Ambition

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

**Improvement in the convergence rate (C**of the nonlinear iteration solver. C

_{r})_{r}is strongly dependent on the numerical algorithms being used in the solution of the non-linear system.

**Improvement in the time per iteration (Time**The Time

_{periteration})._{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 C**

_{r}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.