In order to achieve the objectives, the methodology described above addresses three main lines of action:

  • Improvement in the convergence rate (Cr) of the nonlinear iteration solver. Cr is strongly dependent on the numerical algorithms being used in the solution of the non-linear system.
  • Improvement in the time per iteration (Time periteration). The Time periteration is strongly dependent on the parallelization and the performance of the hardware.
    • Reducing the energy consumed by the simulation by at least an order of magnitude through the optimal use of low-level HW resources (accelerators), minimization of the data movement and optimal load distribution between compute devices.
    The first quantifiable objective of NextSim is to improve the convergence rate Cr to a maximum of a realistic 0.95 for complex geometries.

    The second quantifiable objective of NextSim is to divide   Time per iteration of current simulations by a factor of F=50x, considering a configuration with the same number of cores than before but in an advanced processing architecture (many-core, GP-GP) framework.

    Four complementary points of views will be checked in NextSim:

    • Efficiency. This is the main objective. For a given problem (mesh) the computational time will be reduced.
    • Insight. Higher and more complex meshes will provide better insight into the physics of the problems and the solution can be obtained in the same computational time as before.
    • Accuracy. Extreme scaling implies variable, unstable, non-guaranteed, dynamic resources and this will introduce system noise. The effects will be quantified, introducing a “simulation error bar” concept to assess the reliability of the whole process.
    • Reliability and robustness. Necessary for the final deployment of this technology at industrial level. It is necessary to trust on the obtained solution and it is necessary a small sensitivity under external perturbation or modifications of the flow management and parameters.

    Contact Us


    This project has received funding from the European High-Performance Computing Joint Undertaking Joint Undertaking (JU) under grant agreement No 956104. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, France, Germany.