Can shared memory be swapped out under memory pressure? - linux

Under high memory pressure, if there are processes with massive shared memory, would linux swap out these shared memory pages just like it would regular memory pages?
Does swapping behavior differ for shared memory in any way?
What about when hugepages are being used by the process?
Would that make any difference in swapping policy under memory pressure?

Related

Find exact physical memory usage in Ubuntu/Linux

(I'm new to Linux)
Say I've 1300 MB memory, on a Ubuntu machine. OS and other default programs consumes 300 MB memory and 1000 MB is free for my own applications.
I installed my application and I could configure it to use 700 MB memory, when the application starts.
However I couldn't verify its actual memory usage. Even I disabled swap space.
The "VIRT" value shows a huge value and "RES", "SHR", "%MEM" shows very less value.
It is difficult to find actual physical memory usage, similar to "Resource monitor" in Windows, which will say my application is using 700 MB memory.
Is there any way to find actual physical memory in Ubuntu/Linux ?
TL;DR - Virtual memory is complicated.
The best measure of a Linux processes current usage of physical memory is RES.
The RES value represents the sum of all of the processes pages that are currently resident in physical memory. It includes resident code pages and resident data pages. It also includes shared pages (SHR) that are currently RAM resident, though these pages cannot be exclusively ascribed to >>this<< process.
The VIRT value is actually the sum of all notionally allocated pages for the process, and it includes pages that are currently RAM resident, pages that are currently swapped to disk.
See https://stackoverflow.com/a/56351211/1184752 for another explanation.
Note that RES is giving you (roughly) instantaneous RAM usage. That is what you asked about ...
The "actual" memory usage over time is more complicated because the OS's virtual memory subsystem is typically be swapping pages in and out according to demand. So, for example, some of your application's pages may not have been accesses recently, and the OS may then swap them out (to swap space) to free up RAM for other pages required by your application ... or something else.
The VIRT value while actually representing virtual address space, is a good approximation of total (virtual) memory usage. However, it may be an over-estimate:
Some pages in a processes address space are shared between multiple processes. This includes read-only code segments, pages shared between parent and child processes between vfork and exec, and shared memory segments created using mmap.
Some pages may be set to have illegal access (e.g. for stack red-zones) and may not be backed by either RAM or swap device pages.
Some pages of the address space in certain states may not have been committed to either RAM or disk yet ... depending on how the virtual memory system is implemented. (Consider the case where a process requests a huge memory segment and neither reads from it or writes to it. It is possible that the virtual memory implementation will not allocate RAM pages until the first read or write in the page. And if you use lazy swap reservation, swap pages not be committed either. But beware that you can get into trouble with lazy swap reservation.)
VIRT can also be under-estimate because the OS usually reserves swap space for all pages ... whether they are currently swapped in or swapped out. So if you count the RAM and swap versions of a given page as separate units of storage, VIRT usually underestimates the total storage used.
Finally, if your real goal is to limit your application to using at most
700 MB (of virtual address space) then you can use ulimit -v ... to do this. If the application tries to request memory beyond its limit, the request fails.

mprotect(addr, size, PROT_NONE) for guard pages and its memory consumption

I allocated some memory using memalign, and I set the last page as a guard page using mprotec(adde, size, PROT_NONE), so this page is inaccessible.
Does the inaccessible page consume physical memory? In my opinion, the kernel can offline the physical pages safely, right?
I also tried madvise(MADV_SOFT_OFFLINE) to manually offline the physical memory but the function always fails.
Can anybody tell me the internal behavior of kernel with mprotect(PROT_NONE), and how to offline the physical memory to save physical memory consumption?
Linux applications are using virtual memory. Only the kernel is managing physical RAM. Application code don't see the physical RAM.
A segment protected with mprotect & PROT_NONE won't consume any RAM.
You should allocate your segment with mmap(2) (maybe you want MAP_NORESERVE). Mixing memalign with mprotect may probably break libc invariants.
Read carefully madvise(2) man page. MADV_SOFT_OFFLINE may require a specially configured kernel.

Shared memory marked as virtual memory?

I run a program which allocates 64MB as shared memory for IPC communication. pmap shows that chunk of 64MB is allocated. However, "top" shows the RES memory of the proc is just about 40MB! I conclude the shared memory is marked as VIRT. But why? There Linux still has more than 1GB RAM available.
Have you actually used any of that 64MB yet? Linux defers allocation.
cf. Does malloc lazily create the backing pages for an allocation on Linux (and other platforms)?
Linux doesn't load all memory the process "obtain" to RAM , it load memory form virtual place to RAM just when you program refer that block of memory. Here "memory" means private mem & shared mem both.
I haven't done any experiments to verify the above opinion, but I have seen this in many places like SO, and I do believe it . Just FYI.
Shared memory is, just like most if not all of the memory userland programs deal with, virtual. Only active pages need to be mapped to physical (i.e. resident memory). Doing differently would be a waste of resources.
The only exception is when the process specifically locks the pages in RAM with mlock.

Increase of virtual memory without increse of VmSize

I searched for my problem in Google and at this site but i still don't understand the solution.
I have piece of MPI program which RECV some data. Program crashes on big arrays with error of insufficient virtual memory, and so i started to consider /proc/self/status file.
Before MPI_RECV it was:
Name: model.exe
VmPeak: 841640 kB
VmSize: 841640 kB
VmHWM: 15100 kB
VmRSS: 15100 kB
VmData: 760692 kB
And after:
Name: model.exe
VmPeak: 841640 kB
VmSize: 841640 kB
VmHWM: 719980 kB
VmRSS: 719980 kB
VmData: 760692 kB
I test it on Ubuntu and through System Monitor i saw this memory increasing. But i was confused that there are no changes in VmSize(and VmPeak) parameters.
And the question is - what is the indicator of real memory usage?
Does it mean, that true indicator is VmRSS? (and VmSize is only allocated but still not used memory)
(The possible solution to your problem is the last paragraph)
Memory allocation on most modern operating systems with virtual memory is a two-phase process. First, a portion of the virtual address space of the process is reserved and the virtual memory size of the process (VmSize) increases accordingly. This creates entries in the so-called process page table. Pages are initially not associated with phyiscal memory frames, i.e. no physical memory is actually used. Whenever some part of this allocated portion is actually read from or written to, a page fault occurs and the operating system installs (maps) a free page from the physical memory. This increases the resident set size of the process (VmRSS). When some other process needs memory, the OS might store the content of some infrequently used page (the definition of "infrequently used page" is highly implementation-dependent) to some persistent storage (hard drive in most cases, or generally to the swap device) and then unmap up. This process decreases the RSS but leaves VmSize intact. If this page is later accessed, a page fault would again occur and it will be brought back. The virutal memory size only decreases when virtual memory allocations are freed. Note that VmSize also counts for memory mapped files (i.e. the executable file and all shared libraries it links to or other explicitly mapped files) and shared memory blocks.
There are two generic types of memory in a process - statically allocated memory and heap memory. The statically allocated memory keeps all constants and global/static variables. It is part of the data segment, whose size is shown by the VmData metric. The data segment also hosts part of the program heap, where dynamic memory is being allocated. The data segment is continuous, i.e. it starts at a certain location and grows upwards towards the stack (which starts at a very high address and then grows downwards). The problem with the heap in the data segment is that it is managed by a special heap allocator that takes care of subdividing the contiguous data segment into smaller memory chunks. On the other side, in Linux dynamic memory can also be allocated by directly mapping virtual memory. This is usually done only for large allocations in order to conserve memory, since it only allows memory in multiples of the page size (usually 4 KiB) to be allocated.
The stack is also an important source of heavy memory usage, especially if big arrays are allocated in the automatic (stack) storage. The stack starts near the very top of the usable virtual address space and grows downwards. In some cases it could reach the top of the data segment or it could reach the end of some other virtual allocation. Bad things happen then. The stack size is accounted in the VmStack metric and also in the VmSize.
One can summarise it as so:
VmSize accounts for all virtual memory allocations (file mappings, shared memory, heap memory, whatever memory) and grows almost every time new memory is being allocated. Almost, because if the new heap memory allocation is made in the place of a freed old allocation in the data segment, no new virtual memory would be allocated. It decreses whenever virtual allocations are being freed. VmPeak tracks the max value of VmSize - it could only increase in time.
VmRSS grows as memory is being accessed and decreases as memory is paged out to the swap device.
VmData grows as the data segment part of the heap is being utilised. It almost never shrinks as current heap allocators keep the freed memory in case future allocations need it.
If you are running on a cluster with InfiniBand or other RDMA-based fabrics, another kind of memory comes into play - the locked (registered) memory (VmLck). This is memory which is not allowed to be paged out. How it grows and shrinks depends on the MPI implementation. Some never unregister an already registered block (the technical details about why are too complex to be described here), others do so in order to play better with the virtual memory manager.
In your case you say that you are running into a virtual memory size limit. This could mean that this limit is set too low or that you are running into an OS-imposed limits. First, Linux (and most Unixes) have means to impose artificial restrictions through the ulimit mechanism. Running ulimit -v in the shell would tell you what the limit on the virtual memory size is in KiB. You can set the limit using ulimit -v <value in KiB>. This only applies to processes spawned by the current shell and to their children, grandchilren and so on. You need to instruct mpiexec (or mpirun) to propagate this value to all other processes, if they are to be launched on remote nodes. if you are running your program under the control of some workload manager like LSF, Sun/Oracle Grid Engine, Torque/PBS, etc., there are job parameters which control the virtual memory size limit. And last but not least, 32-bit processes are usually restricted to 2 GiB of usable virtual memory.

Difference between "memory cache" and "memory pool"

By reading "understanding linux network internals" and "understanding linux kernel" the two books as well as other references, I am quite confused and need some clarifications about the "memory cache" and "memory pool" techniques.
1) Are they the same or different techniques?
2) If not the same, what makes the difference, or the distinct goals?
3) Also, how does the Slab Allocator come in?
Regarding the slab allocator:
So imagine memory is flat that is you have a block of 4 gigs contiguous memory. Then one of your programs reqeuests a 256 bytes of memory so what the memory allocator has to do is choose a suitable block of 256 bytes from this 4 gigs. So now you your memory looks something like
<============256bytes=======================>
(each = is a contiguous block of memory). Some time passes and a lot of programs operating with the memory require more 256 blocks or more or less so in the end your memory might look like:
<==256==256=256=86=68=121===>
so it gets fragmented and then there is no trace of your beautiful 4gig block of memory - this is fragmentation. Now, what the slab allocator would do is keep track of allocated objects and once they are not used anymore it will say that the memory is free when in fact it will be retained in some sort of List (You might wanna read about FreeLists).
So now imagine that the first program relinquish the 256 bytes allocated and then a new would like to have 256 bytes so instead of allocating a new chunk of the main memory it might re-use the lastly freed 256 bytes without having to go through the burden of searching the physical memory for appropriate contiguous block of space. This is how you essentially implement the memory cache. This is done so that memory fragmentation is reduced overall because you might end up in situation where memory is so fragmented that it is unusable and the memory-manager has to do some magic to get you block of appropriate size. Where as using a slab allocator pro-actively combats (but doesn't eliminate) the problem.
Linux memory allocator A.K.A slab allocator maintains the frequently used list/pool of memory objects of similar or approximate size. slab is giving extra flexibility to programmer to create their own pool of frequently used memory objects of same size and label it as programmer want,allocate, deallocate and finally destroy it.This cache is known to your driver and private to it.But there is a problem, during memory pressure there are high chances of allocation failures which could be not acceptable in some drivers, then what to do better always reserve some memory handy so that we never feel the memory crunch, since kmem cache is more generic pool mechanism we need some one who can always maintain minimum required memory and that's our buddy memory pool .
Lookaside Caches - The cache manager in the Linux kernel is sometimes called the slab allocator. You might end up allocating many objects of the same size over and over so by using this mechanism you just can allocate many objects in the same size and then use them later, without the need to allocate many objects over and over.
Memory Pool is just a form of lookaside cache that tries to always keep a list of memory around for use in emergencies, so when the memory pool is created, the allocation functions (slab allocators) create a pool of preallocated objects so you can acquire them when you need.

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