How can I parallelize my C++ code to utilize multiple cores?

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In summary, the speaker is seeking advice on how to parallelize their existing program on a quad-core machine. They are not familiar with parallel coding and would appreciate any recommended references or books. The difficulty of parallelizing code depends on the algorithm being used, with some being easier to parallelize than others. The speaker also offers an example of a multi-threaded program for copying files as a potential reference.
  • #1
Niles
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Hi

I have written an extensive simulation in C++ and when I run it on my quad-core machine, only a single core is used (on Windows). This is because my code is not parallelized.

I'm not familiar in any way with code running in parallel, except in Matlab where is happens almost automatically. Will it be an extensive procedure to parallelize my existing program?

If anyone has any references/book titles/etc.. that they can recommend, I would be grateful.


Niles.
 
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  • #2
parallelizing code can be easy or difficult. It depends on the algorithm you're developing.

As an example, fractal generation can be easily parallelized because its a localized computation on one point that doesn't depend on nearby point values. But something like a heat flow is more difficult because now you must use nearby cells to determine the value in the current. This means one cpu has to wait until another has completed a calculation for a neighboring cells.

Anyway wikipedia has an article that talks about it briefly:

http://en.wikipedia.org/wiki/Parallelization
 
  • #3
Assuming this is windows, you need to create threads to utilize multiple cores. There's some overhead in creating the threads and also to create the synchronization variables (mutex and/or semaphore).

I created an example multi-threaded dos console program that copies a file, using the starting thread to read a file and a created thread to write the file. I created a linked list fifo messaging system for thread communication and synchronization that uses mutex and semaphores. You probably won't need a messaging interface, but that part of the code is not complex. Link to zip of example code:

http://rcgldr.net/misc/mtcopy.zip
 
Last edited:

1. How can I parallelize my C++ code?

Parallelizing C++ code involves breaking down a sequential program into smaller tasks that can be executed simultaneously on multiple processors or cores. This can be achieved through various techniques such as using multithreading, OpenMP, or MPI libraries.

2. Will parallelizing my code automatically make it faster?

No, parallelizing code does not guarantee faster execution. It depends on the nature of the program and how well it can be divided into smaller tasks. In some cases, parallelizing code may even result in slower execution due to overhead costs.

3. How do I know if my code is suitable for parallelization?

Not all code can be parallelized effectively. It depends on the level of dependency between different tasks and the amount of data sharing between them. A thorough analysis of the code and its logic is necessary to determine its suitability for parallelization.

4. Can I parallelize any part of my code?

Yes, it is possible to parallelize different parts of a code. However, it is important to identify the most time-consuming and computationally intensive parts of the code to focus on parallelizing those sections for maximum performance gain.

5. Are there any potential drawbacks to parallelizing code?

Parallelizing code can introduce potential issues such as race conditions, deadlocks, and increased memory usage. It also requires additional effort for debugging and maintaining the code. Therefore, it is important to carefully consider the trade-offs before parallelizing code.

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