I'm having an issue with my project. When I run the code of Monte-Carlo simulation, on the local server (the machine in my office) it runs on a rate of roughly 100000 steps per 24 hours. When I run it on the cluster the rate drops to about half of that or even less.
I am trying to figure this but I can't find any reason. I don't want you to read my code and analyze it mainly because this is not your work. I only ask for you experience for any suggestion. What I got so far is this:
- I don't to any parallel computing.
- When I run the code on the local machine, I don't usually run anything heavy aside from it.
- I do run, several copies of the code on the local machine but not more than the number of processor - 1 on that machine. The IT guys aren't sure, but they think that no dual processing are enabled on the local server. (There was an unsolved issue with that)
- When I run a single copy of the code on the cluster it runs okay.
- A significant drop of performance occur only when the number of copies is 8.
- There are two kinds of machines on the cluster. 16 nodes (8 dual processor) and 24 nodes (I think that those are 6 qudriple processors).
- The code is written in C++. Even though it is considered bad programming, all my variables are global and I access them directly (not via function).
- I compile the code using
icc -O3 -fast -ip. Removing any of those flag either reduced the performance or didn't have any noticeable affect.
I think, from all of this that this is an issue with memory management but I don't know how to test this.
I have several question about this:
- Did any of encountered something similar?
- How can I test if this is a memory issue?
- Is there another flag I could add to my compilation?
- Are there any tips for efficient memory usage in c++?
Thank you for any help