Parallel MPIPoolExecutor implementing the concurrent.futures interface
Project description
About
zwembad offers an MPIPoolExecutor class, an implementation of the
concurrent.futures.Executor class of the standard library.
Example usage
from zwembad import MPIPoolExecutor
from mpi4py import MPI
def menial_task(x):
return x ** MPI.COMM_WORLD.Get_rank()
with MPIPoolExecutor() as pool:
pool.workers_exit()
print("Only the master executes this code.")
# Submit some tasks to the pool
fs = [pool.submit(menial_task, i) for i in range(100)]
# Wait for all of the results and print them
print([f.result() for f in fs])
# A shorter notation to dispatch the same function with different args
# and to wait for all results is the `.map` method:
results = pool.map(menial_task, range(100))
print("All processes join again here.")
You'll see that some results will have exponentiated either by 1, 2, ..., n
depending on which worker they were sent to. It's also important to prevent your
workers from running the master code using the pool.workers_exit() call. As a
fail safe any attribute access on the pool object made from workers will
result in them exiting anyway.
The MPIPoolExecutor of zwembad is designed to function without MPI.Spawn()
for cases where this approach isn't feasible, like supercomputers where
MPI.Spawn is deliberatly not implemented (for example CrayMPI).
Therefor the pool can only use MPI processes that are spawned when the MPI world
is initialised and must be run from the command line using an MPI helper such as
mpirun, mpiexec or SLURM's srun:
$ mpirun -n 4 python example.py
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