MPI Task Scheduling

Question

I want to develop a task scheduler using MPI where there is a single master processor and there are worker/client processors. Each worker has all the data it needs to compute, but gets the index to work on from the master. After the computation the worker returns some data to the master. The problem is that some processes will be fast and some will be slow. If I run a loop so that at each iteration the master sends and receives (blocking/non-blocking) data then it can't proceed to next step till it has received data from the current worker from the previous index assigned to it. The bottom line is if a worker takes too long to compute then it becomes the limiting factor and the master can't move on to assign an index to the next worker even if non-blocking techniques are used. Is it possible to skip assigning to a worker and move on to next.

I'm beginning to think that MPI might not be the paradigm to do this. Would python be a nice platform to do task scheduling?

Answer 1

This is absolutely possible using MPI_Irecv() and MPI_Test(). All the master process needs to do is post a non-blocking receive for each worker process, then in a loop test each one for incoming data. If a process is done, send it a new index, post a new non-blocking receive for it, and continue.