Comment by pjc50

10 hours ago

https://learn.microsoft.com/en-us/sysinternals/downloads/vmm... for an empty sublime text window gives me:

- 100MB 'image' (ie executable code; the executable itself plus all the OS libraries loaded.)

- 40MB heap

- 50MB "mapped file", mostly fonts opened with mmap() or the windows equivalent

- 45MB stack (each thread gets 2MB)

- 40MB "shareable" (no idea)

- 5MB "unusable" (appears to be address space that's not usable because of fragmentation, not actual RAM)

Generally if something's using a lot of RAM, the answer will be bitmaps of various sorts: draw buffers, decompressed textures, fonts, other graphical assets, and so on. In this case it's just allocated but not yet used heap+stacks, plus 100MB for the code.

Edit: I may be underestimating the role of binary code size. Visual Studio "devenv.exe" is sitting at 2GB of 'image'. Zoom is 500MB. VSCode is 300MB. Much of which are app-specific, not just Windows DLLs.

Tx for the breakdown. I will play around with it later on my windows machine.

But isn't it crazy how we throw out so much memory just because of random buffers? It feels wrong to me

  • As pointed out below, quite a lot of that isn't in RAM - see "working set".

    There's a common noob complaint about "Linux using all my RAM!" where people are confused about the headline free/buffers numbers. If there's a reasonable chance data could be used again soon it's better to leave it in RAM; if the RAM is needed for something else, the current contents will get paged out. Having a chunk of RAM be genuinely unallocated to anything is doing nothing for you.

    • Nitpick: What you're describing is the disk cache. If a process requests more memory than is free, the OS will not page out pages used for the cache, it will simply either release them (if they're on the read cache) or flush them (if they're on the write cache).

Turning these numbers into "memory consumption" gets complicated to the point of being intractable.

The portions that are allocated but not yet used might just be page table entries with no backing memory, making them free. Except for the memory tracking the page table entries. Almost free....

A lot of "image" will be mmapped and clean. Anything you don't actually use from that will be similarly freeish. Anything that's constantly needed will use memory. Except if it's mapped into multiple processes, then it's needed but responsibility is spread out. How do you count an app's memory usage when there's a big chunk of code that needs to sit in RAM as long as any of a dozen processes are running? How do you count code that might be used sometime in the next few minutes or might not be depending on what the user does?

  • This assumes that executable code pages can be shared between processes. I'm skeptical that this is still a notable optimization on modern systems because dynamic linking writes to executable memory to perform relocations in the loaded code. So this would counteract copy on write. And at least with ASLR, the result should be different for each process anyway.

    • ld writes to the GOT. The executable segment where .text lives is not written to (it's position independent code in dynamic libraries).

      ASLR is not an obstacle -- the same exact code can be mapped into different base addresses in different processes, so they can be backed by the same actual memory.

    • Dynamic linking doesn't have to write to code. I'm not familiar with other platforms, but on macOS, relocations are all in data, and any code that needs a relocation will indirect through non-code pages. I assume it's similar on other OSes.

      This optimization is essential. A typical process maps in hundreds of megabytes of code from the OS. There are hundreds of processes running at any given time. Eyeballing the numbers on an older Mac I have here (a newer one would surely be worse) I'd need maybe 50GB of RAM just to hold the code of all the running processes if the pages couldn't be shared.

But I have sublime text open with a hundred files and it's using 12mb.

  • And how does that breakdown in vmmap? I'm guessing that's working set vs. the whole virtual memory allocation (which is definitely always an overestimate and not the same as RAM)

    • Virtual memory doesn't matter at all. It's virtual. You can take 2TB of address space, use 5MB of it, and nothing on the system cares.