Improve MPI program

I wrote a MPI program that seems to run ok, but I wonder about performance. Master thread needs to do 10 or more times MPI_Send, and the worker receives data 10 or more times and sends it. I wonder if it gives a performance penalty and whether I could transfer everything in single structs or which other technique could I benefit from.

Other general question, once a mpi program works more or less, what are t开发者_StackOverflow社区he best optimization techniques.

It's usually the case that sending 1 large message is faster than sending 10 small messages. The time cost of sending a message is well modelled by considering a latency (how long it would take to send an empty message, which is non-zero because of the overhead of function calls, network latency, etc) and a bandwidth (how much longer it takes to send an extra byte given that the network communications has already started). By bundling up messages into one message, you only incurr the latency cost once, and this is often a win (although it's always possible to come up with cases where it isn't). The best way to know for any particular code is simply to try. Note that MPI datatypes allow you very powerful ways to describe the layout of your data in memory so that you can take it almost directly from memory to the network without having to do an intermediate copy into some buffer (so-called "marshalling" of the data).

As to more general optimization questions about MPI -- without knowing more, all we can do is give you advice which is so general as to not be very useful. Minimize the amount of communications which need to be done; wherever possible, use built-in MPI tools (collectives, etc) rather than implementing your own.

One way to fully understand the performance of your MPI application is to run it within the SimGrid platform simulator. The tooling and models provided are sufficient to get realistic timing predictions of mid-range applications (like, a few dozen thousands lines of C or Fortran), and it can be associated to adapted visualization tools that can help you fully understand what is going on in your application, and the actual performance tradeoffs that you have to consider.

For a demo, please refer to this screencast: https://www.youtube.com/watch?v=NOxFOR_t3xI