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Diffstat (limited to 'Docs/source/running_cpp/parallelization.rst')
| -rw-r--r-- | Docs/source/running_cpp/parallelization.rst | 24 |
1 files changed, 5 insertions, 19 deletions
diff --git a/Docs/source/running_cpp/parallelization.rst b/Docs/source/running_cpp/parallelization.rst index 440c17235..a8c89f340 100644 --- a/Docs/source/running_cpp/parallelization.rst +++ b/Docs/source/running_cpp/parallelization.rst @@ -61,22 +61,8 @@ and MPI decomposition and computer architecture used for the run: * Amount of high-bandwidth memory. -Below is a list of experience-based parameters -that were observed to give good performance on given supercomputers. - -Rule of thumb for 3D runs on NERSC Cori KNL -------------------------------------------- - -For a 3D simulation with a few (1-4) particles per cell using FDTD Maxwell -solver on Cori KNL for a well load-balanced problem (in our case laser -wakefield acceleration simulation in a boosted frame in the quasi-linear -regime), the following set of parameters provided good performance: - -* ``amr.max_grid_size=64`` and ``amr.blocking_factor=64`` so that the size of - each grid is fixed to ``64**3`` (we are not using load-balancing here). - -* **8 MPI ranks per KNL node**, with ``OMP_NUM_THREADS=8`` (that is 64 threads - per KNL node, i.e. 1 thread per physical core, and 4 cores left to the - system). - -* **2 grids per MPI**, *i.e.*, 16 grids per KNL node. +Because these parameters put additional contraints on the domain size for a +simulation, it can be cumbersome to calculate the number of cells and the +physical size of the computational domain for a given resolution. This +:download:`Python script<../../../Tools/compute_domain.py>` does it +automatically. |