Multiprocessing

RMC fitting method runs sequentially by construction. Nevertheless, fullrmc computation blocks are multi-threaded and can make use of the full capacity of your machine. As distributed, fullrmc is compiled to run on single core (thread) only but advanced users have the option to compile the code with openmp. Reason why fullrmc is not distributed as multithreads enabled is because of the following reasons:

1. To avoid compilation errors because not all compilers and machine have openmp library installed and correctly linked (e.g. clang).
2. For small systems (maybe < 20000 atoms), running fullrmc on single core can be faster because threads run with some additional processing overhead time.

How to compile with openmp

To compile fullrmc with openmp it is very simple. You should pull Extensions directory from github and run the following.

python setup.py build_ext --inplace

If compiling with openmp fails, the script ensures recompiling without openmp just to make sure that you didn’t break your fullrmc installation (nothing guaranteed though). In worst case scenario, you can reinstall fullrmc using pip as the following

pip install --upgrade --no-deps --force-reinstall fullrmc

In setup.py you can set the compiler path in ‘COMPILER’ section. In section ‘COMPILER ARGUMENTS’ you should make sure extra arguments lists ‘EXTRA_COMPILE_ARGS’ and ‘EXTRA_LINK_ARGS’ are not commented and -fopenmp is appended to both, otherwise you won’t be compiling with openmp.

ATTENTION: This script is always up to date with the latest distributed version of fullrmc. Compiling with un-matching versions might lead to errors when running fullrmc.

Performance

Running fullrmc on multicores doesn’t mean that you will be dividing the whole fitting process time by some factor of the number of cores (threads) used. Also, using ncores will never result in occupying the ncores 100% because parallelization in fullrmc is an intercalation of multithreaded computation blocks with serial ones. For big systems, You will compute moves faster with no guarantee that those moves will be accepted. The speed of fitting is directly related to the ratio of accepted moves and not just how fast the moves are computed. fullrmc is an interactive fitting platform and the more you used it the more you understand that creating models requires some skills and some understanding of the system you are trying to model.