Implements ServerClient class, which maps the server-client communication model onto MPI. Perfect for running embarrassingly parallel jobs on supercomputers with many nodes. Implements load balancing: clients request more work from server and also signal when they wish to return their results. Server distributes the work list based on client availability, until empty. Instantiated clients are reusable, i.e. other tasks can be worked on collaboratively after completion of a task. This showcase includes a minimal.py example (please read the docstring there). Requires mpi4py and, obviously, an MPI installation.
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signalflow_serverclient.png shows the flow of signals and data between
root (Server) to worker ranks (Clients). Only one rank i is shown, all
other ranks communicate in an identical fashion, and simultaneously,
with root. Solid arrows show the advancement of the program execution,
dashed arrows indicate communication between root and ranks (the
sending of signals and of data).
minimal.py is a trivial example of how to use the ServerClient class. Run:
python minimal.py --help
for more info.