correction to insure scalability, is wellknown and due to that fact that, in the case of elliptic problems, information is only transferred from each subdomain to its direct neighbors at each iteration of a 1-level method such as RAS. This makes the number of iterations grow with the number of subdomains. Scalability is achieved by introducing a coarse grid on which a reduced-size calculation is performed, yielding a coarse correction at each iteration of the solution process. Such a 2-level method permits global propagation of the iterative corrections throughout the entire domain, leading to the scalability of the method. Many choices for the coarse grid point locations are possible, and we here follow a method introduced by M.J. Gander et al. yielding a reduced number of iterations.

The second improvement, namely optimized transmission conditions, stems from the idea that the transmission conditions used in the iterative process at subdomain interfaces can also be chosen such as to reduce the number of iterations. In our case, we consider Robin transmission conditions instead of the classical Dirichlet ones, i.e. a well-chosen combination of Dirichlet and Neumann values at subdomain interfaces. A good choice of the Robin coefficient representing the relative weight of Dirichlet and Neumann values permits minimizing the number of iterations, which led to the name Optimized Schwarz Methods.

We combine these two improvements and apply them to a 2D Laplace test case up to 16,384 CPU cores. We obtain substantially improved computation times, comparable to the ones obtained with the multigrid library HYPRE interfaced by PETSc. This is significant in that Schwarz-type domain decomposition methods were up to now not considered competitive with multigrid methods on this type of problem. Furthermore, we extend the method to non-symmetric problems, adding an advection term to the Laplacian, and investigate various ways of adapting the coarse space.

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[SEMINAR] March 2019 – Emulating quantum computers 🧑‍🏫 Victor Alessandrini

🧑‍🏫 Victor Alessandrini, Maison de la Simulation, France
🌎 March 2019


There is today increasing consensus on the fact that quantum computing – an emerging data processing technology – may in the future play a significant role (with not yet fully understood boundaries) in high performance scientific computing. The simulation of quantum computers on standard computing platforms is today a necessary step to understand, assess, and develop quantum algorithms for computation, paving the way for the eventual future adoption of this disruptive technology. Emulation software will remain useful for some time to validate results of the earlier quantum computing platforms, and to help tuning application quantum codes. We will present a fully portable C++ emulation library under development for more than one year. The library disposes of three interfaces: a shared memory version running on SMP nodes, a MPI extension enabling access to a larger number of qubits, and a Python wrapper of the C++ library. A significant pedagogical effort is implemented in the documentation. Besides the traditional C++ class documentation, we are producing strategic higher level documentation and pedagogical papers on applications, including Jupyter notebooks. This seminar will propose first an introduction to quantum computing, explaining the fundamental differences with classical computing, underlining the strong features as well as the limiting bottlenecks of the technology. We will present next a short and very high level overview of the emulation library, focusing on a few major strategic choices. Then, the issues involved in quantum algorithms will be illustrated with a quantum chemistry example used in the validation tests of the software. Finally, we will conclude with a rapid overview of different areas in which quantum algorithm research is evolving (quantum chemistry, condensed matter physics, combinatorial optimization, fault tolerant quantum computing,…).