I'm experimenting with Pin, an instrumentation tool, which I use to compute some statistics based on memory address of my variables. I want to re-run my program with the information gathered by my instrumentation tool, but for that it's crucial that virtual memory addresses remain the same through different runs.

In general, I should let the OS handle memory allocation, but in this case I need some kind of way to force it to always allocate to the same virtual address. In particular, I'm interested in a very long array, which I'm currently allocating with numa_alloc_onnode(), though I could use something else.

What would be the correct way to proceed?

Thanks

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解决方案

You could try mmap(2).

The instrumented version of your program will use a different memory layout than the original program because pin needs memory for the dynamic translation etc. and will change the memory layout. (if I recall correctly)

其他提示

With the exception of address space layout randomization, most memory allocators, loaders, and system routines for assigning virtual memory addresses will return the same results given the same calls and data (not by deliberate design for that but by natural consequence of how software works). So, you need to:

  • Disable address space layout randomization.
  • Ensure your program executes in the same way each time.

Address space layout randomization is deliberate changes to address space to foil attackers: If the addresses are changed in each program execution, it is more difficult for attacks to use various exploits to control the code that is executed. It should be disabled only temporarily and only for debugging purposes. This answer shows one method of doing that and links to more information, but the exact method may depend on the version of Linux you are using.

Your program may execute differently for a variety of reasons, such as using threads or using asynchronous signals or interprocess communication. It will be up to you to control that in your program.

Generally, memory allocation is not guaranteed to be reproducible. The results you get may be on an as-is basis.

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