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Home/ Questions/Q 864055
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Editorial Team
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Editorial Team
Asked: May 15, 20262026-05-15T09:24:47+00:00 2026-05-15T09:24:47+00:00

So I’ve noticed that the default stack size for threads on linux is 8MB

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So I’ve noticed that the default stack size for threads on linux is 8MB (if I’m wrong, PLEASE correct me), and, incidentally, 1MB on Windows. This is quite bad for my application, as on a 4-core processor that means 64 MB is space is used JUST for threads! The worst part is, I’m never using more than 100kb of stack per thread (I abuse the heap a LOT ;)).

My solution right now is to limit the stack size of threads. However, I have no idea how to do this portably. Just for context, I’m using Boost.Thread for my threading needs. I’m okay with a little bit of #ifdef hell, but I’d like to know how to do it easily first.

Basically, I want something like this (where windows_* is linked on windows builds, and posix_* is linked under linux builds)

// windows_stack_limiter.c
int limit_stack_size()
{
    // Windows impl.
    return 0;
}

// posix_stack_limiter.c
int limit_stack_size()
{
    // Linux impl.
    return 0;
}

// stack_limiter.cpp
int limit_stack_size();
static volatile int placeholder = limit_stack_size();

How do I flesh out those functions? Or, alternatively, am I just doing this entirely wrong? Remember I have no control over the actual thread creation (no new params to CreateThread on Windows), as I’m using Boost.Thread.

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  1. Editorial Team
    Editorial Team
    2026-05-15T09:24:48+00:00Added an answer on May 15, 2026 at 9:24 am

    You do not need to do this. The machine’s physical memory is employed only where it is needed by a demand page fault system. Even if the thread stacks are significantly larger than the amount you are using the extra size is in virtual address space and does not tie up physical RAM.

    Had physical RAM been tied up at that rate, a typical machine would run out of memory with only a few dozen processes running. You can see from a ps -Al that quite a few more than that execute concurrently.

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