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Carrier Migration

The ERTS memory allocators manage memory blocks in two types of raw memory chunks. We call these chunks of raw memory carriers. Singleblock carriers which only contain one large block, and multiblock carriers which contain multiple blocks. A carrier is typically created using mmap() on unix systems. However, how a carrier is created is of minor importance. An allocator instance typically manages a mixture of single- and multiblock carriers.

Problem

When a carrier is empty, i.e. contains only one large free block, it is deallocated. Since multiblock carriers can contain both allocated blocks and free blocks at the same time, an allocator instance might be stuck with a large amount of poorly utilized carriers if the memory load decreases. After a peak in memory usage it is expected that not all memory can be returned since the blocks still allocated are likely to be dispersed over multiple carriers. Such poorly utilized carriers can usually be reused if the memory load increases again. However, since each scheduler thread manages its own set of allocator instances, and memory load is not necessarily correlated to CPU load, we might get into a situation where there are lots of poorly utilized multiblock carriers on some allocator instances while we need to allocate new multiblock carriers on other allocator instances. In scenarios like this, the demand for multiblock carriers in the system might increase at the same time as the actual memory demand in the system has decreased which is both unwanted and quite unexpected for the end user.

Solution

In order to prevent scenarios like this we've implemented support for migration of multiblock carriers between allocator instances of the same type.

Management of Free Blocks

In order to be able to remove a carrier from one allocator instance and add it to another we need to be able to move references to the free blocks of the carrier between the allocator instances. The allocator instance specific data structure referring to the free blocks it manages often refers to the same carrier from multiple places. For example, when the address order bestfit strategy is used this data structure is a binary search tree spanning all carriers that the allocator instance manages. Free blocks in one specific carrier can be referred to from potentially every other carrier that is managed, and the amount of such references can be huge. That is, the work of removing the free blocks of such a carrier from the search tree will be huge. One way of solving this could be not to migrate carriers that contain lots of free blocks, but this would prevent us from migrating carriers that potentially need to be migrated in order to solve the problem we set out to solve.

By using one data structure of free blocks in each carrier and an allocator instance-wide data structure of carriers managed by the allocator instance, the work needed in order to remove and add carriers can be kept to a minimum. When migration of carriers is enabled on a specific allocator type, we require that an allocation strategy with such an implementation is used. Currently we've implemented this for three different allocation strategies. All of these strategies use a search tree of carriers sorted so that we can find the carrier with the lowest address that can satisfy the request. Internally in carriers we use yet another search tree that either implement address order first fit, address order best fit, or best fit. The abbreviations used for these different allocation strategies are aoff, and aoffcaobf, aoffcbf.

Carrier Pool

In order to migrate carriers between allocator instances we move them through a pool of carriers. In order for a carrier migration to complete, one scheduler needs to move the carrier into the pool, and another scheduler needs to take the carrier out of the pool.

The pool is implemented as a lock-free, circular, double linked, list. The list contains a sentinel which is used as the starting point when inserting to, or fetching from, the pool. Carriers in the pool are elements in this list.

The list can be modified by all scheduler threads simultaneously. During modifications the double linked list is allowed to get a bit "out of shape". For example, following the next pointer to the next element and then following the prev pointer does not always take you back to were you started. The following is however always true:

  • Repeatedly following next pointers will eventually take you to the sentinel.
  • Repeatedly following prev pointers will eventually take you to the sentinel.
  • Following a next or a prev pointer will take you to either an element in the pool, or an element that used to be in the pool.

When inserting a new element we search for a place to insert the element by only following next pointers, and we always begin by skipping the first element encountered. When trying to fetch an element we do the same thing, but instead only follow prev pointers.

By going different directions when inserting and fetching, we avoid contention between threads inserting and threads fetching as much as possible. By skipping one element when we begin searching, we preserve the sentinel unmodified as much as possible. This is beneficial since all search operations need to read the content of the sentinel. If we were to modify the sentinel, the cache line containing the sentinel would unnecessarily be bounced between processors.

The prev and next fields in the elements of the list contain the value of the pointer, a modification marker, and a deleted marker. Memory operations on these fields are done using atomic memory operations. When a thread has set the modification marker in a field, no-one except the thread that set the marker is allowed to modify the field. If multiple modification markers need to be set, we always begin with next fields followed by prev fields in the order following the actual pointers. This guarantees that no deadlocks will occur.

When a carrier is being removed from a pool, we mark it with a thread progress value that needs to be reached before we are allowed to modify the next and prev fields. That is, until we reach this thread progress we are not allowed to insert the carrier into the pool again, and we are not allowed to deallocate the carrier. This ensures that threads inspecting the pool always will be able to traverse the pool and reach valid elements. Once we have reached the thread progress value that the carrier was tagged with, we know that no threads may have references to it via the pool.

Migration

There exists one pool for each allocator type enabling migration of carriers between scheduler specific allocator instances of the same allocator type.

Each allocator instance keeps track of the current utilization of its multiblock carriers. When the total utilization falls below the "abandon carrier utilization limit" it starts to inspect the utilization of the current carrier when deallocations are made. If also the utilization of the carrier falls below the "abandon carrier utilization limit" it unlinks the carrier from its data structure of available free blocks and inserts the carrier into the pool.

Since the carrier has been unlinked from the data structure of available free blocks, no more allocations will be made in the carrier. The allocator instance putting the carrier into the pool, however, still has the responsibility of performing deallocations in it while it remains in the pool. The allocator instance with this deallocation responsibility is here called the employer.

Each carrier has a flag field containing information about the employing allocator instance, a flag indicating if the carrier is in the pool or not, and a flag indicating if it is busy or not. When the carrier is in the pool, the employing allocator instance needs to mark it as busy while operating on it. If another thread inspects it in order to try to fetch it from the pool, it will skip it if it is busy. When fetching the carrier from the pool, employment will change and further deallocations in the carrier will be redirected to the new employer using the delayed dealloc functionality.

If a carrier in the pool becomes empty, it will be withdrawn from the pool. All carriers that become empty are also always passed to its owning allocator instance for deallocation using the delayed dealloc functionality. Since carriers this way always will be deallocated by the owner that allocated the carrier, the underlying functionality of allocating and deallocating carriers can remain simple and doesn't have to bother about multiple threads. In a NUMA system we will also not mix carriers originating from multiple NUMA nodes.

In short:

  • The allocator instance that created a carrier owns it.
  • An empty carrier is always deallocated by its owner.
  • Ownership never changes.
  • The allocator instance that uses a carrier employs it.
  • An employer can abandon a carrier into the pool.
  • Pooled carriers are not allocated from.
  • Deallocation in a pooled carrier is still performed by its employer.
  • Employment can only change when a carrier is fetched from the pool.

Searching the pool

To harbor real time characteristics, searching the pool is limited. We only inspect a limited number of carriers. If none of those carriers had a free block large enough to satisfy the allocation request, the search will fail. A carrier in the pool can also be busy if another thread is currently doing block deallocation work on the carrier. A busy carrier will also be skipped by the search as it can not satisfy the request. The pool is lock-free and we do not want to block, waiting for the other thread to finish.

Before OTP 17.4

When an allocator instance needs more carrier space, it always begins by inspecting its own carriers that are waiting for thread progress before they can be deallocated. If no such carrier could be found, it then inspects the pool. If no carrier could be fetched from the pool, it will allocate a new carrier. Regardless of where the allocator instance gets the carrier from it the just links in the carrier into its data structure of free blocks.

After OTP 17.4

The old search algorithm had a problem as the search always started at the same position in the pool, the sentinel. This could lead to contention from concurrent searching processes. But even worse, it could lead to a "bad" state when searches fail with a high rate leading to new carriers instead being allocated. These new carriers may later be inserted into the pool due to bad utilization. If the frequency of insertions into the pool is higher than successful fetching from the pool, memory will eventually get exhausted.

This "bad" state consists of a cluster of small and/or highly fragmented carriers located at the sentinel in the pool. The largest free block in such a "bad" carrier is rather small, making it unable to satisfy most allocation requests. As the search always started at the sentinel, any such "bad" carriers that had been left in the pool would eventually cluster together at the sentinel. All searches first have to skip past this cluster of "bad" carriers to reach a "good" carrier. When the cluster gets to the same size as the search limit, all searches will essentially fail.

To counter the "bad cluster" problem and also ease the contention, the search will now always start by first looking at the allocators own carriers. That is, carriers that were initially created by the allocator itself and later had been abandoned to the pool. If none of our own abandoned carrier would do, then the search continues into the pool, as before, to look for carriers created by other allocators. However, if we have at least one abandoned carrier of our own that could not satisfy the request, we can use that as entry point into the pool.

The result is that we prefer carriers created by the thread itself, which is good for NUMA performance. And we get more entry points when searching the pool, which will ease contention and clustering.

To do the first search among own carriers, every allocator instance has two new lists: pooled_list and traitor_list. These lists are only accessed by the allocator itself and they only contain the allocator's own carriers. When an owned carrier is abandoned and put in the pool, it is also linked into pooled_list. When we search our pooled_list and find a carrier that is no longer in the pool, we move that carrier from pooled_list to traitor_list as it is now employed by another allocator. If searching pooled_list fails, we also do a limited search of traitor_list. When finding an abandoned carrier in traitor_list it is either employed or moved back to pooled_list if it could not satisfy the allocation request.

When searching pooled_list and traitor_list we always start at the point where the last search ended. This to avoid clustering problems and increase the probability to find a "good" carrier. As pooled_list and traitor_list are only accessed by the owning allocator instance, they need no thread synchronization at all.

Furthermore, the search for own carriers that are scheduled for deallocation is now done as the last search option. The idea is that it is better to reuse a poorly utilized carrier than to resurrect an empty carrier that was just about to be released back to the OS.

Result

The use of this strategy of abandoning carriers with poor utilization and reusing them in allocator instances with an increased carrier demand is extremely effective and completely eliminates the problems that otherwise sometimes occurred when CPU load dropped while memory load did not.

When using the aoffcaobf or aoff strategies compared to gf or bf, we loose some performance since we get more modifications in the data structure of free blocks. This performance penalty is however reduced using the aoffcbf strategy. A tradeoff between memory consumption and performance is however inevitable, and it is up to the user to decide what is most important.

Further work

It would be quite easy to extend this to allow migration of multiblock carriers between all allocator types. More or less the only obstacle is maintenance of the statistics information.