I'm doing some research in C++ green threads, mostly boost::coroutine2 and similar POSIX functions like makecontext()/swapcontext(), and planning to implement a C++ green thread library on top of boost::coroutine2. Both require the user code to allocate a stack for every new function/coroutine.
My target platform is x64/Linux. I want my green thread library to be suitable for general use, so the stacks should expand as required (a reasonable upper limit is fine, e.g. 10MB), it would be great if the stacks could shrink when too much memory is unused (not required). I haven't figured out an appropriate algorithm to allocate stacks.
After some googling, I figured out a few options myself:
use split stack implemented by the compiler (gcc -fsplit-stack), but split stack has performance overhead. Go has already moved away from split stack due to performance reasons.
allocate a large chunk of memory with mmap() hope the kernel is smart enough to leave the physical memory unallocated and allocate only when the stacks are accessed. In this case, we are at the mercy of the kernel.
reserve a large memory space with mmap(PROT_NONE) and setup a SIGSEGV signal handler. In the signal handler, when the SIGSEGV is caused by stack access (the accessed memory is inside the large memory space reserved), allocate needed memory with mmap(PROT_READ | PROT_WRITE). Here is the problem for this approach: mmap() isn't asynchronous safe, cannot be called inside a signal handler. It still can be implemented, very tricky though: create another thread during program startup for memory allocation, and use pipe() + read()/write() to send memory allocation information from the signal handler to the thread.
A few more questions about option 3:
I'm not sure the performance overhead of this approach, how well/bad the kernel/CPU performs when the memory space is extremely fragmented due to thousands of mmap() call ?
Is this approach correct if the unallocated memory is accessed in kernel space ? e.g. when read() is called ?
Are there any other (better) options for stack allocation for green threads ? How are green thread stacks allocated in other implementations, e.g. Go/Java ?
The way that glibc allocates stacks for normal C programs is to mmap a region with the following mmap flag designed just for this purpose:
MAP_GROWSDOWN
Used for stacks. Indicates to the kernel virtual memory system
that the mapping should extend downward in memory.
For compatibility, you should probably use MAP_STACK too. Then you don't have to write the SIGSEGV handler yourself, and the stack grows automatically. The bounds can be set as described here What does "ulimit -s unlimited" do?
If you want a bounded stack size, which is normally what people do for signal handlers if they want to call sigaltstack(2), just issue an ordinary mmap call.
The Linux kernel always maps physical pages that back virtual pages, catching the page fault when a page is first accessed (perhaps not in real-time kernels but certainly in all other configurations). You can use the /proc/<pid>/pagemap interface (or this tool I wrote https://github.com/dwks/pagemap) to verify this if you are interested.
Why mmap? When you allocate with new (or malloc) the memory is untouched and definitely not mapped.
const int STACK_SIZE = 10 * 1024*1024;
char*p = new char[STACK_SIZE*numThreads];
p now has enough memory for the threads you want. When you need the memory, start accessing p + STACK_SIZE * i
Related
I am reading mlockall()'s manpage: http://man7.org/linux/man-pages/man2/mlock.2.html
It mentions
Real-time processes that are using mlockall() to prevent delays on page
faults should reserve enough locked stack pages before entering the time-
critical section, so that no page fault can be caused by function calls. This
can be achieved by calling a function that allocates a sufficiently large
automatic variable (an array) and writes to the memory occupied by this array in
order to touch these stack pages. This way, enough pages will be mapped for the
stack and can be locked into RAM. The dummy writes ensure that not even copy-
on-write page faults can occur in the critical section.
I am a bit confused by this statement:
This can be achieved by calling a function that allocates a sufficiently large
automatic variable (an array) and writes to the memory occupied by this array in
order to touch these stack pages.
All the automatic variables (variables on stack) are created "on the fly" on the stack when the function is called. So how can I achieve what the last statement says?
For example, let's say I have this function:
void foo() {
char a;
uint16_t b;
std::deque<int64_t> c;
// do something with those variables
}
Or does it mean before I call any function, I should call a function like this in main():
void reserveStackPages() {
int64_t stackPage[4096/8 * 1024 * 1024];
memset(stackPage, 0, sizeof(stackPage));
}
If yes, does it make a difference if I first allocate the stackPage variable on heap, write and then free? Probably yes, because heap and stack are 2 different region in the RAM?
std::deque exists above is just to bring up another related question -- what if I want to reserve memory for things using both stack pages and heap pages. Will calling "heap" version of reserveStackPages() help?
The goal is to minimize all the jitters in the application (yes, I know there are many other things to look at such as TLB miss, etc; just trying to deal with one kind of jitter at once, and slowly progressing into all).
Thanks in advance.
P.S. This is for a low latency trading application if it matters.
You generally don't need to use mlockall, unless you code (more or less hard) real-time applications (I actually never used it).
If you do need it, you'll better code in C (not in genuine C++) the most real-time parts of your code, because you surely want to understand the details of memory allocation. Notice that unless you dive into std::deque implementation, you don't exactly know where it is sitting (probably most of the data is heap allocated, even if your c is an automatic variable).
You should first understand in details the virtual address space of your process. For that, proc(5) is useful: from inside your process, you'll read /proc/self/maps (see this), from outside (e.g. some terminal) you'll do cat /proc/1234/maps for a process of pid 1234. Or use pmap(1).
because heap and stack are 2 different regions in the RAM?
In fact, your process' address space contains many segments (listed in /proc/1234/maps), much more that two. Typically every dynamically linked shared library (such as libc.so) brings a few segments.
Try cat /proc/self/maps and cat /proc/$$/maps in your terminal to get a better intuition about virtual address spaces. On my machine, the first gives 19 segments of the cat process -each displayed as a line- and the second 97 segments of the zsh (my shell) process.
To ensure that your stack has enough space, you indeed could call a function allocating a large enough automatic variable, like your reserveStackPages. Beware that call stacks are practically of limited size (a few megabytes usually, see also setrlimit(2)).
If you really need mlockall (which is unlikely) you might consider linking statically your program (to have less segments in your virtual address space).
Look also into madvise(2) (and perhaps mincore(2)). It is generally much more useful than mlockall. BTW, in practice, most of your virtual memory is in RAM (unless your system experiments thrashing, and then you'll see it immediately).
Read also Operating Systems: Three Easy Pieces to understand the role of paging.
PS. Nano-second sensitive applications does not make much sense (because of cache misses that the software does not control).
I have the following loop, which pops a C++ concurrent queue I have, from the implementation here. https://juanchopanzacpp.wordpress.com/2013/02/26/concurrent-queue-c11/
while (!interrupted)
{
pxData data = queue->pop();
if (data.value == -1)
{
break; // exit loop on terminating condition
}
usleep(7000); // stub to simulate processing
}
I am looking at the memory history using System Monitor in CentOS7.
I'm trying to free up the memory taken up by the queue, after reading the value from the queue. However, as the following while loop runs, I don't see the memory usage going down. I've verified that the queue length does go down.
It does go down, however, when -1 is encountered and the loop exits. (program is still running) But I can't have this, because where usleep is, I want to do some intensive processing.
Question: Why doesn't the memory occupied by data get free-ed? (according to System Monitor) Isn't the stack allocated memory supposed to be free-ed when the variable goes out of scope?
The struct is defined as follows, and populated at the beginning of the program.
typedef struct pxData
{
float value; // -1 value terminates the loop
float x, y, z;
std::complex<float> valueData[65536];
} pxData;
It's populated with ~10000 pxData, which roughly translates to 5GB. System only has ~8GB.
So it's important that the memory is free-ed up for doing other processing in the system.
There are a few things at play here.
Virtual Memory
First, you need to understand that just because your program is "using" 5 GB of memory does not mean that there are only 3 GB of RAM left for other programs. Virtual memory means that those 5 GB might be only 1 GB of actual "resident" data, and the other 4 GB may actually be on disk rather than in RAM. So it's important to look at the "resident set size" rather than the "virtual size" when you're looking at your program. And note that if your system actually runs low on RAM, the OS may shrink the RSS of some programs by "paging out" some of their memory. So don't worry too much about "5 GB" appearing in the system monitor--worry if you have a real, concrete performance problem.
Heap Allocation
The second aspect is why your virtual size does not decrease as you remove items from the queue. We can guess that you put those elements into the queue by creating them with malloc or new one-by-one, then pushing them onto the back of the queue. This means that the first element you allocated will come out of the queue first. And that in turn means that when you have drained 90% of the queue, your memory allocation might look like this:
[program|------------------unused-------------------|pxData]
The problem here is that in the real world, just because you free or delete something does not mean the operating system instantly reclaims that memory. In fact, it may not be able to reclaim any unused spans unless they are at the "end" (i.e. most recently allocated). Since C++ does not have garbage collection and cannot move items around in memory without your consent, you end up with this big "hole" in your program's virtual memory. That hole would be used to satisfy future memory allocation requests, but if you haven't got any, it just sits there, until the queue is completely empty:
[program|------------------unused--------------------------]
Then the system is able to shrink your virtual address space back down:
[program]
Which brings you back to where you started.
Solutions
If you want to "fix" this, one option is to allocate your memory in "reverse", i.e. put the last items allocated into the front of the queue.
Another option is to allocate the elements for the queue via mmap, which is something that e.g. Linux will do automatically for allocations which are "large." You can change the threshold for this by calling mallopt(3) with M_MMAP_THRESHOLD and setting it to be a little bit smaller than your struct size. This makes the allocations independent of each other, so the OS can reclaim them individually. This technique can even be applied to existing programs without recompilation, so is often useful if you need to solve this problem in a program you cannot modify.
A C++ implementation would call some operator delete to release dynamically allocated (using some operator new) memory. In several C++ standard libraries, new calls malloc and delete calls free.
(I am focusing with a Linux point of view, but the principles are similar on other OSes)
But while malloc (or ::operator new) is sometimes asking the OS kernel some more memory by system calls changing the virtual address space like mmap(2), free (or ::operator delete) is often simply marking the released memory zone as re-available to future calls to malloc (or to new)
So from the kernel point of view (e.g. as seen thru /proc/, see proc(5)...), the virtual address space is not changing, and the memory remains consumed, even if inside the application it is marked as "freed" and will be reused at some future allocation (by future calls to malloc or new)
And most C++ standard containers are internally using heap data. In particular your local (stack-allocated) std::map or std::vector (or std::deque) variable will call new & delete for internal data.
BTW, I find quite strange your declaration. Unless every struct pxData has exactly 65536 used valueData slots, I would suggest to use some std::vector so have
std::vector<std::complex<float>> valueData;
and improve your code accordingly. You'll probably need to do some valueData.reserve(somesize); and/or valueData.resize(somesize); and/or valueData.push_back(somecomplexnumber); etc....
I am a student of a system software faculty. Now I'm developing a memory manager for Windows. Here's my simple implementation of malloc() and free():
HANDLE heap = HeapCreate(0, 0, 0);
void* hmalloc(size_t size)
{
return HeapAlloc(heap, 0, size);
}
void hfree(void* memory)
{
HeapFree(heap, 0, memory);
}
int main()
{
int* ptr1 = (int*)hmalloc(100*sizeof(int));
int* ptr2 = (int*)hmalloc(100*sizeof(int));
int* ptr3 = (int*)hmalloc(100*sizeof(int));
hfree(ptr2);
hfree(ptr3);
hfree(ptr1);
return 0;
}
It works fine. But I can't understand is there a reason to use multiple heaps? Well, I can allocate memory in the heap and get the address to an allocated memory chunk. But here I use ONE heap. Is there a reason to use multiple heaps? Maybe for multi-threaded/multi-process applications? Please explain.
The main reason for using multiple heaps/custom allocators are for better memory control. Usually after lots of new/delete's the memory can get fragmented and loose performance for the application (also the app will consume more memory). Using the memory in a more controlled environment can reduce heap fragmentation.
Also another usage is for preventing memory leaks in the application, you could just free the entire heap you allocated and you don't need to bother with freeing all the object allocated there.
Another usage is for tightly allocated objects, if you have for example a list then you could allocate all the nodes in a smaller dedicated heap and the app will gain performance because there will be less cache misses when iterating the nodes.
Edit: memory management is however a hard topic and in some cases it is not done right. Andrei Alexandrescu had a talk at one point and he said that for some application replacing the custom allocator with the default one increased the performance of the application.
This is a good link that elaborates on why you may need multiple heap:
https://caligari.dartmouth.edu/doc/ibmcxx/en_US/doc/libref/concepts/cumemmng.htm
"Why Use Multiple Heaps?
Using a single runtime heap is fine for most programs. However, using multiple
heaps can be more efficient and can help you improve your program's performance
and reduce wasted memory for a number of reasons:
1- When you allocate from a single heap, you may end up with memory blocks on
different pages of memory. For example, you might have a linked list that
allocates memory each time you add a node to the list. If you allocate memory for
other data in between adding nodes, the memory blocks for the nodes could end up
on many different pages. To access the data in the list, the system may have to
swap many pages, which can significantly slow your program.
With multiple heaps, you can specify which heap you allocate from. For example,
you might create a heap specifically for the linked list. The list's memory blocks
and the data they contain would remain close together on fewer pages, reducing the
amount of swapping required.
2- In multithread applications, only one thread can access the heap at a time to
ensure memory is safely allocated and freed. For example, say thread 1 is
allocating memory, and thread 2 has a call to free. Thread 2 must wait until
thread 1 has finished its allocation before it can access the heap. Again, this
can slow down performance, especially if your program does a lot of memory
operations.
If you create a separate heap for each thread, you can allocate from them
concurrently, eliminating both the waiting period and the overhead required to
serialize access to the heap.
3- With a single heap, you must explicitly free each block that you allocate. If you
have a linked list that allocates memory for each node, you have to traverse the
entire list and free each block individually, which can take some time.
If you create a separate heap for that linked list, you can destroy it with a
single call and free all the memory at once.
4- When you have only one heap, all components share it (including the IBM C and
C++ Compilers runtime library, vendor libraries, and your own code). If one
component corrupts the heap, another component might fail. You may have trouble
discovering the cause of the problem and where the heap was damaged.
With multiple heaps, you can create a separate heap for each component, so if
one damages the heap (for example, by using a freed pointer), the others can
continue unaffected. You also know where to look to correct the problem."
A reason would be the scenario that you need to execute a program internally e.g. running simulation code. By creating your own heap you could allow that heap to have execution rights which by default for security reasons is turned off. (Windows)
You have some good thoughts and this'd work for C but in C++ you have destructors, it is VERY important they run.
You can think of all types as having constructors/destructors, just that logically "do nothing".
This is about allocators. See "The buddy algorithm" which uses powers of two to align and re-use stuff.
If I allocate 4 bytes somewhere, my allocator might allocate a 4kb section just for 4 byte allocations. That way I can fit 1024 4 byte things in the block, if I need more add another block and so forth.
Ask it for 4kb and it wont allocate that in the 4byte block, it might have a separate one for larger requests.
This means you can keep big things together. If I go 17 bytes then 13 bytes the 1 byte and the 13byte gets freed, I can only stick something in there of <=13 bytes.
Hence the buddy system and powers of 2, easy to do using lshifts, if I want a 2.5kb block, I allocate it as the smallest power of 2 that'll fit (4kb in this case) that way I can use the slot afterwards for <=4kb items.
This is not for garbage collection, this is just keeping things more compact and neat, using your own allocator can stop calls to the OS (depending on the default implementation of new and delete they might already do this for your compiler) and make new/delete very quick.
Heap-compacting is very different, you need a list of every pointer that points to your heap, or some way to traverse the entire memory graph (like spits Java) so when you move stuff round and "compact" it you can update everything that pointed to that thing to where it currently is.
The only time I ever used more than one heap was when I wrote a program that would build a complicated data structure. It would have been non-trivial to free the data structure by walking through it and freeing the individual nodes, but luckily for me the program only needed the data structure temporarily (while it performed a particular operation), so I used a separate heap for the data structure so that when I no longer needed it, I could free it with one call to HeapDestroy.
While investigating a memory link in one of our projects, I've run into a strange issue. Somehow, the memory allocated for objects (vector of shared_ptr to object, see below) is not fully reclaimed when the parent container goes out of scope and can't be used except for small objects.
The minimal example: when the program starts, I can allocate a single continuous block of 1.5Gb without problem. After I use the memory somewhat (by creating and destructing an number of small objects), I can no longer do big block allocation.
Test program:
#include <iostream>
#include <memory>
#include <vector>
using namespace std;
class BigClass
{
private:
double a[10000];
};
void TestMemory() {
cout<< "Performing TestMemory"<<endl;
vector<shared_ptr<BigClass>> list;
for (int i = 0; i<10000; i++) {
shared_ptr<BigClass> p(new BigClass());
list.push_back(p);
};
};
void TestBigBlock() {
cout<< "Performing TestBigBlock"<<endl;
char* bigBlock = new char [1024*1024*1536];
delete[] bigBlock;
}
int main() {
TestBigBlock();
TestMemory();
TestBigBlock();
}
Problem also repeats if using plain pointers with new/delete or malloc/free in cycle, instead of shared_ptr.
The culprit seems to be that after TestMemory(), the application's virtual memory stays at 827125760 (regardless of number of times I call it). As a consequence, there's no free VM regrion big enough to hold 1.5 GB. But I'm not sure why - since I'm definitely freeing the memory I used. Is it some "performance optimization" CRT does to minimize OS calls?
Environment is Windows 7 x64 + VS2012 + 32-bit app without LAA
Sorry for posting yet another answer since I am unable to comment; I believe many of the others are quite close to the answer really :-)
Anyway, the culprit is most likely address space fragmentation. I gather you are using Visual C++ on Windows.
The C / C++ runtime memory allocator (invoked by malloc or new) uses the Windows heap to allocate memory. The Windows heap manager has an optimization in which it will hold on to blocks under a certain size limit, in order to be able to reuse them if the application requests a block of similar size later. For larger blocks (I can't remember the exact value, but I guess it's around a megabyte) it will use VirtualAlloc outright.
Other long-running 32-bit applications with a pattern of many small allocations have this problem too; the one that made me aware of the issue is MATLAB - I was using the 'cell array' feature to basically allocate millions of 300-400 byte blocks, causing exactly this issue of address space fragmentation even after freeing them.
A workaround is to use the Windows heap functions (HeapCreate() etc.) to create a private heap, allocate your memory through that (passing a custom C++ allocator to your container classes as needed), and then destroy that heap when you want the memory back - This also has the happy side-effect of being very fast vs delete()ing a zillion blocks in a loop..
Re. "what is remaining in memory" to cause the issue in the first place: Nothing is remaining 'in memory' per se, it's more a case of the freed blocks being marked as free but not coalesced. The heap manager has a table/map of the address space, and it won't allow you to allocate anything which would force it to consolidate the free space into one contiguous block (presumably a performance heuristic).
There is absolutely no memory leak in your C++ program. The real culprit is memory fragmentation.
Just to be sure(regarding memory leak point), I ran this program on Valgrind, and it did not give any memory leak information in the report.
//Valgrind Report
mantosh#mantosh4u:~/practice$ valgrind ./basic
==3227== HEAP SUMMARY:
==3227== in use at exit: 0 bytes in 0 blocks
==3227== total heap usage: 20,017 allocs, 20,017 frees, 4,021,989,744 bytes allocated
==3227==
==3227== All heap blocks were freed -- no leaks are possible
Please find my response to your query/doubt asked in original question.
The culprit seems to be that after TestMemory(), the application's
virtual memory stays at 827125760 (regardless of number of times I
call it).
Yes, real culprit is hidden fragmentation done during the TestMemory() function.Just to understand the fragmentation, I have taken the snippet from wikipedia
"
when free memory is separated into small blocks and is interspersed by allocated memory. It is a weakness of certain storage allocation algorithms, when they fail to order memory used by programs efficiently. The result is that, although free storage is available, it is effectively unusable because it is divided into pieces that are too small individually to satisfy the demands of the application.
For example, consider a situation wherein a program allocates 3 continuous blocks of memory and then frees the middle block. The memory allocator can use this free block of memory for future allocations. However, it cannot use this block if the memory to be allocated is larger in size than this free block."
The above explains paragraph explains very nicely about memory fragmentation.Some allocation patterns(such as frequent allocation and deal location) would lead to memory fragmentation,but its end impact(.i.e. memory allocation 1.5GBgets failed) would greatly vary on different system as different OS/heap manager has different strategy and implementation.
As an example, your program ran perfectly fine on my machine(Linux) however you have encountered the memory allocation failure.
Regarding your observation on VM size remains constant: VM size seen in task manager is not directly proportional to our memory allocation calls. It mainly depends on the how much bytes is in committed state. When you allocate some dynamic memory(using new/malloc) and you do not write/initialize anything in those memory regions, it would not go committed state and hence VM size would not get impacted due to this. VM size depends on many other factors and bit complicated so we should not rely completely on this while understanding about dynamic memory allocation of our program.
As a consequence, there's no free VM regrion big enough to hold 1.5
GB.
Yes, due to fragmentation, there is no contiguous 1.5GB memory. It should be noted that total remaining(free) memory would be more than 1.5GB but not in fragmented state. Hence there is not big contiguous memory.
But I'm not sure why - since I'm definitely freeing the memory I used.
Is it some "performance optimization" CRT does to minimize OS calls?
I have explained about why it may happen even though you have freed all your memory. Now in order to fulfil user program request, OS will call to its virtual memory manager and try to allocate the memory which would be used by heap memory manager. But grabbing the additional memory does depend on many other complex factor which is not very easy to understand.
Possible Resolution of Memory Fragmentation
We should try to reuse the memory allocation rather than frequent memory allocation/free. There could be some patterns(like a particular request size allocation in particular order) which may lead overall memory into fragmented state. There could be substantial design change in your program in order to improve memory fragmentation. This is complex topic and require internal understanding of memory manager to understand the complete root cause of such things.
However there are tools exists on Windows based system which I am not much aware. But I found one excellent SO post regarding the which tool(on windows) can be useful to understand and check the fragmentation status of your program by yourself.
https://stackoverflow.com/a/1684521/2724703
This is not memory leak. The memory U used was allocated by C\C++ Runtime. The Runtime apply a a bulk of memory from OS once and then each new you called will allocated from that bulk memory. when delete one object, the Runtime not return memory to OS immediately, it may hold that memory for performance.
There is nothing here which indicates a genuine "leak". The pattern of memory you describe is not unexpected. Here are a few points which might help to understand. What happens is highly OS dependent.
A program often has a single heap which can be extended or shrunk in length. It is however one contiguous memory area, so changing the size is just changing where the end of the heap is. This makes it very difficult to ever "return" memory to the OS, since even one little tiny object in that space will prevent its shrinking. On Linux you can lookup the function 'brk' (I know you're on Windows, but I presume it does something similar).
Large allocations are often done with a different strategy. Rather than putting them in the general purpose heap, an extra block of memory is created. When it is deleted this memory can actually be "returned" to the OS since its guaranteed nothing is using it.
Large blocks of unused memory don't tend to consume a lot of resources. If you generally aren't using the memory any more they might just get paged to disk. Don't presume that because some API function says you're using memory that you are actually consuming significant resources.
APIs don't always report what you think. Due to a variety of optimizations and strategies it may not actually be possible to determine how much memory is in use and/or available on a system at a particular moment. Unless you have intimate details of the OS you won't know for sure what those values mean.
The first two points can explain why a bunch of small blocks and one large block result in different memory patterns. The latter points indicate why this approach to detecting leaks is not useful. To detect genuine object-based "leaks" you generally need a dedicated profiling tool which tracks allocations.
For example, in the code provided:
TestBigBlock allocates and deletes array, assume this uses a special memory block, so memory is returned to OS
TestMemory extends the heap for all the small objects, and never returns any heap to the OS. Here the heap is entirely available from the applications point-of-view, but from the OS's point of view it is assigned to the application.
TestBigBlock now fails, since although it would use a special memory block, it shares the overall memory space with heap, and there just isn't enough left after 2 is complete.
Is it possible for stack space allocated by CreateThread to interfere with the usage of VirtualAlloc? I can't find any discussion or documentation explaining precisely where stack space is allowed to be allocated...
The following more precisely illustrates my question:
uint8_t *baseA = (uint8_t*)VirtualAlloc(NULL,1,MEM_RESERVE,PAGE_NOACCESS);
// Create a thread with the default stack size
HANDLE hThread = CreateThread(NULL,0,SomeThreadProc,NULL,NULL,NULL);
// Possibly create even more threads here.
// Can this ever fail in the absence of other allocators? It doesn't here...
uint8_t *baseB = (uint8_t*)VirtualAlloc(NULL,1,MEM_RESERVE,PAGE_NOACCESS);
// Furthermore, in this test, baseB-baseA == 65536 (unless the debugger did something),
// so nothing appeared between baseA and baseB... not even enough space for the
// full 64kb of wastage, as baseA points to 4096 bytes by itself
If it does in fact use some analogue of VirtualAlloc, is there a way to change how Windows allocates stack space in a given process?
Stack space can be allocated anywhere in the address space of the process. There is no documentation on this now and it is unlikely that such documentation will appear in the future.
You can safely assume that creation of the thread and virtual alloc are independent. If this would not be the case, a lot of things would be broken. Allocator cannot give out overlapping address ranges. This is unthinkable. The problem is somewhere else.
The only thing that might look like correlation - amount of memory used and virtual address space fragmentation. In this case the latest request will simply fail.
I worked on a memory analysis utilities.
This picture shows distribution of the numbers of virtual allocations per size of the allocation.
This is example of the address space contents for a 32-bit process (blue - committed, magenta - reserved, green is a free memory).
What I write here is based on a real experience.
the windows NT kernel treats memory alloc operations on a high interrupt priority, also in a thread safe manner.
That means only one thread of a process can allocate memory at the same time, which makes all allocation processes thread safe (in theory).
there shouldn't be any interferences between stack allocation and virtual allocation.
Also you should keep in mine that you can allocate 1GB of space but your program still only uses it's 2mb RAM.
That's because windows "pre allocates" virtual space, but it doesen't assign it until you use it (write on it).
Actually the memory management is alot more complicated but for now you can be shure that no allocation operations should interfere, ever, since windows is locking your process onto one core, delaying all other threads alloc requests, as long as allocation is processed. (deadlock)
*EDIT: That also means that allocation and de-allocation is kinda a performance needing process if you allocate millions of small bits. It's always better to allocate/de-allocate larger memory areas, because of this deadlock behavior.