Sample configuration files and geometry input files are provided with the binary to test the proper system setting
and see if the simulation starts correctly on the system.
nanoFluidX prep, shortened as nFX[p], is an auxiliary executable for nanoFluidX intended to eliminate a number of potential user errors during the pre-processing phase.
nanoFluidX companion, also known as nFX[c], is a post-processing tool developed to accompany the nanoFluidX solver allowing for an easier execution of certain post-processing tasks.
nanoFluidX monitor, known as nFX[m], is a single file portable Python executable that is aimed for helping with monitoring a nanoFluidX simulation during runtime.
Source set_nFX_environment.sh (*.csh)
from the nanoFluidX installation directory.
Note: This sets paths to the CUDA and MPI executables
packaged with nanoFluidX.
Navigate to the directory containing the nanoFluidX
case (*.cfg and *.prtl files).
Execute nvidia-smi.
If NVIDIA drivers are properly installed, this command will show the available
GPU devices are available. Figure 1.
The number of GPUs should be determined according to the number of
particles. Ensure there is at least 2M particles per GPU to scale efficiently.
To quickly count the number of lines (particles) inside the
.prtl file from the terminal, use the
wc
command:
wc EGBX_1mm.prtl -l
5673046 EGBX_1mm.prtl
Once you know which GPUs to use, enter the launch command string: