Parallel execution

It is highly recommended to run MDDF calculations in parallel, using multiple processors of a single computer. To run the computation in parallel, initialize julia with the -t N option, where N is the number of processes to be used. For example, to use 8 parallel processes, use:

julia -t 8 example.jl

The computation will use a number of parallel processes equal to N. Use -t auto to automatically pick the number of threads available in your computer.

Optimal number of threads

The number of threads used for computation of the MDDF is the number of threads available to Julia. Many computers allow hyperthreading, and not necessarily this this beneficial for the execution of this package. The optimal number of threads may vary. Some newer CPUs have "energy saving" cores, which are also relatively slow.

Independently of the number of threads initialized with the -t command-line parameter, the number of processes launched by ComplexMixtures in any given computation can be adjusted by the Options(nthreads=N) option. This won't provide any speedup if the optional number of threads is greater than the number of threads available to Julia at runtime.

Memory issues

If the calculations get Killed by no apparent reason, that is probably because you are running out of memory because of the many parallel computations running.

The main reason for memory exhaustion is the annotation of the contributions of each atom of the solute molecules to the total counts. By default, in a parallel run, one copy of such data structures is saved for each thread. This might be an issue if the solute is molecular structure with many hundreds of thousand atoms, and if the number of CPUs available is very high, but memory is not as abundant.

There are different ways to deal with this issue:

Use predefined groups, to reduce the size of the group array contributions.
Use the low_memory=true option the call to mddf (for example with mddf(traj, options; low_memory=true).
Reduce the number of threads used (with Options(nthreads=N)).
Increase the frequency of garbage collection calls:
```
options = Options(GC=true, GC_threshold=0.5)
R = mddf(trajectory, options)
```
The GC_threshold=0.5 indicates that if the free memory is smaller than 50% of the total memory of the machine, a garbage-collection run will occur. The default parameters are GC=true and GC_threshold=0.3.