Logo Questions Linux Laravel Mysql Ubuntu Git Menu
 

jemalloc, mmap and shared memory?

Can jemalloc be modified to allocate from shared memory? The FreeBSD function dallocx() implies you can provide a pointer to use for allocation, but I don't see an obvious way to tell jemalloc to restrict all allocations from that memory (nor set a size, etc).

The dallocx() function causes the memory referenced by ptr to be made available for future allocations.

If not, what is the level of effort for such a feature? I'm struggling to find an off-the-shelf allocation scheme that can allocate from a shared memory section that I provided.

Similarly, can jemalloc be configured to allocate from a locked region of memory to prevent swapping?

Feel free to point me to relevant code sections that require modification and provide any ideas or suggestions.

The idea I am exploring is — since you can create arenas/heaps for allocating in a threaded environment, as jemalloc does to minimize contention, the concept seems scalable to allocating regions of shared memory in a multiprocessing environment, i.e. I create N regions of shared memory using mmap(), and I want to leverage the power of jemalloc (or any allocation scheme) to allocate as efficiently as possible, with minimum thread contention, from those one of those shared regions, i.e. if threads/processes are not accessing the same shared regions and arenas, the chance for contention is minimal and speed of the malloc operation is increased.

This is different than a global pool alloc with malloc() API since usually these require a global lock effectively serializing the user-space. I'd like to avoid this.

edit 2:

Ideally an api like this:

// init the alloc context to two shmem pools
ctx1 = alloc_init(shm_region1_ptr);
ctx2 = alloc_init(shm_region2_ptr);

(... bunch of code determines pool 2 should be used, based on some method
of pool selection which can minimize possibility of lock contention
with other processes allocating shmem buffers)

// allocate from pool2
ptr = malloc(ctx2, size)
like image 561
trench_digger Avatar asked Jun 15 '15 01:06

trench_digger


People also ask

Is jemalloc scalable to multiprocessing environments?

The idea I am exploring is — since you can create arenas/heaps for allocating in a threaded environment, as jemalloc does to minimize contention, the concept seems scalable to allocating regions of shared memory in a multiprocessing environment, i.e.

What is the difference between shmget and mmap?

And why? Both methods are viable. mmap method is a little bit more restrictive then shmget, but easier to use. shmget is the old System V shared memory model and has the widest support. mmap / shm_open is the new POSIX way to do shared memory and is easier to use.

What does mmap (2) do to jemalloc?

It also makes jemalloc use mmap(2)or equivalent in a more greedy way, mapping larger chunks in one go.

Should we retain unused virtual memory in jemalloc?

If true, retain unused virtual memory for later reuse rather than discarding it by calling munmap(2)or equivalent (see stats.retainedfor related details). It also makes jemalloc use mmap(2)or equivalent in a more greedy way, mapping larger chunks in one go.


1 Answers

Yes. But this was not true when you asked the question.

Jemalloc 4 (released in August of 2015) has a couple of mallctl namespaces that would be useful for this purpose; they allow you to specify per-arena, application-specific chunk allocation hooks. In particular, the arena.<i>.chunk_hooks namespace and the arenas.extend mallctl options are of use. An integration test exists that demonstrates how to consume this API.

Regarding the rationale, I would expect that the effective "messaging" overhead required to understand where contention on any particular memory segment lies would be similar to the overhead of just contending, since you're going to degrade into contending on a cache line to accurately update the "contention" value of a particular arena.

Since jemalloc already employs a number of techniques to reduce contention, you could get a similar behavior in a highly threaded environment by creating additional arenas with opt.narenas. This would reduce contention as fewer threads would be mapped to an arena, but since threads are effectively round-robined, it's possible you get to hot-spots anyway.

To get around this, you could do your contention counting and hotspot detection, and simply use the thread.arena mallctl interface to switch a thread onto an arena with less contention.

like image 186
dho Avatar answered Sep 29 '22 11:09

dho