On 04/18/2018 07:16 PM, simona bellavista wrote: > I have a code fortran 90 that is parallelised with MPI. I would like to > traslate it in python, but I am not sure on the parallelisation strategy and > libraries. I work on clusters, with each node with 5GB memory and 12 > processors or 24 processors (depending on the cluster I am using). Ideally I > would like to split the computation on several nodes. > > Let me explain what this code does: It read ~100GB data, they are divided in > hdf5 files of ~25GB each. The code should read the data, go through it and > then select a fraction of the data, ~1GB and then some CPU intensive work on > it, and repeat this process many times, say 1000 times, then write the > results to a single final file. > > I was thinking that the CPU intensive part would be written as a shared > object in C. > > Do you have suggestions about which library to use?
Since your Fortran code already uses MPI, why not use MPI with Python as well? I know there are python bindings for MPI. That way you could use python while keeping the MPI workflow. -- https://mail.python.org/mailman/listinfo/python-list
