---
myst:
    substitutions:
        sentence:
            python: "`TPythonEval`"
            cpp: "`TCJitEval`"
---
# `TBiMpiRun` and `TSubMpiRun`

In some case, users want to use multi level of parallelism. Two examples are given in the use cases 
section : first one is an optimization where each evaluation realizes an experiment design and 
launchs many evaluations and returns a overview of values (max, min, mean) ; second one uses an MPI 
function ({{sentence[language]}}) for evaluation.

For a two level MPI, two classes are provided : `TBiMpiRun` and `TSubMpiRun`. `TBiMpirun` is the 
high level class and splits MPI resources in different parts : one ressource for the `TMaster` and n 
resources for each `TEval`. `TSubMpiRun` gives acces to the n ressources reserved for evaluation. For 
example with 16 resources, 1 resource is reserved for the master and the rest can be splited in 3 
parts of 5 resources each for evaluation. `TBiMpiRun` got an extra parameter, an `int` defining the 
number of each evaluation resource. This number must be compatible with available resources (with 16 
resources, it could be only 3 or 5).